HPC Technology Compass 2014/15

HighPerformance
Computing2014/15
TechnologyCompass
SciencesRiskAnalysisSimulationBigDataAnalyticsCADHighPerformanceComputing

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More Than 30 Years of Experience in
Scientific Computing
1980 marked the beginning of a decade where numerous start-
ups were created, some of which later transformed into big play-
ers in the IT market. Technical innovations brought dramatic
changes to the nascent computer market. In Tübingen, close to
one of Germany’s prime and oldest universities, transtec was
founded.
In the early days, transtec focused on reselling DEC computers
and peripherals, delivering high-performance workstations to
university institutes and research facilities. In 1987, SUN/Sparc
and storage solutions broadened the portfolio, enhanced by
IBM/RS6000 products in 1991. These were the typical worksta-
tions and server systems for high performance computing then,
used by the majority of researchers worldwide.
In the late 90s, transtec was one of the first companies to offer
highly customized HPC cluster solutions based on standard Intel
architecture servers, some of which entered the TOP 500 list of
the world’s fastest computing systems.
Thus, given this background and history, it is fair to say that
transtec looks back upon a more than 30 years’ experience in sci-
entific computing; our track record shows more than 750 HPC in-
stallations. With this experience, we know exactly what custom-
ers’ demands are and how to meet them. High performance and
ease of management – this is what customers require today. HPC
systems are for sure required to peak-perform, as their name in-
dicates, but that is not enough: they must also be easy to handle.
Unwieldy design and operational complexity must be avoided
or at least hidden from administrators and particularly users of
HPC computer systems.
This brochure focusses on where transtec HPC solutions excel.
transtec HPC solutions use the latest and most innovative tech-
nology. Bright Cluster Manager as the technology leader for uni-
fied HPC cluster management, leading-edge Moab HPC Suite for
job and workload management, Intel Cluster Ready certification
as an independent quality standard for our systems, Panasas
HPC storage systems for highest performance and real ease of
management required of a reliable HPC storage system. Again,
with these components, usability, reliability and ease of man-
agement are central issues that are addressed, even in a highly
heterogeneous environment. transtec is able to provide custom-
ers with well-designed, extremely powerful solutions for Tesla
GPU computing, as well as thoroughly engineered Intel Xeon Phi
systems. Intel’s InfiniBand Fabric Suite makes managing a large
InfiniBand fabric easier than ever before, and Numascale pro-
vides excellent Technology for AMD-based large-SMP Systems
– transtec masterly combines excellent and well-chosen compo-
nents that are already there to a fine-tuned, customer-specific,
and thoroughly designed HPC solution.
Your decision for a transtec HPC solution means you opt for
most intensive customer care and best service in HPC. Our ex-
perts will be glad to bring in their expertise and support to assist
you at any stage, from HPC design to daily cluster operations, to
HPC Cloud Services.
Last but not least, transtec HPC Cloud Services provide custom-
ers with the possibility to have their jobs run on dynamically pro-
vided nodes in a dedicated datacenter, professionally managed
and individually customizable. Numerous standard applications
like ANSYS, LS-Dyna, OpenFOAM, as well as lots of codes like Gro-
macs, NAMD, VMD, and others are pre-installed, integrated into
an enterprise-ready cloud management environment, and ready
to run.
Have fun reading the transtec HPC Compass 2014/15!
TechnologyCompass
Table of Contents and Introduction
High Performance Computing...........................................4
Performance Turns Into Productivity......................................................6
Flexible Deployment With xCAT..................................................................8
Service and Customer Care From A to Z .............................................10
Advanced Cluster Management Made Easy ........... 12
Easy-to-use, Complete and Scalable......................................................14
Cloud Bursting With Bright.........................................................................18
Intelligent HPC Workload Management................... 30
Moab HPC Suite – Basic Edition................................................................32
Moab HPC Suite – Enterprise Edition....................................................34
Moab HPC Suite – Grid Option...................................................................36
Optimizing Accelerators with Moab HPC Suite..............................38
Moab HPC Suite – Application Portal Edition..................................42
Moab HPC Suite – Remote Visualization Edition...........................44
Using Moab With Grid Environments...................................................46
Remote Visualization and
Workflow Optimization....................................................... 52
NICE EnginFrame: A Technical Computing Portal .........................54
Desktop Cloud Virtualization ....................................................................58
Cloud Computing ..............................................................................................62
NVIDIA Grid............................................................................................................66
Intel Cluster Ready ................................................................ 70
A Quality Standard for HPC Clusters......................................................72
Intel Cluster Ready builds HPC Momentum .....................................76
The transtec Benchmarking Center.......................................................80
Parallel NFS................................................................................. 82
The New Standard for HPC Storage .......................................................84
Whats´s New in NFS 4.1? ..............................................................................86
Panasas HPC Storage ......................................................................................88
NVIDIA GPU Computing.....................................................100
What is GPU Computing? .......................................................................... 102
Kepler GK110 – The Next Generation GPU...................................... 104
Introducing NVIDIA Parallel Nsight..................................................... 106
A Quick Refresher on CUDA...................................................................... 118
Intel TrueScale InfiniBand and GPUs.................................................. 124
Intel Xeon Phi Coprocessor.............................................128
The Architecture.............................................................................................. 130
InfiniBand...................................................................................142
High-speed Interconnects ........................................................................ 144
Top 10 Reasons to Use Intel TrueScale InfiniBand ..................... 146
Intel MPI Library 4.0 Performance........................................................ 148
Intel Fabric Suite 7......................................................................................... 152
Numascale.................................................................................158
Background........................................................................................................ 160
NumaConnect Value Proposition......................................................... 162
Technology......................................................................................................... 163
Redefining Scalable OpenMP and MPI.............................................. 169
Glossary.......................................................................................174

5
High Performance Computing (HPC) has been with us from the very beginning of the
computer era. High-performance computers were built to solve numerous problems
which the “human computers” could not handle. The term HPC just hadn’t been coined
yet. More important, some of the early principles have changed fundamentally.
HighPerformance
Computing–Performance
TurnsIntoProductivity
SciencesRiskAnalysisSimulationBigDataAnalyticsCADHighPerformanceComputing

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Variations on the theme: MPP and SMP
Parallel computations exist in two major variants today. Ap-
plications running in parallel on multiple compute nodes are
frequently so-called Massively Parallel Processing (MPP) appli-
cations. MPP indicates that the individual processes can each
utilize exclusive memory areas. This means that such jobs are
predestined to be computed in parallel, distributed across the
nodes in a cluster. The individual processes can thus utilize the
separate units of the respective node – especially the RAM, the
CPU power and the disk I/O.
Communication between the individual processes is imple-
mented in a standardized way through the MPI software inter-
face (Message Passing Interface), which abstracts the underlying
network connections between the nodes from the processes.
However, the MPI standard (current version 2.0) merely requires
source code compatibility, not binary compatibility, so an off-
the-shelf application usually needs specific versions of MPI
libraries in order to run. Examples of MPI implementations are
OpenMPI, MPICH2, MVAPICH2, Intel MPI or – for Windows clusters
– MS-MPI.
If the individual processes engage in a large amount of commu-
nication, the response time of the network (latency) becomes im-
portant. Latency in a Gigabit Ethernet or a 10GE network is typi-
cally around 10 μs. High-speed interconnects such as InfiniBand,
reduce latency by a factor of 10 down to as low as 1 μs. Therefore,
high-speed interconnects can greatly speed up total processing.
The other frequently used variant is called SMP applications.
SMP, in this HPC context, stands for Shared Memory Processing.
It involves the use of shared memory areas, the specific imple-
mentation of which is dependent on the choice of the underly-
ing operating system. Consequently, SMP jobs generally only run
on a single node, where they can in turn be multi-threaded and
thus be parallelized across the number of CPUs per node. For
many HPC applications, both the MPP and SMP variant can be
chosen.
Many applications are not inherently suitable for parallel execu-
tion. In such a case, there is no communication between the in-
dividual compute nodes, and therefore no need for a high-speed
network between them; nevertheless, multiple computing jobs
can be run simultaneously and sequentially on each individual
node, depending on the number of CPUs.
In order to ensure optimum computing performance for these
applications, it must be examined how many CPUs and cores de-
liver the optimum performance.
We find applications of this sequential type of work typically in
the fields of data analysis or Monte-Carlo simulations.
Performance Turns Into Productivity
HPC systems in the early days were much different from those
we see today. First, we saw enormous mainframes from large
computer manufacturers, including a proprietary operating
system and job management system. Second, at universities
and research institutes, workstations made inroads and sci-
entists carried out calculations on their dedicated Unix or
VMS workstations. In either case, if you needed more comput-
ing power, you scaled up, i.e. you bought a bigger machine.
Today the term High-Performance Computing has gained a
fundamentally new meaning. HPC is now perceived as a way
to tackle complex mathematical, scientific or engineering
problems. The integration of industry standard, “off-the-shelf”
server hardware into HPC clusters facilitates the construction
of computer networks of such power that one single system
could never achieve. The new paradigm for parallelization is
scaling out.
Computer-supported simulations of realistic processes (so-
called Computer Aided Engineering – CAE) has established
itself as a third key pillar in the field of science and research
alongside theory and experimentation. It is nowadays incon-
ceivable that an aircraft manufacturer or a Formula One rac-
ing team would operate without using simulation software.
And scientific calculations, such as in the fields of astrophys-
ics, medicine, pharmaceuticals and bio-informatics, will to a
large extent be dependent on supercomputers in the future.
Software manufacturers long ago recognized the benefit of
high-performance computers based on powerful standard
servers and ported their programs to them accordingly.
The main advantages of scale-out supercomputers is just that:
they are infinitely scalable, at least in principle. Since they are
based on standard hardware components, such a supercom-
puter can be charged with more power whenever the com-
putational capacity of the system is not sufficient any more,
simply by adding additional nodes of the same kind. A cum-
bersome switch to a different technology can be avoided in
most cases.
HighPerformanceComputing
Performance Turns Into Productivity
“transtec HPC solutions are meant to provide cus-
tomers with unparalleled ease-of-management and
ease-of-use. Apart from that, deciding for a transtec
HPC solution means deciding for the most intensive
customer care and the best service imaginable.”
Dr. Oliver Tennert Director Technology Management &
HPC Solutions

