Azinta presented on their GPU cloud services for accelerating analytics, describing their offerings of dedicated GPU hosting with Nvidia Tesla GPUs through their partnership with Peer 1 Hosting, as well as Python/MATLAB acceleration, analytical algorithms, and derivative pricing services to reduce processing times from days to seconds using GPUs. They also compared their offerings to Amazon GPU clusters.

1. An Azinta Presentation for the London Financial Python User Group
17th January 2011
Azinta Systems Ltd
www.azinta.com
Commercial In Confidence - (c) Azinta 2011 17th January 2011

2.  Azinta Systems:
◦ Product and Systems Integration & Consultancy Company
 Azinta Solutions:
◦ Developed the APADO Business Agility Platform:
 APADO Platform integrates 30 Enterprise Open Source products
covering BPM, Business Rules, SOA, CEP, Analytics, Business Constraint
Optimisation into a single deployment platform – “Six Levers of Business
Agility”.
◦ GPU-Accelerated Analytics Cloud Services
 Provide GPU acceleration services, for non GPU experts, who want the
benefits of 400x increase in performance without having to become GPU
experts.
 Azinta Systems – A Protean Corporation
◦ (See book “The Future Arrived Yesterday: the rise of the Protean
Corporation” by Michael Malone)
◦ Azinta are “competence aggregators” who dynamically brings
people together with IP, products, services and expertise to solve
business problems
Commercial In Confidence - (c) Azinta 2011 17th January 2011

3.  Azinta GPU Cloud Services Comprises:
◦ Dedicated GPU Hosting Service – powered by PEER 1 Hosting GPU Cloud comprising:
 Nvidia Tesla M1070 GPUs
 Nvidia Tesla M2050 GPUs (Fermi)
 Azinta is GOLD partner of PEER 1 Hosting
◦ Python, Matlab, R and Mathematica Acceleration
 Accelerate algorithms by up to 1000x. Azinta provides GPU algorithm tuning
services
◦ GPU-Accelerated Analytics Services
 Conduct analytical and data mining processing on large data sets using GPU
acceleration
 Reduce analytical data processing from days, hours to minutes, seconds
 Azinta provides analytical algorithms tailored for GPUs service; removing the need
for domain modellers to be GPU development experts
◦ GPU-Accelerated Derivative Pricing and Valuations
 Develop near real-time pricing and risk management models optimised for GPU
acceleration
◦ Custom GPU Development Services
 Off-shore GPU development services (India + Eastern Europe)
 GPU software development services using Python, Matlab, R, C, C** for both
Windows and Linux.
Commercial In Confidence - (c) Azinta 2011 17th January 2011

4.  Fermi contains 16 SM:
◦ Each containing 32 cores
◦ Each core contains one integer
and one floating-point maths unit
◦ Each SM can schedule two groups
of 32 threads at once
◦ Each SM contains 4 Special
Function Unit for complex maths
such as sine and cosines
◦ Total of 512 cores
◦ 64kb shared L1 cache
◦ All 16 SM can access 768kb L2
cache and can access up to 6GB of
GDDR5 memory over 384 bit
interface with ECC support
◦ Supports tens of thousands of
concurrent threads
Fermi delivers 1 teraflop single
One of the Fermi 16 Streaming precision OR 515 double
Multiprocessors (SM) precision gigaflops per GPU
Commercial In Confidence - (c) Azinta 2011 17th January 2011

5.  Notes
◦ GPU require CPUs where the sequential code is
executed on the CPU and massively parallel
processing is executed on the GPU
◦ Data to be processed is transferred from the CPU
memory to the GPU GDDR 5 memory
◦ A GPU requires at least one CPU core for execution
◦ There are two main GPUs families:
 Nvidia CUDA GPUs – the market leaders with rich
ecosystem of development tools + applications
 AMD Fusion GPUs – the challengers.
 Since there are as yet no AMD GPU cloud services we
will focus only on Nvidia CUDA GPUs.
Commercial In Confidence - (c) Azinta 2011 17th January 2011

