High-Performance-Computing-on-AWS-and-Industry-Simulation

© 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.S U M M I T
High Performance Computing on AWS
Driving innovation without infrastructure constraints
David Pellerin
Head WW Business Development,
Hitech/Semiconductor
AWS
Anh Tran
Sr. HPC Solutions Architect
AWS

Flexible configuration and virtually unlimited scalability
to grow and shrink your infrastructure as your HPC workloads
dictate, not the other way around
HPC on AWS

Why HPC on AWS
Virtually unlimited infrastructure enabling
scaling and agility not attainable on-premises
Flexible configuration options quickly iterate resource
selection and ensure cost optimization
Increased collaboration with secure access
to clusters around the world
Better ROI
Faster time
to results

Mapping HPC use cases
- Fluid Dynamics/Res.Sim.
- Weather Forecasting
- Materials Simulations
- Crash Simulations
- Metagenomics
- Astrophysics
- Deep Learning
- Coupled DL & Simulation
- Seismic Processing
- Animation and VFX
- Semiconductor Verification
- Image Processing/GIS
- Genomics
- Risk Simulations
- Molecular Modeling
- Contextual Search
- Logistics Simulations
Clustered (Tightly Coupled)
Distributed/Grid (Loosely Coupled)
Data Light
Minimal
requirement for
high performance
storage
Data Heavy
Benefits from access
to high performance
storage

Components of a well-architected HPC environment

HPC on AWS solution components
Automation and
orchestration
AWS Batch
AWS ParallelCluster
NICE EnginFrame
Storage
Amazon EBS
Amazon EFS
Amazon S3
Compute
Amazon
EC2 instances
(Compute and
accelerated)
Amazon EC2 Spot
AWS Auto Scaling
Visualization
NICE DCV
Amazon
AppStream 2.0
Networking
Enhanced
networking
Placement
groups
Elastic Fabric
Adapter
Amazon FSx for
Lustre

High Performance Computing (HPC) on AWS
Virtual Private Cloud on AWS
3D graphics virtual workstation
License managers and cluster head
nodes with job schedulers
Cloud-based, auto-scaling HPC clusters
Shared file storage Storage cache
On AWS, secure and well-
optimized HPC clusters can
be automatically created,
operated, and torn down in
just minutes
Encryption everywhere—
With your own keys!
Amazon S3
and Amazon Glacier
On-premises
HPC resources
Corporate datacenter
AWS Snowball
AWS Direct Connect
Thin or zero client—
no local data
Third-party IP providers
and collaborators
Machine learning
and analytics

Broadest and deepest compute platform choice
Categories Capabilities Options
+ + =
175instance types

Broadest choice of processors and architectures
Right compute for the right application and workload
Intel® Xeon®
Scalable (Skylake)
processor
AMD EPYC
processor
AWS Graviton
Processor
Xilinx UltraScale+
FPGA
NVIDIA V100
Tensor Core
GPUs

Hypervisor
Management,
Security, and
Monitoring
Storage
Compute
Instances
Network
Nitro Architecture
 Nearly 100% of
resources available
for compute
 Improved security
SERVER
NITRO

Wide range of compute instances for HPC
workloads
General
purpose
Dense
storage
Compute
optimized
FPGA
GPU
Compute
Storage
optimized
Graphics
intensive
Memory optimized
High I/O
R5
R5d
R4
EC2
Bare Metal
R5a
High
I/O
General
purpose
burstable
Direct
access to
physical
server
resources
Virtual
Private
Servers
Amazon
Lightsail
X1 X1eT2
T2
Unlimited
M4
M5
M5d
C5
C5n
C4 I3I2 I3m G2 G3 P2
P3
P3dn
F1
Compute &
memory
intensive
Z1d Z1dmD2 H1
EC2 Elastic GPUs
Graphics acceleration for EC2
instances
EC2 Fleet
• Simplified provisioning
• Massive scale
• Flexible capacity allocation

High bandwidth compute instances: C5n
HPC stack on AWS
Massively scalable performance
• C5n Instances will offer up to 100 Gbps of
network bandwidth
• Significant improvements in maximum bandwidth,
packet per seconds, and packets processing
• Custom designed Nitro network cards
• Purpose-built to run network bound workloads including
distributed cluster and database workloads, HPC, real-time
communications and video streaming
Featuring