8 9
solution Nagios, according to the customer’s preferences and
requirements.
Local Installation or Diskless Installation
We offer a diskful or a diskless installation of the cluster
nodes. A diskless installation means the operating system is
hosted partially within the main memory, larger parts may or
may not be included via NFS or other means. This approach
allows for deploying large amounts of nodes very efficiently,
and the cluster is up and running within a very small times-
cale. Also, updating the cluster can be done in a very efficient
way. For this, only the boot image has to be updated, and the
nodes have to be rebooted. After this, the nodes run either a
new kernel or even a new operating system. Moreover, with
this approach, partitioning the cluster can also be very effi-
ciently done, either for testing purposes, or for allocating dif-
ferent cluster partitions for different users or applications.
Development Tools, Middleware, and Applications
According to the application, optimization strategy, or under-
lying architecture, different compilers lead to code results of
very different performance. Moreover, different, mainly com-
mercial, applications, require different MPI implementations.
And even when the code is self-developed, developers often
prefer one MPI implementation over another.
According to the customer’s wishes, we install various compil-
ers, MPI middleware, as well as job management systems like
Parastation, Grid Engine, Torque/Maui, or the very powerful
Moab HPC Suite for the high-level cluster management.
xCAT as a Powerful and Flexible Deployment Tool
xCAT (Extreme Cluster Administration Tool) is an open source
toolkit for the deployment and low-level administration of
HPC cluster environments, small as well as large ones.
xCAT provides simple commands for hardware control, node
discovery, the collection of MAC addresses, and the node de-
ployment with (diskful) or without local (diskless) installation.
The cluster configuration is stored in a relational database.
Node groups for different operating system images can be
defined. Also, user-specific scripts can be executed automati-
cally at installation time.
xCAT Provides the Following Low-Level Administrative Fea-
tures
Remote console support
Parallel remote shell and remote copy commands
Plugins for various monitoring tools like Ganglia or Nagios
Hardware control commands for node discovery, collect-
ing MAC addresses, remote power switching and resetting
of nodes
Automatic configuration of syslog, remote shell, DNS,
DHCP, and ntp within the cluster
Extensive documentation and man pages
For cluster monitoring, we install and configure the open
source tool Ganglia or the even more powerful open source
Flexible Deployment With xCAT

10 11
benchmarking routines; this aids customers in sizing and devising
the optimal and detailed HPC configuration.
Each and every piece of HPC hardware that leaves our factory un-
dergoes a burn-in procedure of 24 hours or more if necessary. We
make sure that any hardware shipped meets our and our custom-
ers’ quality requirements. transtec HPC solutions are turnkey solu-
tions.Bydefault,atranstecHPCclusterhaseverythinginstalledand
configured – from hardware and operating system to important
middleware components like cluster management or developer
tools and the customer’s production applications. Onsite delivery
means onsite integration into the customer’s production environ-
ment, be it establishing network connectivity to the corporate net-
work, or setting up software and configuration parts.
transtec HPC clusters are ready-to-run systems – we deliver, you
turn the key, the system delivers high performance. Every HPC proj-
ect entails transfer to production: IT operation processes and poli-
ciesapplytothenewHPCsystem.Effectively,ITpersonnelistrained
hands-on, introduced to hardware components and software, with
all operational aspects of configuration management.
transtec services do not stop when the implementation projects
ends. Beyond transfer to production, transtec takes care. transtec
offers a variety of support and service options, tailored to the cus-
tomer’s needs. When you are in need of a new installation, a major
reconfiguration or an update of your solution – transtec is able to
support your staff and, if you lack the resources for maintaining
the cluster yourself, maintain the HPC solution for you. From Pro-
fessional Services to Managed Services for daily operations and
required service levels, transtec will be your complete HPC service
and solution provider. transtec’s high standards of performance, re-
liability and dependability assure your productivity and complete
satisfaction.
transtec’s offerings of HPC Managed Services offer customers the
possibility of having the complete management and administra-
tion of the HPC cluster managed by transtec service specialists, in
an ITIL compliant way. Moreover, transtec’s HPC on Demand servic-
es help provide access to HPC resources whenever they need them,
for example, because they do not have the possibility of owning
and running an HPC cluster themselves, due to lacking infrastruc-
ture, know-how, or admin staff.
transtec HPC Cloud Services
Lastbutnotleasttranstec’sservicesportfolioevolvesascustomers‘
demands change. Starting this year, transtec is able to provide HPC
Cloud Services. transtec uses a dedicated datacenter to provide
computing power to customers who are in need of more capacity
than they own, which is why this workflow model is sometimes
called computing-on-demand. With these dynamically provided
resources, customers with the possibility to have their jobs run on
HPC nodes in a dedicated datacenter, professionally managed and
secured, and individually customizable. Numerous standard ap-
plications like ANSYS, LS-Dyna, OpenFOAM, as well as lots of codes
like Gromacs, NAMD, VMD, and others are pre-installed, integrated
intoanenterprise-readycloudandworkloadmanagementenviron-
ment, and ready to run.
Alternatively, whenever customers are in need of space for hosting
their own HPC equipment because they do not have the space ca-
pacity or cooling and power infrastructure themselves, transtec is
also able to provide Hosting Services to those customers who’d like
to have their equipment professionally hosted, maintained, and
managed. Customers can thus build up their own private cloud!
Are you interested in any of transtec’s broad range of HPC related
services? Write us an email to HPC@transtec.de. We’ll be happy to
hear from you!
Services and Customer Care from A to Z
transtec HPC as a Service
You will get a range of applications like LS-Dyna, ANSYS,
Gromacs, NAMD etc. from all kinds of areas pre-installed,
integrated into an enterprise-ready cloud and workload
management system, and ready-to run. Do you miss your
application?
Ask us: HPC@transtec.de
transtec Platform as a Service
You will be provided with dynamically provided compute
nodes for running your individual code. The operating
system will be pre-installed according to your require-
ments. Common Linux distributions like RedHat, CentOS,
or SLES are the standard. Do you need another distribu-
tion?
Ask us: HPC@transtec.de
transtec Hosting as a Service
You will be provided with hosting space inside a profes-
sionally managed and secured datacenter where you
can have your machines hosted, managed, maintained,
according to your requirements. Thus, you can build up
your own private cloud. What range of hosting and main-
tenance services do you need?
Tell us: HPC@transtec.de
HPC @ transtec: Services and Customer Care from
A to Z
transtec AG has over 30 years of experience in scientific computing
and is one of the earliest manufacturers of HPC clusters. For nearly
a decade, transtec has delivered highly customized High Perfor-
manceclustersbasedonstandardcomponentstoacademicandin-
dustry customers across Europe with all the high quality standards
and the customer-centric approach that transtec is well known for.
Every transtec HPC solution is more than just a rack full of hard-
ware – it is a comprehensive solution with everything the HPC user,
owner,andoperatorneed.Intheearlystagesofanycustomer’sHPC
project, transtec experts provide extensive and detailed consult-
ing to the customer – they benefit from expertise and experience.
Consulting is followed by benchmarking of different systems with
either specifically crafted customer code or generally accepted
individual Presales
consulting
application-,
customer-,
site-speciﬁc
sizing of
HPC solution
burn-in tests
of systems
benchmarking of
different systems
continual
improvement
software
OS
installation
application
installation
onsite
hardware
assembly
integration
into
customer’s
environment
customer
training
maintenance,
support
managed services
individual Presales
consulting
application-,
customer-,
site-speciﬁc
sizing of
HPC solution
burn-in tests
of systems
benchmarking of
different systems
continual
improvement
software
OS
installation
application
installation
onsite
hardware
assembly
integration
into
customer’s
environment
customer
training
maintenance,
support
managed services
Services and Customer Care from A to Z

13
Bright Cluster Manager removes the complexity from the installation, management
and use of HPC clusters — on premise or in the cloud.
With Bright Cluster Manager, you can easily install, manage and use multiple clusters si-
multaneously, including compute, Hadoop, storage, database and workstation clusters.
AdvancedCluster
ManagementMadeEasy
EngineeringLifeSciencesAutomotivePriceModellingAerospaceCAEDataAnalytics

15
Comprehensive cluster monitoring and health checking: au-
tomatic sidelining of unhealthy nodes to prevent job failure
Scalability from Deskside to TOP500
Off-loadable provisioning: enables maximum scalability
Proven: used on some of the world’s largest clusters
Minimum Overhead / Maximum Performance
Lightweight: single daemon drives all functionality
Optimized: daemon has minimal impact on operating system
and applications
Efficient: single database for all metric and configuration
data
Top Security
Key-signed repositories: controlled, automated security and
other updates
Encryptionoption:forexternalandinternalcommunications
Safe: X509v3 certificate-based public-key authentication
Sensible access: role-based access control, complete audit
trail
Protected: firewalls and LDAP
A Unified Approach
Bright Cluster Manager was written from the ground up as a to-
tally integrated and unified cluster management solution. This
fundamental approach provides comprehensive cluster manage-
ment that is easy to use and functionality-rich, yet has minimal
impact on system performance. It has a single, light-weight
daemon, a central database for all monitoring and configura-
tion data, and a single CLI and GUI for all cluster management
functionality. Bright Cluster Manager is extremely easy to use,
scalable, secure and reliable. You can monitor and manage all
aspects of your clusters with virtually no learning curve.
Bright’s approach is in sharp contrast with other cluster man-
agement offerings, all of which take a “toolkit” approach. These
toolkits combine a Linux distribution with many third-party
tools for provisioning, monitoring, alerting, etc. This approach
has critical limitations: these separate tools were not designed
to work together; were often not designed for HPC, nor designed
to scale. Furthermore, each of the tools has its own interface
(mostly command-line based), and each has its own daemon(s)
and database(s). Countless hours of scripting and testing by
highly skilled people are required to get the tools to work for a
specific cluster, and much of it goes undocumented.
Time is wasted, and the cluster is at risk if staff changes occur,
losing the “in-head” knowledge of the custom scripts.
14
The Bright Advantage
Bright Cluster Manager delivers improved productivity, in-
creased uptime, proven scalability and security, while reduc-
ing operating cost:
Rapid Productivity Gains
Short learning curve: intuitive GUI drives it all
Quick installation: one hour from bare metal to compute-
ready
Fast, flexible provisioning: incremental, live, disk-full, disk-less,
over InfiniBand, to virtual machines, auto node discovery
Comprehensive monitoring: on-the-fly graphs, Rackview, mul-
tiple clusters, custom metrics
Powerful automation: thresholds, alerts, actions
Complete GPU support: NVIDIA, AMD1, CUDA, OpenCL
Full support for Intel Xeon Phi
On-demand SMP: instant ScaleMP virtual SMP deployment
Fast customization and task automation: powerful cluster
management shell, SOAP and JSON APIs make it easy
Seamless integration with leading workload managers: Slurm,
Open Grid Scheduler, Torque, openlava, Maui2, PBS Profes-
sional, Univa Grid Engine, Moab2, LSF
Integrated (parallel) application development environment
Easy maintenance: automatically update your cluster from
Linux and Bright Computing repositories
Easily extendable, web-based User Portal
Cloud-readiness at no extra cost3, supporting scenarios “Clus-
ter-on-Demand” and “Cluster-Extension”, with data-aware
scheduling
Deploys, provisions, monitors and manages Hadoop clusters
Future-proof: transparent customization minimizes disrup-
tion from staffing changes
Maximum Uptime
Automatic head node failover: prevents system downtime
Powerful cluster automation: drives pre-emptive actions
based on monitoring thresholds
AdvancedClusterManagement
MadeEasy
Easy-to-use, complete and scalable
By selecting a cluster node in the tree on the left and the Tasks tab on the right,
you can execute a number of powerful tasks on that node with just a single
mouse click.
The cluster installer takes you through the installation process and
offers advanced options such as “Express” and “Remote”.