6.  In 2015 Nivida Predicts CUDA GPUs will be:
◦ 20x the performance of the Fermi
◦ 5,000 cores instead of 512 cores in the Fermi
◦ 20 TFLOPS
◦ 1.2 TB/s of memory bandwidth
◦ This GPU is called Maxwell
 In 2012 the Kepler GPU will arrive with 4x
performance of Fermi
Commercial In Confidence - (c) Azinta 2011 17th January 2011

7. ◦ Massive acceleration of Financial, Risk Management
and Analytical Applications create high value:
 Traditionally GPUs have been used for pricing and
valuation of derivatives and to support front and back
office operations
 However there are many other applications – Namely
any application that requires statistical, mathematical
and analytical modelling coupled with processing of
large data sets can get a significant speed up typically
400x to 1000x or more
 There is a link between speed of processing and
additional revenues a company can make or to
mitigate losses from real-time analysis
Commercial In Confidence - (c) Azinta 2011 17th January 2011

8. ◦ For further information on some of the analytical
performance improvements that GPU can deliver
see my blog post: “GPUs for Large Scale Data
Mining” http://goo.gl/dH0i
◦ Also for my vision on how distributed processing
across GPU clusters could be implemented see my
blog post: “Scaling up GPUs for Big Data Analytics,
MapReduce and Fat Nodes” http://goo.gl/jG4Q
◦ /
Commercial In Confidence - (c) Azinta 2011 17th January 2011

9.  So why Python and GPUs?
◦ Python is very good for Financial and Analytical
modeling and the rapid production of prototypes which
can then be deployed into production applications
◦ Developing good GPU kernels is non-trivial exercise and
is normally done using C or C++ with a deep knowledge
of how massively parallel processing should be
implemented on GPUs
◦ What you want is the ability hide the complexity of the
GPU world using efficient Python wrapper libraries that
will generate the required C code for the GPUs and
handle data transfers between the GPU and the CPU.
Commercial In Confidence - (c) Azinta 2011 17th January 2011

10.  Many Python CUDA Software options:
◦ PyCUDA http://mathema.tician.de/software/pycuda
◦ Tutorial Slides
http://mathema.tician.de/news.tiker.net/files/main
.pdf
◦ PyCUDA documentation
http://documen.tician.de/pycuda/
◦ Theano
http://deeplearning.net/software/theano/tutorial/u
sing_gpu.html
◦ Ian Ozsvald gave an excellent talk on Python and
GPU programming at a recent London Financial
Python User Group meeting
Commercial In Confidence - (c) Azinta 2011 17th January 2011

11.  Development & Prototyping
◦ Question:
 I have a PC that has an Nvidia GPU card is this ok for development and
prototyping?
◦ Answer:
 No because it will be based on earlier versions of the GPU and will not
have all the new hardware and software features of the Fermi. Plus it is
not likely to have the on GPU memory you need.
◦ Using a GPU Hosted Service gives you:
 No need to use out of date GPU development environment.
 No need to get IT approval to add GPU clusters into your data centre for
your prototyping and development.
 Get full proactive support so that you do not have to manage and
support the GPU infrastructure.
 Jump-Start Service Kit to get you up and running on your development
environment.
 No up-front capital investment… Pay as you go.
Commercial In Confidence - (c) Azinta 2011 17th January 2011

12.  Production Deployment:
◦ Question:
 I have finished my Python/GPU application and I want to
deploy it, but no space in data centre to support new GPU
clusters. What are my options?
 How can I quickly deploy my production application securely
and keeping to EU/Corporate regulations on data storage
location?
 Also the application requires Windows so CPU attached to
the GPUs must support Windows, is this supported?
◦ Answer:
◦ Use a secure fully hosted dedicated GPU clusters, located
in the UK with full proactive support and network
security monitoring. Depending on your cloud provider
Windows is supported.
Commercial In Confidence - (c) Azinta 2011 17th January 2011