High clock speed compute instances: Z1d
HPC stack on AWS
Up to 4 GHz sustained, all-turbo performance
• Z1d instances are optimized for memory-intensive, compute-
intensive applications
• Custom Intel Xeon Scalable processor
• Up to 4 GHz sustained, all-turbo performance
• Up to 385GiB DDR4 memory
• Enhanced networking, up to 25 GB throughput
Featuring

High bandwidth compute instances: P3dn
HPC stack on AWS
Optimized for distributed ML training
• One of the most powerful GPU instance available in the cloud
• Distributed machine learning training across multiple
GPU instances
• 100 Gbps of networking throughput
• Based on NVIDIA’s latest GPU Tesla V100 with 32GB
of memory each
• The largest Amazon Elastic Compute Cloud (Amazon EC2)
P3 instance size available

M5d
Ideal for workloads
that require a balance
compute, memory, and
networking.
Compute intensive
workloads
Advanced memory
intensive workloads.
High compute and
memory workloads.
Currently the fastest
available instance.
local NVMe-based SSD block-level , high-speed, low-latency storage options.
C5d R5d z1d$
M5d Instances C5d Instances R5d Instances z1d Instances
Instances with local storage

Comprehensive portfolio of high performance
storage options
Block Storage File Storage Object Storage
Amazon EBS
Amazon EFS
gp2io1
st1 sc1
Amazon S3
HDD
SSD
FSx for Lustre
FSx for
Windows File
Server
S3 Multi-
tiering
Glacier

Fully managed high performance shared file
system: Amazon FSx for Lustre
HPC stack on AWS
High
performing
Parallel
distributed
file system
Tune complex
performance
parameters
Massively scalable performance
• 100+ GiB/s throughput
• Millions of IOPS
• Consistent low latencies

High Performance Interconnect for HPC applications:
Elastic Fabric Adapter (EFA)
HPC stack on AWS
Scale MPI-based applications on AWS
• Super-low latency for message passing
• Improves application performance
• Enables HPC applications to take advantage of the
flexibility and elasticity of AWS Cloud
• Support for industry-standard Message Passing Interface
(MPI) facilities migration of existing HPC applications to
AWS with no code changes

HPC software stack in Amazon EC2
Userspace
Kernel
Without EFA With EFA

What can EFA do?

Easy cluster management: AWS ParallelCluster
HPC stack on AWS
Create and manage HPC clusters
• Simplifies deployment of HPC in the cloud, including
integrating with popular HPC schedulers
• Built on AWS CloudFormation, easy to modify to meet
specific application or project requirements
• Now integrated with AWS Batch
• ParallelCluster now supports FSX Lustre and EFA

AWS Batch
AWS Batch dynamically provisions
resources
Plans, schedules, and executes
No batch software to install
Focus on your applications and results!

Efficient job scheduling: Multi-node parallel job
support on AWS Batch
HPC stack on AWS
Simplify your compute clusters and scale jobs across
multiple instances with AWS Batch support for
Multi-node Parallel (MNP) jobs
Container 2
Container 4Container 3
Container 1

AWS pricing principles

Simplifying capacity and cost-optimization
Reserved Instances
for known/steady-state workloads
Scale using
On-Demand,
Spot,
or both
AWS services make this easy and efficient
Now with hibernate on-demand
Amazon Elastic
Container Service
Amazon
EMR
AWS
CloudFormation
AWS BatchAmazon EC2
Auto Scaling
Amazon Elastic
Container Service
for Kubernetes
EC2 Fleet AWS
Thinkbox

Broad HPC partner community
Application partners Infrastructure partners Technology partners Consulting partners

Customer innovations enabled by HPC on AWS

® 2019 Amazon Web Services Inc. or its Affiliates. All rights reserved.
QRT delivers investment strategies faster using AWS
• QRT lacked the scalability and agility to use compute capacity on demand and
keep pace with data growth, which meant it could not generate new alpha
fast enough for its business
• QRT chose to run its HPC platform on AWS, enabling the company to analyze
large volumes of data, unconstrained by capacity issues and no longer
needing to restrict analysis to a subset of historical data due to escalating
storage costs
• As a result, QRT has been able to drive better investment recommendations,
bring new strategies to market in weeks instead of six months, and onboard
new researchers faster
Qube Research &
Technologies (QRT)
is a quantitative and systematic
investment management firm based in
London. The company offers services
including wealth management, financial
planning, and investment advisory to
customers across the globe.
We can integrate trading data from more data sources each day by scaling our HPC
system on demand on AWS.
– Nick Harris, Chief Technology Officer, Qube Research & Technologies
“
”