16 1717
Extensive Development Environment
Bright Cluster Manager provides an extensive HPC development
environment for both serial and parallel applications, including
the following (some are cost options):
Compilers, including full suites from GNU, Intel, AMD and Port-
land Group.
Debuggers and profilers, including the GNU debugger and
profiler, TAU, TotalView, Allinea DDT and Allinea MAP.
GPU libraries, including CUDA and OpenCL.
MPI libraries, including OpenMPI, MPICH, MPICH2, MPICHMX,
MPICH2-MX, MVAPICH and MVAPICH2; all cross-compiled with
the compilers installed on Bright Cluster Manager, and opti-
mized for high-speed interconnects such as InfiniBand and
10GE.
Mathematical libraries, including ACML, FFTW, Goto-BLAS,
MKL and ScaLAPACK.
Other libraries, including Global Arrays, HDF5, IIPP, TBB, Net-
CDF and PETSc.
Bright Cluster Manager also provides Environment Modules to
make it easy to maintain multiple versions of compilers, libraries
and applications for different users on the cluster, without creating
compatibility conflicts. Each Environment Module file contains the
information needed to configure the shell for an application, and
automatically sets these variables correctly for the particular appli-
cationwhenitisloaded.BrightClusterManagerincludesmanypre-
configured module files for many scenarios, such as combinations
of compliers, mathematical and MPI libraries.
Powerful Image Management and Provisioning
Bright Cluster Manager features sophisticated software image
management and provisioning capability. A virtually unlimited
number of images can be created and assigned to as many dif-
ferent categories of nodes as required. Default or custom Linux
kernels can be assigned to individual images. Incremental
changes to images can be deployed to live nodes without re-
booting or re-installation.
The provisioning system only propagates changes to the images,
minimizing time and impact on system performance and avail-
ability. Provisioning capability can be assigned to any number of
nodes on-the-fly, for maximum flexibility and scalability. Bright
Cluster Manager can also provision over InfiniBand and to ram-
disk or virtual machine.
Comprehensive Monitoring
With Bright Cluster Manager, you can collect, monitor, visual-
ize and analyze a comprehensive set of metrics. Many software
and hardware metrics available to the Linux kernel, and many
hardware management interface metrics (IPMI, DRAC, iLO, etc.)
are sampled.
16
Ease of Installation
Bright Cluster Manager is easy to install. Installation and testing
of a fully functional cluster from “bare metal” can be complet-
ed in less than an hour. Configuration choices made during the
installation can be modified afterwards. Multiple installation
modes are available, including unattended and remote modes.
Cluster nodes can be automatically identified based on switch
ports rather than MAC addresses, improving speed and reliabil-
ity of installation, as well as subsequent maintenance. All major
hardware brands are supported: Dell, Cray, Cisco, DDN, IBM, HP,
Supermicro, Acer, Asus and more.
Ease of Use
Bright Cluster Manager is easy to use, with two interface op-
tions: the intuitive Cluster Management Graphical User Interface
(CMGUI) and the powerful Cluster Management Shell (CMSH).
The CMGUI is a standalone desktop application that provides
a single system view for managing all hardware and software
aspects of the cluster through a single point of control. Admin-
istrative functions are streamlined as all tasks are performed
through one intuitive, visual interface. Multiple clusters can be
managed simultaneously. The CMGUI runs on Linux, Windows
and OS X, and can be extended using plugins. The CMSH provides
practically the same functionality as the CMGUI, but via a com-
mand-line interface. The CMSH can be used both interactively
and in batch mode via scripts.
Either way, you now have unprecedented flexibility and control
over your clusters.
Support for Linux and Windows
Bright Cluster Manager is based on Linux and is available with
a choice of pre-integrated, pre-configured and optimized Linux
distributions, including SUSE Linux Enterprise Server, Red Hat
Enterprise Linux, CentOS and Scientific Linux. Dual-boot installa-
tions with Windows HPC Server are supported as well, allowing
nodes to either boot from the Bright-managed Linux head node,
or the Windows-managed head node.
MadeEasy
Cluster metrics, such as GPU, Xeon Phi and CPU temperatures, fan speeds and network statistics can be visualized by simply dragging and dropping them into a graphing
window. Multiple metrics can be combined in one graph and graphs can be zoomed into. A Graphing wizard allows creation of all graphs for a selected combination of
metrics and nodes. Graph layout and color configurations can be tailored to your requirements and stored for re-use.
TheOverviewtabprovidesinstant,high-levelinsightintothestatusof
the cluster.

18 19
Bright Cluster Manager unleashes and manages
the unlimited power of the cloud
Create a complete cluster in Amazon EC2, or easily extend your
onsite cluster into the cloud, enabling you to dynamically add
capacity and manage these nodes as part of your onsite cluster.
Both can be achieved in just a few mouse clicks, without the
need for expert knowledge of Linux or cloud computing.
Bright Cluster Manager’s unique data aware scheduling capabil-
ity means that your data is automatically in place in EC2 at the
start of the job, and that the output data is returned as soon as
the job is completed.
With Bright Cluster Manager, every cluster is cloud-ready, at no
extra cost. The same powerful cluster provisioning, monitoring,
scheduling and management capabilities that Bright Cluster
Manager provides to onsite clusters extend into the cloud.
The Bright advantage for cloud bursting
Ease of use: Intuitive GUI virtually eliminates user learning
curve; no need to understand Linux or EC2 to manage system.
Alternatively, cluster management shell provides powerful
scripting capabilities to automate tasks
Complete management solution: Installation/initialization,
provisioning, monitoring, scheduling and management in
one integrated environment
Integrated workload management: Wide selection of work-
load managers included and automatically configured with
local, cloud and mixed queues
Singlesystemview;completevisibilityandcontrol:Cloudcom-
pute nodes managed as elements of the on-site cluster; visible
from a single console with drill-downs and historic data.
Efficient data management via data aware scheduling: Auto-
matically ensures data is in position at start of computation;
delivers results back when complete.
Secure, automatic gateway: Mirrored LDAP and DNS services
over automatically-created VPN connects local and cloud-
based nodes for secure communication.
Cost savings: More efficient use of cloud resources; support
for spot instances, minimal user intervention.
Two cloud bursting scenarios
Bright Cluster Manager supports two cloud bursting scenarios:
“Cluster-on-Demand” and “Cluster Extension”.
Scenario 1: Cluster-on-Demand
The Cluster-on-Demand scenario is ideal if you do not have a
cluster onsite, or need to set up a totally separate cluster. With
just a few mouse clicks you can instantly create a complete clus-
ter in the public cloud, for any duration of time.
Scenario 2: Cluster Extension
TheClusterExtensionscenarioisidealifyouhaveaclusteronsite
but you need more compute power, including GPUs. With Bright
Cluster Manager, you can instantly add EC2-based resources to
High performance meets efficiency
Initially, massively parallel systems constitute a challenge to
both administrators and users. They are complex beasts. Anyone
building HPC clusters will need to tame the beast, master the
complexity and present users and administrators with an easy-
to-use, easy-to-manage system landscape.
Leading HPC solution providers such as transtec achieve this
goal. They hide the complexity of HPC under the hood and match
high performance with efficiency and ease-of-use for both users
and administrators. The “P” in “HPC” gains a double meaning:
“Performance” plus “Productivity”.
Cluster and workload management software like Moab HPC
Suite, Bright Cluster Manager or QLogic IFS provide the means
to master and hide the inherent complexity of HPC systems.
For administrators and users, HPC clusters are presented as
single, large machines, with many different tuning parameters.
The software also provides a unified view of existing clusters
whenever unified management is added as a requirement by the
customer at any point in time after the first installation. Thus,
daily routine tasks such as job management, user management,
queue partitioning and management, can be performed easily
with either graphical or web-based tools, without any advanced
scripting skills or technical expertise required from the adminis-
trator or user.
MadeEasy
Cloud Bursting With Bright

