Scientific Simulation Platform presentation

1. Scientific Simulation Platform created using a kernel for parallel
computations with Microsoft DirectCompute.
Gubanov Oleg Igorevich
(CEO Omenart Technology)
GPUDIGITALLAB

2. PROJECT HISTORY
I started experimenting with 3D graphics technologies since 2005.
During my second year at Aberystwyth University I had my first
exposure to 3D graphics technologies.
I have spent my industrial year at Microsoft Reading working on a
game engine prototype that would later be a part of Microsoft
DirectX Engine in Windows 8.
My final year project was a 3D Engine prototype Imagine3D – a
simulation system where you can create 3D cartoons by loading
graphics from a 3D package and then program the animation
scenario using a scripting language

3. GPUDIGITALLAB CONCEPT
• At the heart of the simulation system there is a computational kernel. Using the kernel we
can perform calculations on compute shader technology.
• The complex task can be split into a set of independent processes called computational
agents.
• The agent management framework controls the behavior of every agent created and
updates the final outcome of the computations.
• The result of the computations can be used to program the 3D animation of a graphics
model.
• On startup the kernel loads up the rendering ray-tracer and render to texture modules in
order to visualize the process of 3D animation

4. KERNEL STRUCTURE
Main
Kernel
Algorithm
Executor
Domain Manager
Raytracing
Engine
Computational Agent
Framework
Connected
Application Manager
Mathematical
Modelling Engine

5. DIAGRAM DESCRIPTION
• Main Kernel – primary start point of the engine. Launches the subsystem modules and
processes events
• Algorithm Executor – module to execute computations using compute shaders with
installed data set
• Computational Agent Framework – system to split the complex task into a set of smaller
algorithms and collect the outcomes
• Connected Application Manager – module to interchange with system utilities based on
the application protocol
• Raytracing Engine – module to produce the video image of the mathematical model
simulation
• Mathematical model engine – module to load mathematical concepts from the knowledge
database.

6. SIMPLE COMPUTATIONAL ALGORITHM
IMPLEMENTATION
Load up the graphics framework
Launch the computational kernel
Launch the data processing engine
Load the compute shader
Create the data buffers

7. HOW TO USE GPUDIGITALLAB FOR
COMPUTATIONS
Open the cloud
server
www.gpudigitallab
.com
Launch the application Set the initial parameters
Select the application to
use
Process the results of
the computations

8. MATHEMATICAL MODEL ESTABLISHMENT AND
SIMULATION
Connect to the data
processing engine
Install the initial dataset
from excel file or MS
SQL Server Database
Open the Graphics
Framework
Load up the 3D Model Project
Analyze data and compute the
system of equations. Save
mathematical model
Program the animation of the
graphics object using the
mathematical model. Start the
simulation.

9. HOW TO SIMULATE AN ENVIRONMENT
• EXAMPLE: Solat System Simulation
• Launch Graphics Environment
• Launch Physics Engine
• Load 3D Models of the Solar System
• Connect to the Database
• Download Data and Compute the mathematical Model.
• Create a new simulation object
• Set Graphics
• Set Mathematical Model And Created Data.

10. PLANNED SOFTWARE UTILITIES FOR 2017-2018
• Image Processing Engine
• Voxelization Engine
• Fluid Dynamics Engine
• Chemical Reactions Simulation Engine
• Biological Processes Simulation Engine
• Power Plant Simulator
• Factory Simulator
• Car Race Simulator.

11. SCIENTIFIC SIMULATION DATA-CENTRE
PROJECT
• An institution building consisting of 2 separate block
• The 1-st block is the server room where we would install our clusters as well as cooling
mechanism for the servers.
• The 2-nd block is the visualization room where we would like to install plasma panels to
output the results of the scientific experiments that can be manipulated using Kinect
Sensors

12. SERVER BLOCK

13. VISUALIZATION BLOCK

14. HARDWARE REQUIREMENTS
Server
Model: GPX XT10-2260-6GPU
CPU: 2 x Six-Core Intel® Xeon® Processor E5-2630 v2 2.60GHz 15MB Cache (80W)
RAM: 8 x 4GB PC3-14900 1866MHz DDR3 ECC Registered DIMM
HDD: 250GB SATA 6.0Gb/s 7200RPM - 2.5" - Seagate Constellation.2™
4 x 800GB Micron M500DC 2.5" SATA 6.0Gb/s Solid State Drive
2 x 1.6TB Intel® DC S3500 Series 2.5" SATA 6.0Gb/s Solid State Drive
2 x 800GB Intel® DC S3700 Series 2.5" SATA 6.0Gb/s Solid State Drive
GPU: NVIDIA® Tesla™ K40M GPU Computing Accelerator - 12GB GDDR5 - 2880 CUDA
Cores
Network Card: Intel® 10-Gigabit Ethernet Converged Network Adapter X540-T1 (1x RJ-
45)
UPS: APC Smart-UPS 1000VA LCD 120V - 2U Rackmount
Operating System: Microsoft Windows Server 2012

15. SOFTWARE REQUIREMENTS
 Microsoft Visual Studio 2015 Ultimate
 Microsoft Windows Server 2012 Data-Centre Edition
 Microsoft Direct3D 11
 Microsoft DirectCompute
 Microsoft SQL Server 2014
 Microsoft Direct2D
 Microsoft Media Foundation
 NVIDIA PhysX
 NVIDIA OptiX
 OpenCV

16. OUR CURRENT INVESTOR PURPOSAL
• Estimated Technology Value – 15 000 000$
• Our Current Needs – 3 000 000$ during 5 years
• 1 year – 600 0000$
• 2 year – 800 000$
• 3 year – 800 000$
• 4 year – 800 000$
• Sales Forecast
• Scientific Cloud Services – 50 000$ (per month)
• Simulation Projects – 50 000$ (4 per year)
• 3D Graphics Simulators – 12 000$ (1 per moths)
• Total per year = 600 000 + 200 000 + 144 000 = 944 000$
• Total per 3 years = 944 000 * 3 = 2 832 000$
• Break Even Point – 3 years

17. DIRECTCOMPUTE FLUID SIMULATION