Manage 50X the number
of securities
4,000 times faster
In hours, instead of months
Run risk models
Helping financial institutions
model investment risks

Large hedge fund: Quantitative Research
The challenge
A quantitative trading firm wanted to provide additional modeling capacity to its
researchers responsible for creating and developing risk and trading algorithms in order to
reduce the time required to see the results of their models and allow them to more rapidly
improve the efficacy of their trading strategies.
The solution
The firm piloted an implementation of its existing grid infrastructure, which could utilize
Amazon EC2 on-demand instances, significantly reducing analysis time. Reluctant to
increase costs, not wanting to lose existing responsiveness to the end users, and not
beholden to any regulatory or reporting deadlines, the firm turned to Amazon EC2 spot
pricing.
The result
Today, the firm is able to deploy over 80% of its instances using spot pricing, and has
achieved a 75% reduction in costs compared to the use of on-demand instances. This grid
is deployed across multiple availability zones in the eastern US and can peak up to 75,000
cores. The availability of accelerated compute instances was also a key benefit as their
grid relies primarily on GPU-enabled instances.

® 2019 Amazon Web Services Inc. or its Affiliates. All rights reserved.
AQR Capital leverages AWS to research new investment signals
• AQR makes investment decisions based on numerical models and
systematic trading. Their on-premises compute grid could not keep up
with demand, and the company needed a scalable solution in both
compute and memory that was fast without long queue times, easy to
use, and secure…and they didn’t want to manage a job scheduler.
• AQR leveraged core application services like Amazon S3, Amazon EC2,
and Amazon DynamoDB, added encryption at every level, and used
AWS Batch to plan, schedule, and execute computing workflows on
Spot instances.
• With AWS, AQR developed a solution to provide freedom to their
researchers while automating everything with virtually unlimited
compute, short start times, and no queues at lower costs.
AQR Capital Management
is a quantitative asset
management firm with $196
billion AUM with over 40
strategies, ranging from traditional
to alternative products
We can back test 20,000 equities times 20 years worth of data, creating an
enormous amount of jobs all at once...using spot, we lowered our costs to
$15 for 500 physical cores. That is an incredibly low price and something we
cannot match on premises.
– Michael Raposa, Head of Platform Engineering, AQR Capital
“
”

3 million core-hours of
Amazon EC2 capacity
3.24 billion base pairs
Complete sequencing of
Saving koalas using
genomics research

FPGA Acceleration for Genomics
Acceleratingtime to science
“Orlando, Fla., Oct 19, 2017 – The Children’s Hospital of Philadelphia (CHOP) and Edico Genome today set a new scientific
world standard in rapidly processing whole human genomes into data files usable for researchers aiming to bring precision
medicine into mainstream clinical practice. Utilizing Edico Genome’s DRAGENTM Genome Pipeline, deployed on 1,000
Amazon EC2 F1 instances on the Amazon Web Services (AWS) Cloud, 1,000 pediatric genomes were processed in two hours
and 25 minutes. ”
single
HPC cluster of 1000 FPGAs

600 times faster
Engineering simulations
Helping to make supersonic
flights mainstream

Running HPC applications at extreme scale
Acceleratingtime to innovation
“Storage technology is amazingly complex and we’re constantly pushing the limits of physics and engineering to deliver next-
generation capacities and technical innovation. This successful collaboration with AWS shows the extreme scale, power and
agility of cloud-based HPC to help us run complex simulations for future storage architecture analysis and materials science
explorations. Using AWS to easily shrink simulation time from 20 days to 8 hours allows Western Digital R&D teams to
explore new designs and innovations at a pace un-imaginable just a short time ago.” – Steve Phillpott, CIO, Western Digital
single
HPC cluster of 1 million vCPUs

High-Performance-Computing-on-AWS-and-Industry-Simulation

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