20 21
Amazon spot instance support
Bright Cluster Manager enables users to take advantage of the
cost savings offered by Amazon’s spot instances. Users can spec-
ify the use of spot instances, and Bright will automatically sched-
ule as available, reducing the cost to compute without the need
to monitor spot prices and manually schedule.
Hardware Virtual Machine (HVM) virtualization
Bright Cluster Manager automatically initializes all Amazon
instance types, including Cluster Compute and Cluster GPU in-
stances that rely on HVM virtualization.
Data aware scheduling
Data aware scheduling ensures that input data is transferred to
the cloud and made accessible just prior to the job starting, and
that the output data is transferred back. There is no need to wait
(and monitor) for the data to load prior to submitting jobs (de-
laying entry into the job queue), nor any risk of starting the job
before the data transfer is complete (crashing the job). Users sub-
mit their jobs, and Bright’s data aware scheduling does the rest.
Bright Cluster Manager provides the choice:
“To Cloud, or Not to Cloud”
Not all workloads are suitable for the cloud. The ideal situation
for most organizations is to have the ability to choose between
onsite clusters for jobs that require low latency communication,
complex I/O or sensitive data; and cloud clusters for many other
types of jobs.
Bright Cluster Manager delivers the best of both worlds: a pow-
erful management solution for local and cloud clusters, with
the ability to easily extend local clusters into the cloud without
compromising provisioning, monitoring or managing the cloud
resources.
your onsite cluster, for any duration of time. Bursting into the
cloud is as easy as adding nodes to an onsite cluster — there are
only a few additional steps after providing the public cloud ac-
count information to Bright Cluster Manager.
The Bright approach to managing and monitoring a cluster in
the cloud provides complete uniformity, as cloud nodes are man-
aged and monitored the same way as local nodes:
Load-balanced provisioning
Software image management
Integrated workload management
Interfaces — GUI, shell, user portal
Monitoring and health checking
Compilers, debuggers, MPI libraries, mathematical libraries
and environment modules
Bright Cluster Manager also provides additional features that
are unique to the cloud.
MadeEasy
One or more cloud nodes can be configured under the Cloud Settings tab.
The Add Cloud Provider Wizard and
the Node Creation Wizard make the
cloud bursting process easy, also for
users with no cloud experience. Bright Computing

22 23
overheated GPU unit and sending a text message to your mobile
phone. Several predefined actions are available, but any built-in
cluster management command, Linux command or script can be
used as an action.
Comprehensive GPU Management
Bright Cluster Manager radically reduces the time and effort
of managing GPUs, and fully integrates these devices into the
single view of the overall system. Bright includes powerful GPU
management and monitoring capability that leverages function-
ality in NVIDIA Tesla and AMD GPUs.
You can easily assume maximum control of the GPUs and gain
instant and time-based status insight. Depending on the GPU
make and model, Bright monitors a full range of GPU metrics,
including:
GPU temperature, fan speed, utilization
GPU exclusivity, compute, display, persistance mode
GPU memory utilization, ECC statistics
Unit fan speed, serial number, temperature, power usage, vol-
tages and currents, LED status, firmware.
Board serial, driver version, PCI info.
Beyond metrics, Bright Cluster Manager features built-in support
for GPU computing with CUDA and OpenCL libraries. Switching
between current and previous versions of CUDA and OpenCL has
also been made easy.
Full Support for Intel Xeon Phi
Bright Cluster Manager makes it easy to set up and use the Intel
Xeon Phi coprocessor. Bright includes everything that is needed
to get Phi to work, including a setup wizard in the CMGUI. Bright
ensures that your software environment is set up correctly, so
that the Intel Xeon Phi coprocessor is available for applications
that are able to take advantage of it.
Bright collects and displays a wide range of metrics for Phi, en-
suring that the coprocessor is visible and manageable as a de-
vice type, as well as including Phi as a resource in the workload
management system. Bright’s pre-job health checking ensures
that Phi is functioning properly before directing tasks to the co-
processor.
Furthermore, Bright allows you to take advantage of two execu-
tion models available from the Intel MIC architecture and makes
the workload manager aware of the models:
Native – the application runs exclusively on the coprocessor
without involving the host CPU.
Offload – the application runs on the host and some specific
computations are offloaded to the coprocessor.
Multi-Tasking Via Parallel Shell
The parallel shell allows simultaneous execution of multiple
commands and scripts across the cluster as a whole, or across
easily definable groups of nodes. Output from the executed com-
mands is displayed in a convenient way with variable levels of
verbosity. Running commands and scripts can be killed easily if
necessary. The parallel shell is available through both the CMGUI
and the CMSH.
Examples include CPU, GPU and Xeon Phi temperatures, fan
speeds, switches, hard disk SMART information, system load,
memory utilization, network metrics, storage metrics, power
systems statistics, and workload management metrics. Custom
metrics can also easily be defined.
Metric sampling is done very efficiently — in one process, or out-
of-band where possible. You have full flexibility over how and
when metrics are sampled, and historic data can be consolidat-
ed over time to save disk space.
Cluster Management Automation
Cluster management automation takes pre-emptive actions
when predetermined system thresholds are exceeded, saving
time and preventing hardware damage. Thresholds can be con-
figured on any of the available metrics. The built-in configura-
tion wizard guides you through the steps of defining a rule:
selecting metrics, defining thresholds and specifying actions.
For example, a temperature threshold for GPUs can be estab-
lished that results in the system automatically shutting down an
MadeEasy
The automation configuration wizard guides you through the steps of defining
a rule: selecting metrics, defining thresholds and specifying actions
The parallel shell allows for simultaneous execution of commands or scripts
across node groups or across the entire cluster.
The status of cluster nodes, switches, other hardware, as well as up
to six metrics can be visualized in the Rackview. A zoomout option
is available for clusters with many racks.

24 25
Integrated SMP Support
Bright Cluster Manager — Advanced Edition dynamically aggre-
gates multiple cluster nodes into a single virtual SMP node, us-
ing ScaleMP’s Versatile SMP™ (vSMP) architecture. Creating and
dismantling a virtual SMP node can be achieved with just a few
clicks within the CMGUI. Virtual SMP nodes can also be launched
and dismantled automatically using the scripting capabilities of
the CMSH.
In Bright Cluster Manager a virtual SMP node behaves like any
other node, enabling transparent, on-the-fly provisioning, con-
figuration, monitoring and management of virtual SMP nodes as
part of the overall system management.
Maximum Uptime with Failover
Failover Bright Cluster Manager — Advanced Edition allows two
head nodes to be configured in active-active failover mode. Both
head nodes are on active duty, but if one fails, the other takes
over all tasks, seamlesly.
Maximum Uptime with Health Checking
Bright Cluster Manager — Advanced Edition includes a power-
ful cluster health checking framework that maximizes system
uptime. It continually checks multiple health indicators for
all hardware and software components and proactively initi-
ates corrective actions. It can also automatically perform a se-
ries of standard and user-defined tests just before starting a
new job, to ensure a successful execution, and preventing the
“black hole node syndrome”. Examples of corrective actions
include autonomous bypass of faulty nodes, automatic job
requeuing to avoid queue flushing, and process “jailing” to al-
locate, track, trace and flush completed user processes. The
health checking framework ensures the highest job through-
put, the best overall cluster efficiency and the lowest admin-
istration overhead.
Top Cluster Security
Bright Cluster Manager offers an unprecedented level of secu-
rity that can easily be tailored to local requirements. Security
features include:
Automated security and other updates from key-signed Linux
and Bright Computing repositories.
Encrypted internal and external communications.
X509v3 certificate based public-key authentication to the
cluster management infrastructure.
Role-based access control and complete audit trail.
Firewalls, LDAP and SSH.
User and Group Management
Users can be added to the cluster through the CMGUI or the
CMSH. Bright Cluster Manager comes with a pre-configured
LDAP database, but an external LDAP service, or alternative au-
thentication system, can be used instead.
Web-Based User Portal
The web-based User Portal provides read-only access to essen-
tial cluster information, including a general overview of the clus-
ter status, node hardware and software properties, workload
Integrated Workload Management
Bright Cluster Manager is integrated with a wide selection of
free and commercial workload managers. This integration pro-
vides a number of benefits:
The selected workload manager gets automatically installed
and configured
Many workload manager metrics are monitored
The CMGUI and User Portal provide a user-friendly interface
to the workload manager
The CMSH and the SOAP JSON APIs provide direct and po-
werful access to a number of workload manager commands
and metrics
Reliable workload manager failover is properly configured
The workload manager is continuously made aware of the
health state of nodes (see section on Health Checking)
The workload manager is used to save power through auto-
power on/off based on workload
The workload manager is used for data-aware scheduling
of jobs to the cloud
The following user-selectable workload managers are tightly in-
tegrated with Bright Cluster Manager:
PBS Professional, Univa Grid Engine, Moab, LSF
Slurm, openlava, Open Grid Scheduler, Torque, Maui
Alternatively, other workload managers, such as LoadLevele and
Condor can be installed on top of Bright Cluster Manager.
MadeEasy
Workload management queues can be viewed and configured from the GUI,
without the need for workload management expertise.
Creating and dismantling a virtual SMP node can be achieved with just a few
clicks within the GUI or a single command in the cluster management shell.
Example graphs that visualize metrics on a GPU cluster.

26 27
MadeEasy
manager statistics and user-customizable graphs. The User Por-
tal can easily be customized and expanded using PHP and the
SOAP or JSON APIs.
Multi-Cluster Capability
Bright Cluster Manager — Advanced Edition is ideal for organiza-
tions that need to manage multiple clusters, either in one or in
multiple locations. Capabilities include:
All cluster management and monitoring functionality is
available for all clusters through one GUI.
Selecting any set of configurations in one cluster and ex-
porting them to any or all other clusters with a few mouse
clicks.
Metric visualizations and summaries across clusters.
Making node images available to other clusters.
Fundamentally API-Based
Bright Cluster Manager is fundamentally API-based, which
means that any cluster management command and any piece
of cluster management data — whether it is monitoring data
or configuration data — is available through the API. Both a
SOAP and a JSON API are available and interfaces for various
programming languages, including C++, Python and PHP are
provided.
Cloud Utilization
Bright Cluster Manager supports two cloud utilization sce-
narios for Amazon EC2:
Cluster-on-Demand –running stand-alone clusters in the
cloud; and
Cluster Extension – adding cloud-based resources to exist-
ing, onsite clusters and managing these cloud nodes as if
they were local.
Both scenarios utilize the full range of Bright’s capabilitiesand can
be achieved in a few simple steps. In the Cluster Extension scenar-
io, two additional capabilities significantly enhance productivity:
Data-Aware Scheduling – this ensures that the workload
manager automatically transfers the input data to the cloud
intimefortheassociatedjobtostart.Outputdataisautomati-
cally transfered back to the on-premise head node.
Automatic Cloud Resizing – this allows you to specify
policies for automatically increasing and decreasing the
number of cloud nodes based on the load in your queues.
Bright supports Amazon VPC setups which allows com-
pute nodes in EC2 to be placed in an isolated network,
thereby separating them from the outside world. It is even
possible to route part of a local corporate IP network to a
VPC subnet in EC2, so that local nodes and nodes in EC2
can communicate without any effort.
Hadoop Cluster Management
Bright Cluster Manager is the ideal basis for Hadoop clusters.
Bright installs on bare metal, configuring a fully operational
Hadoop cluster in less than one hour. In the process, Bright pre-
pares your Hadoop cluster for use by provisioning the operating
system and the general cluster management and monitoring ca-
pabilities required as on any cluster.
The web-based User Portal provides read-only access to essential cluster in-
formation, including a general overview of the cluster status, node hardware
and software properties, workload manager statistics and user-customizable
graphs.
Bright Cluster Manager can manage multiple clusters simultaneously. This
overview shows clusters in Oslo, Abu Dhabi and Houston, all managed through
one GUI.
“The building blocks for transtec HPC solutions
must be chosen according to our goals ease-of-
management and ease-of-use. With Bright Cluster
Manager, we are happy to have the technology
leader at hand, meeting these requirements, and
our customers value that.”
Armin Jäger HPC Solution Engineer