13. NVIDIA Tesla S1070 GPU Sever Specs: Prices start at:
Cloud
Dell R710 Server $18/GPU/Day
4 x Tesla 1070 GPUs $365/GPU/Month
2 x Intel 5520 Quad Core Processors
16GB RAM
NVIDA Tesla M2050 GPU Server Specs Prices start at:
Cloud
SuperMicro 1U Server $30/GPU/Day
2 Fermi 2050 GPUs $720/GPU/Month
2 x Intel 5520 Quad Core Processors
16 GB RAM
Notes:
• Both Windows and Linux Operating Systems supported (Amazon only support Linux)
• Supports all Windows CUDA debugging tools (not supported on Amazon)
• 2TB data transfer per month provided for free (Amazon charges extra for this)
• GPU networks comprising between 100 and 200 GPUs have been configured for clients in
the banking and insurance sectors.
• Technical support manager provided (Amazon has a utility support not personalised)
• Peer 1 has data centres based in UK and Canada (Amazon only in the USA)
• Major customers such as Microsoft, MathWorks, Autodesk, Mental Images, many clients
in banking and insurance. New 55,000 sq. ft. data centre in London opening in 2011
• Many GPU app require full access to CPU power (Amazon only provides VMs)
Commercial In Confidence - (c) Azinta 2011 17th January 2011

14. Cluster GPU Instances Sever Specs: Prices start at:
22 GB of memory $25/GPU/Day
33.5 EC2 Compute Units (2 x Intel $756/GPU/Month
Xeon X5570, quad-core “Nehalem”
architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
Notes:
• Amazon GPU Clusters only support Linux operating system
• Amazon GPU Clusters are only available within the USA
• Data transfers and inter-node cluster transfers are chargeable at extra costs
• No CUDA third-party development and debugging tools such as NVIDIA
Parallel Nsight for Microsoft Visual Studio
• No dedicated proactive support manager
Commercial In Confidence - (c) Azinta 2011 17th January 2011

15.  Amazon GPU Cluster Offerings:
◦ If your GPU applications are Linux only and you have experience
of using Amazon cloud services
◦ If you have no requirement for EU based GPU clusters EU based
data storage
◦ If you do not need data centre in UK/London to eliminate trans-
Atlantic network latencies.
 PEER 1 GPU Cluster Offerings
◦ If your GPU Application require Windows and or Linux
◦ If you require a secure dedicated hosting with firewalls and
network monitoring
◦ If you require a UK based GPU data centre (London data centre
opening 2011) to meet your EU storage requirements and to
eliminate trans-Atlantic network latencies
◦ If you want to use development tools such as Nvidia Parallel
Nsight for Microsoft Visual Studio and other Windows applications
◦ If you want an assigned support manager for proactive help and
support
Commercial In Confidence - (c) Azinta 2011 17th January 2011

16.  PEER 1 Hosting:
◦ One of the world’s leading IT hosting providers
◦ Over 10, 000 customers world-wide
◦ 10GB SuperNetwork ™ connected to 17 data
centres, 21 point-of-presence and 10 collocation
facilities through-out North America and Europe.
◦ 100% uptime guarantee 24x7x365
◦ Portfolio includes: Managed Hosting, Dedicated
Servers, Colocation and Cloud Services
◦ Headquartered in Vancouver Canada
◦ Traded on the TSX under the symbol PIX
◦ Website: http://www.peer1hosting.co.uk/
Commercial In Confidence - (c) Azinta 2011 17th January 2011

17.  To find out how GPU’s can provide
substantial revenue generation or real-time
risk mitigation:
◦ Consider implementing a Proof-of-Concept (PoC).
◦ To discuss how Azinta can help you in your project
email me at suleiman.shehu@azinta.com or
call me +44 (0) 845 658 6909
Commercial In Confidence - (c) Azinta 2011 17th January 2011

18. Millennium House
3 Humber Trading Estate
Humber Road
London
NW2 6DW
Tel: +44 (0) 845 658 6909
www.azinta.com
suleiman.shehu@azinta.com
Commercial In Confidence - (c) Azinta 2011 17th January 2011