28 29
MadeEasy
Bright then manages and monitors your Hadoop cluster’s
hardware and system software throughout its life-cycle,
collecting and graphically displaying a full range of Hadoop
metrics from the HDFS, RPC and JVM sub-systems. Bright sig-
nificantly reduces setup time for Cloudera, Hortonworks and
other Hadoop stacks, and increases both uptime and Map-
Reduce job throughput.
This functionality is scheduled to be further enhanced in
upcoming releases of Bright, including dedicated manage-
ment roles and profiles for name nodes, data nodes, as well
as advanced Hadoop health checking and monitoring func-
tionality.
Standard and Advanced Editions
Bright Cluster Manager is available in two editions: Standard
and Advanced. The table on this page lists the differences. You
can easily upgrade from the Standard to the Advanced Edition as
your cluster grows in size or complexity.
Documentation and Services
A comprehensive system administrator manual and user man-
ual are included in PDF format. Standard and tailored services
are available, including various levels of support, installation,
training and consultancy.
Feature Standard Advanced
Choice of Linux distributions x x
Intel Cluster Ready x x
Cluster Management GUI x x
Cluster Management Shell x x
Web-Based User Portal x x
SOAP API x x
Node Provisioning x x
Node Identification x x
Cluster Monitoring x x
Cluster Automation x x
User Management x x
Role-based Access Control x x
Parallel Shell x x
Workload Manager Integration x x
Cluster Security x x
Compilers x x
Debuggers Profilers x x
MPI Libraries x x
Mathematical Libraries x x
Environment Modules x x
Cloud Bursting x x
Hadoop Management Monitoring x x
NVIDIA CUDA OpenCL - x
GPU Management Monitoring - x
Xeon Phi Management Monitoring - x
ScaleMP Management Monitoring - x
Redundant Failover Head Nodes - x
Cluster Health Checking - x
Off-loadable Provisioning - x
Multi-Cluster Management - x
Suggested Number of Nodes 4–128 129–10,000+
Standard Support x x
Premium Support Optional Optional
Cluster health checks can be visualized in the Rackview. This screenshot shows
that GPU unit 41 fails a health check called “AllFansRunning”.

While all HPC systems face challenges in workload demand, resource complexity, and
scale, enterprise HPC systems face more stringent challenges and expectations.
Enterprise HPC systems must meet mission-critical and priority HPC workload demands
for commercial businesses and business-oriented research and academic organizations.
They have complex SLAs and priorities to balance. Their HPC workloads directly impact
the revenue, product delivery, and organizational objectives of their organizations.
IntelligentHPC
WorkloadManagement
31
HighTrouhputComputingCADBigDataAnalyticsSimulationAerospaceAutomotive

32 33
Enterprise HPC Challenges
Enterprise HPC systems must eliminate job delays and failures.
They are also seeking to improve resource utilization and man-
agement efficiency across multiple heterogeneous systems. To-
maximize user productivity, they are required to make it easier to
access and use HPC resources for users or even expand to other
clusters or HPC cloud to better handle workload demand surges.
Intelligent Workload Management
As today’s leading HPC facilities move beyond petascale towards
exascale systems that incorporate increasingly sophisticated and
specialized technologies, equally sophisticated and intelligent
management capabilities are essential. With a proven history of
managing the most advanced, diverse, and data-intensive sys-
tems in the Top500, Moab continues to be the preferred workload
management solution for next generation HPC facilities.
Moab HPC Suite – Basic Edition
Moab HPC Suite - Basic Edition is an intelligent workload man-
agement solution. It automates the scheduling, managing,
monitoring, and reporting of HPC workloads on massive scale,
multi-technology installations. The patented Moab intelligence
engine uses multi-dimensional policies to accelerate running
workloads across the ideal combination of diverse resources.
These policies balance high utilization and throughput goals
with competing workload priorities and SLA requirements. The
speed and accuracy of the automated scheduling decisions
optimizes workload throughput and resource utilization. This
gets more work accomplished in less time, and in the right prio-
rity order. Moab HPC Suite - Basic Edition optimizes the value
and satisfaction from HPC systems while reducing manage-
ment cost and complexity.
Moab HPC Suite – Enterprise Edition
MoabHPCSuite-EnterpriseEditionprovidesenterprise-readyHPC
workload management that accelerates productivity, automates
workload uptime, and consistently meets SLAs and business prior-
ities for HPC systems and HPC cloud. It uses the battle-tested and
patented Moab intelligence engine to automatically balance the
complex, mission-critical workload priorities of enterprise HPC
systems. Enterprise customers benefit from a single integrated
product that brings together key enterprise HPC capabilities, im-
plementation services, and 24x7 support. This speeds the realiza-
tion of benefits from the HPC system for the business including:
Higher job throughput
Massive scalability for faster response and system expansion
Optimum utilization of 90-99% on a consistent basis
Fast, simple job submission and management to increase
productivity
IntelligentHPC
WorkloadManagement
Moab HPC Suite – Basic Edition
Moab is the “brain” of an HPC system, intelligently optimizing workload
throughput while balancing service levels and priorities.

34 35
Reduced cluster management complexity and support costs
across heterogeneous systems
Reduced job failures and auto-recovery from failures
SLAs consistently met for improved user satisfaction
Reduce power usage and costs by 10-30%
Productivity Acceleration
Moab HPC Suite – Enterprise Edition gets more results deliv-
ered faster from HPC resources at lower costs by accelerating
overall system, user and administrator productivity. Moab pro-
vides the scalability, 90-99 percent utilization, and simple job
submission that is required to maximize the productivity of
enterprise HPC systems. Enterprise use cases and capabilities
include:
Massive multi-point scalability to accelerate job response
and throughput, including high throughput computing
Workload-optimized allocation policies and provisioning
to get more results out of existing heterogeneous resources
and reduce costs, including topology-based allocation
Unify workload management cross heterogeneous clus-
ters to maximize resource availability and administration
efficiency by managing them as one cluster
Optimized, intelligent scheduling packs workloads and
backfills around priority jobs and reservations while balanc-
ing SLAs to efficiently use all available resources
Optimized scheduling and management of accelerators,
both Intel MIC and GPGPUs, for jobs to maximize their utili-
zation and effectiveness
Simplified job submission and management with advanced
job arrays, self-service portal, and templates
Administrator dashboards and reporting tools reduce man-
agement complexity, time, and costs
Workload-aware auto-power management reduces energy
use and costs by 10-30 percent
Uptime Automation
Job and resource failures in enterprise HPC systems lead to de-
layed results, missed organizational opportunities, and missed
objectives. Moab HPC Suite – Enterprise Edition intelligently au-
tomates workload and resource uptime in the HPC system to en-
sure that workload completes successfully and reliably, avoiding
these failures. Enterprises can benefit from:
Intelligent resource placement to prevent job failures with
granular resource modeling to meet workload requirements
and avoid at-risk resources
Auto-response to failures and events with configurable ac-
tions to pre-failure conditions, amber alerts, or other metrics
and monitors
Workload-aware future maintenance scheduling that helps
maintain a stable HPC system without disrupting workload
productivity
Real-world expertise for fast time-to-value and system
uptime with included implementation, training, and 24x7
support remote services
Auto SLA Enforcement
Moab HPC Suite – Enterprise Edition uses the powerful Moab
intelligence engine to optimally schedule and dynamically
adjust workload to consistently meet service level agree-
ments (SLAs), guarantees, or business priorities. This auto-
matically ensures that the right workloads are completed at
the optimal times, taking into account the complex number of
using departments, priorities and SLAs to be balanced. Moab
provides:
Usage accounting and budget enforcement that schedules
resources and reports on usage in line with resource shar-
ing agreements and precise budgets (includes usage limits,
Intelligent HPC
Workload Management
Moab HPC Suite – Enterprise Edition
“With Moab HPC Suite, we can meet very demand-
ing customers’ requirements as regards unified
management of heterogeneous cluster environ-
ments, grid management, and provide them with
flexible and powerful configuration and reporting
options. Our customers value that highly.”
Thomas Gebert HPC Solution Architect

36 37
usage reports, auto budget management and dynamic fair-
share policies)
SLA and priority polices that make sure the highest priorty
workloads are processed first (includes Quality of Service,
hierarchical priority weighting)
Continuous plus future scheduling that ensures priorities
and guarantees are proactively met as conditions and work-
load changes (i.e. future reservations, pre-emption, etc.)
Grid- and Cloud-Ready Workload Management
The benefits of a traditional HPC environment can be extended
to more efficiently manage and meet workload demand with
the ulti-cluster grid and HPC cloud management capabilities in
Moab HPC Suite - Enterprise Edition. It allows you to:
Showback or chargeback for pay-for-use so actual resource
usage is tracked with flexible chargeback rates and report-
ing by user, department, cost center, or cluster
Manage and share workload across multiple remote clusters
to meet growing workload demand or surges by adding on
the Moab HPC Suite – Grid Option.
Moab HPC Suite – Grid Option
The Moab HPC Suite - Grid Option is a powerful grid-workload
management solution that includes scheduling, advanced poli-
cy management, and tools to control all the components of ad-
vanced grids. Unlike other grid solutions, Moab HPC Suite - Grid
Option connects disparate clusters into a logical whole, enabling
grid administrators and grid policies to have sovereignty over all
systems while preserving control at the individual cluster.
Moab HPC Suite - Grid Option has powerful applications that al-
low organizations to consolidate reporting; information gather-
ing; and workload, resource, and data management. Moab HPC
Suite - Grid Option delivers these services in a near-transparent
way: users are unaware they are using grid resources—they
know only that they are getting work done faster and more eas-
ily than ever before.
Moab manages many of the largest clusters and grids in the
world. Moab technologies are used broadly across Fortune 500
companies and manage more than a third of the compute cores
in the top 100 systems of the Top500 supercomputers. Adaptive
Computing is a globally trusted ISV (independent software ven-
dor), and the full scalability and functionality Moab HPC Suite
with the Grid Option offers in a single integrated solution has
traditionally made it a significantly more cost-effective option
than other tools on the market today.
Components
The Moab HPC Suite - Grid Option is available as an add-on to
Moab HPC Suite - Basic Edition and -Enterprise Edition. It extends
the capabilities and functionality of the Moab HPC Suite compo-
nents to manage grid environments including:
Moab Workload Manager for Grids – a policy-based work-
load management and scheduling multi-dimensional deci-
sion engine
Moab Cluster Manager for Grids – a powerful and unified
graphical administration tool for monitoring, managing and
reporting tool across multiple clusters
Moab ViewpointTM for Grids – a Web-based self-service
end-user job-submission and management portal and ad-
ministrator dashboard
Benefits
Unified management across heterogeneous clusters provides
ability to move quickly from cluster to optimized grid
Policy-driven and predictive scheduling ensures that jobs
start and run in the fastest time possible by selecting optimal
resources
Flexible policy and decision engine adjusts workload pro-
cessing at both grid and cluster level
Grid-wide interface and reporting tools provide view of grid
resources, status and usage charts, and trends over time for
capacity planning, diagnostics, and accounting
Advanced administrative control allows various business
units to access and view grid resources, regardless of physical
or organizational boundaries, or alternatively restricts access
to resources by specific departments or entities
Scalable architecture to support peta-scale, highthroughput
computing and beyond
Grid Control with Automated Tasks, Policies, and Re-
porting
Guarantee that the most-critical work runs first with flexible
global policies that respect local cluster policies but continue
to support grid service-level agreements
Ensure availability of key resources at specific times with ad-
vanced reservations
Tune policies prior to rollout with cluster- and grid-level simu-
lations
Use a global view of all grid operations for self-diagnosis, plan-
ning, reporting, and accounting across all resources, jobs, and
clusters
Intelligent HPC
Workload Management
Moab HPC Suite – Grid Option
Moab HPC Suite -Grid Option can be flexibly configured for centralized, cen-
tralized and local, or peer-to-peer grid policies, decisions and rules. It is able to
manage multiple resource managers and multiple Moab instances.

38 39
HarnessingthePowerofIntelXeonPhiandGPGPUs
The mathematical acceleration delivered by many-core Gen-
eral Purpose Graphics Processing Units (GPGPUs) offers signifi-
cant performance advantages for many classes of numerically
intensive applications. Parallel computing tools such as NVID-
IA’s CUDA and the OpenCL framework have made harnessing
the power of these technologies much more accessible to
developers, resulting in the increasing deployment of hybrid
GPGPU-based systems and introducing significant challenges
for administrators and workload management systems.
The new Intel Xeon Phi coprocessors offer breakthrough per-
formance for highly parallel applications with the benefit of
leveraging existing code and flexibility in programming mod-
els for faster application development. Moving an application
to Intel Xeon Phi coprocessors has the promising benefit of re-
quiring substantially less effort and lower power usage. Such a
small investment can reap big performance gains for both data-
intensive and numerical or scientific computing applications
that can make the most of the Intel Many Integrated Cores (MIC)
technology. So it is no surprise that organizations are quickly
embracing these new coprocessors in their HPC systems.
The main goal is to create breakthrough discoveries, products
and research that improve our world. Harnessing and optimiz-
ing the power of these new accelerator technologies is key to
doing this as quickly as possible. Moab HPC Suite helps organi-
zations easily integrate accelerator and coprocessor technolo-
gies into their HPC systems, optimizing their utilization for the
right workloads and problems they are trying to solve.
Moab HPC Suite automatically schedules hybrid systems incor-
porating Intel Xeon Phi coprocessors and GPGPU accelerators,
optimizing their utilization as just another resource type with
policies. Organizations can choose the accelerators that best
meet their different workload needs.
Managing Hybrid Accelerator Systems
Hybrid accelerator systems add a new dimension of manage-
ment complexity when allocating workloads to available re-
sources. In addition to the traditional needs of aligning work-
load placement with software stack dependencies, CPU type,
memory, and interconnect requirements, intelligent workload
management systems now need to consider:
Workload’s ability to exploit Xeon Phi or GPGPU
technology
Additional software dependenciesand reduce costs,
including topology-based allocation
Current health and usage status of available Xeon Phis
or GPGPUs
Resource configuration for type and number of Xeon Phis
or GPGPUs
Moab HPC Suite auto detects which types of accelerators are
where in the system to reduce the management effort and costs
as these processors are introduced and maintained together in
an HPC system. This gives customers maximum choice and per-
formance in selecting the accelerators that work best for each
of their workloads, whether Xeon Phi, GPGPU or a hybrid mix of
the two.
Intelligent HPC
Workload Management
OptimizingAcceleratorswithMoabHPCSuite
Moab HPC Suite optimizes accelerator utilization with policies that ensure
the right ones get used for the right user and group jobs at the right time.

40 41
Optimizing Intel Xeon Phi and GPGPUs Utilization
System and application diversity is one of the first issues
workload management software must address in optimizing
accelerator utilization. The ability of current codes to use GP-
GPUs and Xeon Phis effectively, ongoing cluster expansion,
and costs usually mean only a portion of a system will be
equipped with one or a mix of both types of accelerators.
Moab HPC Suite has a twofold role in reducing the complex-
ity of their administration and optimizing their utilization.
First, it must be able to automatically detect new GPGPUs
or Intel Xeon Phi coprocessors in the environment and their
availability without the cumbersome burden of manual ad-
ministrator configuration. Second, and most importantly, it
must accurately match Xeon Phi-bound or GPGPUenabled
workloads with the appropriately equipped resources in ad-
dition to managing contention for those limited resources
according to organizational policy. Moab’s powerful alloca-
tion and prioritization policies can ensure the right jobs from
users and groups get to the optimal accelerator resources at
the right time. This keeps the accelerators at peak utilization
for the right priority jobs.
Moab’s policies are a powerful ally to administrators in auto
determining the optimal Xeon Phi coprocessor or GPGPU to
use and ones to avoid when scheduling jobs. These alloca-
tion policies can be based on any of the GPGPU or Xeon Phi
metrics such as memory (to ensure job needs are met), tem-
perature (to avoid hardware errors or failures), utilization, or
other metrics.
Use the following metrics in policies to optimize allocation of
Intel Xeon Phi coprocessors:
Number of Cores
Number of Hardware Threads
Physical Memory
Free Physical Memory
Swap Memory
Free Swap Memory
Max Frequency (in MHz)
Use the following metrics in policies to optimize allocation of
GPGPUs and for management diagnostics:
Error counts; single/double-bit, commands to reset counts
Temperature
Fan speed
Memory; total, used, utilization
Utilization percent
Metrics time stamp
Improve GPGPU Job Speed and Success
The GPGPU drivers supplied by vendors today allow multiple
jobs to share a GPGPU without corrupting results, but sharing
GPGPUs and other key GPGPU factors can significantly impact
the speed and success of GPGPU jobs and the final level of ser-
vice delivered to the system users and the organization.
Consider the example of a user estimating the time for a GP-
GPU job based on exclusive access to a GPGPU, but the work-
IntelligentHPC
WorkloadManagement
OptimizingAcceleratorswithMoabHPCSuite
load manager allowing the GPGPU to be shared when the job is
scheduled. The job will likely exceed the estimated time and be
terminated by the workload manager unsuccessfully, leaving
a very unsatisfied user and the organization, group or project
they represent. Moab HPC Suite provides the ability to sched-
ule GPGPU jobs to run exclusively and finish in the shortest time
possible for certain types, or classes of jobs or users to ensure
job speed and success.

42 43
Cluster Sovereignty and Trusted Sharing
Guarantee that shared resources are allocated fairly with
global policies that fully respect local cluster configuration
and needs
Establish trust between resource owners through graphical
usage controls, reports, and accounting across all shared
resources
Maintain cluster sovereignty with granular settings to con-
trol where jobs can originate and be processed n Establish
resource ownership and enforce appropriate access levels
with prioritization, preemption, and access guarantees
Increase User Collaboration and Productivity
Reduce end-user training and job management time with
easy-to-use graphical interfaces
Enable end users to easily submit and manage their jobs
through an optional web portal, minimizing the costs of ca-
tering to a growing base of needy users
Collaborate more effectively with multicluster co-allocation,
allowing key resource reservations for high-priority projects
Leverage saved job templates, allowing users to submit mul-
tiple jobs quickly and with minimal changes
Speed job processing with enhanced grid placement options
for job arrays; optimal or single cluster placement
Process More Work in Less Time to Maximize ROI
Achieve higher, more consistent resource utilization with in-
telligent scheduling, matching job requests to the bestsuited
resources, including GPGPUs
Use optimized data staging to ensure that remote data trans-
fers are synchronized with resource availability to minimize
poor utilization
Allow local cluster-level optimizations of most grid workload
Unify Management Across Independent Clusters
Unify management across existing internal, external, and
partner clusters – even if they have different resource man-
agers, databases, operating systems, and hardware
Out-of-the-box support for both local area and wide area
grids
Manage secure access to resources with simple credential
mapping or interface with popular security tool sets
Leverage existing data-migration technologies, such as SCP
or GridFTP
Moab HPC Suite – Application Portal Edition
Remove the Barriers to Harnessing HPC
Organizations of all sizes and types are looking to harness the
potential of high performance computing (HPC) to enable and
accelerate more competitive product design and research. To
do this, you must find a way to extend the power of HPC resourc-
es to designers, researchers and engineers not familiar with or
trained on using the specialized HPC technologies. Simplifying
the user access to and interaction with applications running on
more efficient HPC clusters removes the barriers to discovery
and innovation for all types of departments and organizations.
Moab® HPC Suite – Application Portal Edition provides easy sin-
gle-point access to common technical applications, data, HPC
resources, and job submissions to accelerate research analysis
and collaboration process for end users while reducing comput-
ing costs.
HPC Ease of Use Drives Productivity
Moab HPC Suite – Application Portal Edition improves ease of
use and productivity for end users using HPC resources with sin-
gle-point access to their common technical applications, data,
resources, and job submissions across the design and research
process. It simplifies the specification and running of jobs on
HPC resources to a few simple clicks on an application specific
template with key capabilities including:
Application-centric job submission templates for common
manufacturing, energy, life-sciences, education and other
industry technical applications
Support for batch and interactive applications, such as
simulations or analysis sessions, to accelerate the full proj-
ect or design cycle
No special HPC training required to enable more users to
start accessing HPC resources with intuitive portal
Distributed data management avoids unnecessary remote
file transfers for users, storing data optimally on the network
for easy access and protection, and optimizing file transfer
to/ from user desktops if needed
Accelerate Collaboration While Maintaining Control
More and more projects are done across teams and with part-
ner and industry organizations. Moab HPC Suite – Application
Portal Edition enables you to accelerate this collaboration be-
tween individuals and teams while maintaining control as ad-
ditional users, inside and outside the organization, can easily
and securely access project applications, HPC resources and
data to speed project cycles. Key capabilities and benefits you
can leverage are:
Encrypted and controllable access, by class of user, ser-
vices, application or resource, for remote and partner users
improves collaboration while protecting infrastructure and
intellectual property
Intelligent HPC
Workload Management
Moab HPC Suite – Application Portal Edition
The Visual Cluster view in Moab Cluster Manager for Grids makes cluster and
grid management easy and efficient.

44 45
Enable multi-site, globally available HPC services available
anytime, anywhere, accessible through many different types
of devices via a standard web browser
Reduced client requirements for projectsmeans new proj-
ect members can quickly contribute without being limited by
their desktop capabilities
Reduce Costs with Optimized Utilization and Sharing
Moab HPC Suite – Application Portal Edition reduces the costs
of technical computing by optimizing resource utilization and
the sharing of resources including HPC compute nodes, applica-
tion licenses, and network storage. The patented Moab intelli-
gence engine and its powerful policies deliver value in key areas
of utilization and sharing:
Maximize HPC resource utilization with intelligent, opti-
mized scheduling policies that pack and enable more work
to be done on HPC resources to meet growing and changing
demand
Optimize application license utilization and access by shar-
ing application licenses in a pool, re-using and optimizing us-
age with allocation policies that integrate with license man-
agers for lower costs and better service levels to a broader
set of users
Usage budgeting and priorities enforcement with usage
accounting and priority policies that ensure resources are
shared in-line with service level agreements and project pri-
orities
Leverage and fully utilize centralized storage capacity in-
stead of duplicative, expensive, and underutilized individual
workstation storage
Key Intelligent Workload Management Capabilities:
Massive multi-point scalability
Workload-optimized allocation policies and provisioning
Unify workload management cross heterogeneous clusters
Optimized, intelligent scheduling
Optimized scheduling and management of accelerators
(both Intel MIC and GPGPUs)
Administrator dashboards and reporting tools
Workload-aware auto power management
Intelligent resource placement to prevent job failures
Auto-response to failures and events
Workload-aware future maintenance scheduling
Usage accounting and budget enforcement
SLA and priority polices
Continuous plus future scheduling
MoabHPCSuite–RemoteVisualizationEdition
Removing Inefficiencies in Current 3D Visualization Methods
Using 3D and 2D visualization, valuable data is interpreted and
new innovations are discovered. There are numerous inefficien-
cies in how current technical computing methods support users
and organizations in achieving these discoveries in a cost effec-
tive way. High-cost workstations and their software are often
not fully utilized by the limited user(s) that have access to them.
They are also costly to manage and they don’t keep pace long
with workload technology requirements. In addition, the work-
station model also requires slow transfers of the large data sets
between them. This is costly and inefficient in network band-
width, user productivity, and team collaboration while posing
increased data and security risks. There is a solution that re-
moves these inefficiencies using new technical cloud comput-
ing models. Moab HPC Suite – Remote Visualization Edition
significantly reduces the costs of visualization technical com-
puting while improving the productivity, collaboration and se-
curity of the design and research process.
ReducetheCostsofVisualizationTechnicalComputing
Moab HPC Suite – Remote Visualization Edition significantly
reduces the hardware, network and management costs of vi-
sualization technical computing. It enables you to create easy,
centralized access to shared visualization compute, applica-
tion and data resources. These compute, application, and data
resources reside in a technical compute cloud in your data
center instead of in expensive and underutilized individual
workstations.
Reduce hardware costs by consolidating expensive individual
technical workstations into centralized visualization servers
for higher utilization by multiple users; reduce additive or up-
grade technical workstation or specialty hardware purchases,
such as GPUs, for individual users.
Reduce management costs by moving from remote user work-
stations that are difficult and expensive to maintain, upgrade,
and back-up to centrally managed visualization servers that
require less admin overhead
Decreasenetworkaccesscostsandcongestionassignificantly
lower loads of just compressed, visualized pixels are moving to
users, not full data sets
Reduce energy usageas centralized visualization servers con-
sume less energy for the user demand met
Reduce data storage costs by consolidating data into com-
Intelligent HPC Workload
Management
The Application Portal Edition easily extends the power of HPC to your users
and projects to drive innovation and competentive advantage.

46 47
Consolidation and Grid
Many sites have multiple clusters as a result of having multiple
independent groups or locations, each with demands for HPC,
and frequent additions of newer machines. Each new cluster
increases the overall administrative burden and overhead. Ad-
ditionally, many of these systems can sit idle while others are
overloaded. Because of this systems-management challenge,
sites turn to grids to maximize the efficiency of their clusters.
Grids can be enabled either independently or in conjunction
with one another in three areas:
Reporting Grids Managers want to have global reporting
across all HPC resources so they can see how users and proj-
ects are really utilizing hardware and so they can effectively
plan capacity. Unfortunately, manually consolidating all of
this information in an intelligible manner for more than just
a couple clusters is a management nightmare. To solve that
problem, sites will create a reporting grid, or share informa-
tion across their clusters for reporting and capacity-plan-
ning purposes.
Management Grids Managing multiple clusters indepen-
dently can be especially difficult when processes change,
because policies must be manually reconfigured across all
clusters. To ease that difficulty, sites often set up manage-
ment grids that impose a synchronized management layer
across all clusters while still allowing each cluster some
level of autonomy.
Workload-Sharing Grids Sites with multiple clusters often
have the problem of some clusters sitting idle while other
clusters have large backlogs. Such inequality in cluster uti-
lization wastes expensive resources, and training users to
perform different workload-submission routines across var-
ious clusters can be difficult and expensive as well. To avoid
these problems, sites often set up workload-sharing grids.
These grids can be as simple as centralizing user submission
or as complex as having each cluster maintain its own user
submission routine with an underlying grid-management
tool that migrates jobs between clusters.
Inhibitors to Grid Environments
Three common inhibitors keep sites from enabling grid environ-
ments:
Politics Because grids combine resources across users,
groups, and projects that were previously independent, grid
implementation can be a political nightmare. To create a
grid in the real world, sites need a tool that allows clusters
to retain some level of sovereignty while participating in the
larger grid.
Multiple Resource Managers Most sites have a variety of
resource managers used by various groups within the orga-
nization, and each group typically has a large investment in
scripts that are specific to one resource manager and that
cannot be changed. To implement grid computing effective-
ly, sites need a robust tool that has flexibility in integrating
with multiple resource managers.
Credentials Many sites have different log-in credentials for
each cluster, and those credentials are generally indepen-
dent of one another. For example, one user might be Joe.P on
one cluster and J_Peterson on another. To enable grid envi-
ronments, sites must create a combined user space that can
recognize and combine these different credentials.
Using Moab in a Grid
Sites can use Moab to set up any combination of reporting, man-
agement, and workload-sharing grids. Moab is a grid metas-
cheduler that allows sites to set up grids that work effectively
in the real world. Moab’s feature-rich functionality overcomes
the inhibitors of politics, multiple resource managers, and vary-
ing credentials by providing:
Intelligent HPC
Workload Management
Using Moab With Grid Environments
Grid Sovereignty Moab has multiple features that break
down political barriers by letting sites choose how each
cluster shares in the grid. Sites can control what information
is shared between clusters and can specify which workload
is passed between clusters. In fact, sites can even choose
to let each cluster be completely sovereign in making deci-
sions about grid participation for itself.
Support for Multiple Resource Managers Moab meta-
schedules across all common resource managers. It fully
integrates with TORQUE and SLURM, the two most-common
open-source resource managers, and also has limited in-
tegration with commercial tools such as PBS Pro and SGE.
Moab’s integration includes the ability to recognize when a
user has a script that requires one of these tools, and Moab
can intelligently ensure that the script is sent to the correct
machine. Moab even has the ability to translate common
scripts across multiple resource managers.
Credential Mapping Moab can map credentials across clus-
ters to ensure that users and projects are tracked appropri-
ately and to provide consolidated reporting.

48 49
mon storage node(s) instead of under-utilized individual
storage
Improve Collaboration, Productivity and Security
With Moab HPC Suite – Remote Visualization Edition, you can im-
prove the productivity, collaboration and security of the design
and research process by only transferring pixels instead of data
to users to do their simulations and analysis. This enables a wid-
er range of users to collaborate and be more productive at any
time,onthesamedata,fromanywherewithoutanydatatransfer
time lags or security issues. Users also have improved immediate
access to specialty applications and resources, like GPUs, they
might need for a project so they are no longer limited by personal
workstation constraints or to a single working location.
Improve workforce collaboration by enabling multiple
users to access and collaborate on the same interactive ap-
plication data at the same time from almost any location or
device, with little or no training needed
Eliminate data transfer time lags for users by keeping data
close to the visualization applications and compute resourc-
es instead of transferring back and forth to remote worksta-
tions; only smaller compressed pixels are transferred
Improve security with centralized data storage so data no
longer gets transferred to where it shouldn’t, gets lost, or
gets inappropriately accessed on remote workstations, only
pixels get moved
MaximizeUtilizationandSharedResourceGuarantees
Moab HPC Suite – Remote Visualization Edition maximizes your
resource utilization and scalability while guaranteeing shared
resource access to users and groups with optimized workload
management policies. Moab’s patented policy intelligence en-
gine optimizes the scheduling of the visualization sessions
across the shared resources to maximize standard and spe-
cialty resource utilization, helping them scale to support larger
volumes of visualization workloads. These intelligent policies
also guarantee shared resource access to users to ensure a high
service level as they transition from individual workstations.
Guarantee shared visualization resource access for users
with priority policies and usage budgets that ensure they
receive the appropriate service level. Policies include ses-
sion priorities and reservations, number of users per node,
fairshare usage policies, and usage accounting and budgets
across multiple groups or users.
Maximize resource utilization and scalability by packing
visualization workload optimally on shared servers using
Moab allocation and scheduling policies. These policies can
include optimal resource allocation by visualization session
characteristics (like CPU, memory, etc.), workload packing,
number of users per node, and GPU policies, etc.
Improve application license utilization to reduce software
costs and improve access with a common pool of 3D visual-
ization applications shared across multiple users, with usage
optimized by intelligent Moab allocation policies, integrated
with license managers.
Optimized scheduling and management of GPUs and other
accelerators to maximize their utilization and effectiveness
Enable multiple Windows or Linux user sessions on a single
machine managed by Moab to maximize resource and power
utilization.
Enable dynamic OS re-provisioning on resources, managed
by Moab, to optimally meet changing visualization applica-
tion workload demand and maximize resource utilization
and availability to users.
Management
The Remote Visualization Edition makes visualization more cost effective and productive with an innovative technical compute cloud.

Moab HPC Suite Use Case Basic Enterprise Application Portal Remote Visualization
ProductivityAcceleration
Massive multifaceted scalability x x x x
Workload optimized resource allocation x x x x
Optimized, intelligent scheduling of work-
load and resources
x x x x
Optimized accelerator scheduling manage-
ment (Intel MIC GPGPU)
x x x x
Simplified user job submission mgmt.
- Application Portal
x x x
x
x
Administrator dashboard and management
reporting
x x x x
Unified workload management across het-
erogeneous cluster(s)
x
Single cluster only
x x x
Workload optimized node provisioning x x x
Visualization Workload Optimization x
Workload-aware auto-power management x x x
Uptime Automation
Intelligent resource placement for failure
prevention
x x x x
Workload-aware maintenance scheduling x x x x
Basic deployment, training and premium
(24x7) support service
Standard
support only
x x x
Auto response to failures and events x
Limited no
re-boot/provision
x x x
Auto SLA enforcement
Resource sharing and usage policies x x x x
SLA and oriority policies x x x x
Continuous and future reservations scheduling x x x x
Usage accounting and budget enforcement x x x
Grid- and Cloud-Ready
Manage and share workload across multiple
clusters in wich area grid
x
w/grid Option
x
w/grid Option
x
w/grid Option
x
w/grid Option
User self-service: job request management
portal
x x x x
Pay-for-use showback and chargeback x x x
Workload optimized node provisioning
re-purposing
x x x
Multiple clusters in
single domain
50 51
Management
transtec HPC solutions are designed for maximum flexibility,
and ease of management. We not only offer our customers the
most powerful and flexible cluster management solution out
there, but also provide them with customized setup and site-
specific configuration. Whether a customer needs a dynamical
Linux-Windows dual-boot solution, unifi ed management of
different clusters at different sites, or the fi ne-tuning of the
Moab scheduler for implementing fi ne-grained policy confi
guration – transtec not only gives you the framework at hand,
but also helps you adapt the system according to your special
needs. Needless to say, when customers are in need of special
trainings, transtec will be there to provide customers, adminis-
trators, or users with specially adjusted Educational Services.
Having a many years’ experience in High Performance Comput-
ing enabled us to develop effi cient concepts for installing and
deploying HPC clusters. For this, we leverage well-proven 3rd
party tools, which we assemble to a total solution and adapt
and confi gure according to the customer’s requirements.
We manage everything from the complete installation and
confi guration of the operating system, necessary middleware
components like job and cluster management systems up to
the customer’s applications.

RemoteVirtualizationand
WorkflowOptimization
It’s human nature to want to ‘see’ the results from simulations, tests, and analyses. Up
until recently, this has meant ‘fat’ workstations on many user desktops. This approach
provides CPU power when the user wants it – but as dataset size increases, there can be
delays in downloading the results. Also, sharing the results with colleagues means gath-
ering around the workstation - not always possible in this globalized, collaborative work-
place.
LifeSciencesCAEHighPerformanceComputingBigDataAnalyticsSimulationCAD

54 55
Aerospace, Automotive and Manufacturing
The complex factors involved in CAE range from compute-in-
tensive data analysis to worldwide collaboration between de-
signers, engineers, OEM’s and suppliers. To accommodate these
factors, Cloud (both internal and external) and Grid Computing
solutions are increasingly seen as a logical step to optimize IT
infrastructure usage for CAE. It is no surprise then, that automo-
tive and aerospace manufacturers were the early adopters of
internal Cloud and Grid portals.
Manufacturers can now develop more “virtual products” and
simulate all types of designs, fluid flows, and crash simula-
tions. Such virtualized products and more streamlined col-
laboration environments are revolutionizing the manufac-
turing process.
With NICE EnginFrame in their CAE environment engineers can
take the process even further by connecting design and simula-
tion groups in “collaborative environments” to get even greater
benefits from “virtual products”. Thanks to EnginFrame, CAE en-
gineers can have a simple intuitive collaborative environment
that can care of issues related to:
Access Security - Where an organization must give access
to external and internal entities such as designers, engi-
neers and suppliers.
Distributed collaboration - Simple and secure connection of
design and simulation groups distributed worldwide.
Time spent on IT tasks - By eliminating time and resources
spent using cryptic job submission commands or acquiring
knowledge of underlying compute infrastructures, engi-
neers can spend more time concentrating on their core de-
sign tasks.
EnginFrame’s web based interface can be used to access the
compute resources required for CAE processes. This means ac-
cess to job submission monitoring tasks, input output data
associated with industry standard CAE/CFD applications for
Fluid-Dynamics, Structural Analysis, Electro Design and Design
Collaboration (like Abaqus, Ansys, Fluent, MSC Nastran, PAM-
Crash, LS-Dyna, Radioss) without cryptic job submission com-
mands or knowledge of underlying compute infrastructures.
EnginFrame has a long history of usage in some of the most
prestigious manufacturing organizations worldwide including
Aerospace companies like AIRBUS, Alenia Space, CIRA, Galileo
Avionica, Hamilton Sunstrand, Magellan Aerospace, MTU and
Automotive companies like Audi, ARRK, Brawn GP, Bridgestone,
Bosch, Delphi, Elasis, Ferrari, FIAT, GDX Automotive, Jaguar-Lan-
dRover, Lear, Magneti Marelli, McLaren, P+Z, RedBull, Swagelok,
Suzuki, Toyota, TRW.
Life Sciences and Healthcare
NICE solutions are deployed in the Life Sciences sector at com-
panies like BioLab, Partners HealthCare, Pharsight and the
M.D.Anderson Cancer Center; also in leading research projects like
DEISA or LitBio in order to allow easy and transparent use of com-
puting resources without any insight of the HPC infrastructure.
The Life Science and Healthcare sectors have some very strict re-
quirement when choosing its IT solution like EnginFrame, for in-
stance
Security - To meet the strict security privacy requirements
of the biomedical and pharmaceutical industry any solution
needs to take account of multiple layers of security and au-
thentication.
Industry specific software - ranging from the simplest cus-
tom tool to the more general purpose free and open middle-
wares.
EnginFrame’s modular architecture allows for different Grid mid-
dlewares and software including leading Life Science applica-
tions like Schroedinger Glide, EPFL RAxML, BLAST family, Taverna,
and R) to be exploited, R Users can compose elementary services
into complex applications and “virtual experiments”, run, moni-
tor,andbuildworkflowsviaastandardWebbrowser.EnginFrame
also has highly tunable resource sharing and fine-grained access
control where multiple authentication systems (like Active Direc-
tory, Kerberos/LDAP) can be exploited simultaneously.
Growing complexity in globalized teams
HPC systems and Enterprise Grids deliver unprecedented time-
to-market and performance advantages to many research and
corporate customers, struggling every day with compute and
data intensive processes.
This often generates or transforms massive amounts of jobs
and data, that needs to be handled and archived efficiently to
deliver timely information to users distributed in multiple loca-
tions, with different security concerns.
Poor usability of such complex systems often negatively im-
pacts users’ productivity, and ad-hoc data management often
increases information entropy and dissipates knowledge and
intellectual property.
The solution
Solving distributed computing issues for our customers, we un-
derstand that a modern, user-friendly web front-end to HPC and
RemoteVirtualization
NICE EnginFrame:
A Technical Computing Portal

56 57
RemoteVirtualization
NICE EnginFrame:
A Technical Computing Portal
Grids can drastically improve engineering productivity, if prop-
erly designed to address the specific challenges of the Technical
Computing market
NICE EnginFrame overcomes many common issues in the areas
of usability, data management, security and integration, open-
ing the way to a broader, more effective use of the Technical
Computing resources.
The key components of the solution are:
A flexible and modular Java-based kernel, with clear separa-
tion between customizations and core services
Powerful data management features, reflecting the typical
needs of engineering applications
Comprehensive security options and a fine grained authori-
zation system
Scheduler abstraction layer to adapt to different workload
and resource managers
Responsive and competent Support services
End users can typically enjoy the following improvements:
User-friendly, intuitive access to computing resources, using
a standard Web browser
Application-centric job submission
Organized access to job information and data
Increased mobility and reduced client requirements
On the other side, the Technical Computing Portal delivers sig-
nificant added-value for system administrators and IT:
Reduced training needs to enable users to access the
resources
Centralized configuration and immediate deployment of
services
Comprehensive authorization to access services and
information
Reduced support calls and submission errors
Coupled with our Remote Visualization solutions, our custom-
ers quickly deploy end-to-end engineering processes on their
Intranet, Extranet or Internet.

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