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    Programming CUDA-enabled GPUs

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    If you are new to GPU computing or would like to add to your knowledge of NVIDIA CUDA programming and Tesla hardware then this resource CD is for you.

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SciFinance: GPU-Accelerated Derivatives Pricing Models without Learning CUDA Programming.

 
 
SciFinance®, SciComp Inc.'s flagship product, automatically generates CUDA-enabled source code for any financial derivatives pricing model that employs a Monte Carlo or PDE (partial derivative equation) methodology. No hand-coding, no CUDA programming or parallel computing expertise necessary. More information about GPU computing with SciFinance.

SciFinance is part of an effective derivatives portfolio/risk management solution.

Accurately measuring, managing and hedging derivatives risk exposure in a timely fashion is a primary objective for financial institutions. Fast, accurate derivative pricing models are therefore of key importance.

SciFinance automatically generates NVIDIA CUDA-enabled source code for derivatives pricing models.
  • CUDA Monte Carlo pricing models:
    • 30X-50X faster than serial code (single GPU, double precision)
  • CUDA PDE pricing models
    • 10X-35X faster than serial code (single GPU, double precision)

Brief Overview Movie of GPU Computing with SciFinance
SciFinance-generated Derivatives Pricing Model Examples
More on SciFinance
> Download the SciComp / NVIDIA Tech Brief to learn more

SciFinance is a cross-platform derivatives pricing model source code generator that automatically creates C/C++/CUDA source code from concise, keyword-rich pricing model specifications.

> How does SciFinance work?

  • Select from hundreds of provided pricing model specifications
  • Modify the model specification as needed
  • Test the serial version of the pricing model
  • Add keyword "CUDA" to the specification and re-synthesize
  • SciFinance does the rest by automatically generating fully documented GPU-enabled pricing model source code
Recommended Professional Products
The powerful GPU computing capabilities in SciFinance were developed on Tesla GPU computing products and benefit from the use of recent CUDA-capable NVIDIA GPUs, such as NVIDIA Tesla 10-series or 20-series products. (Learn More).

Tesla GPU computing products are designed to deliver the highest computational performance with the most reliable numerical accuracy, and are available and supported by the world's leading professional system manufacturers.

Tesla Benefits
Highest Computational Performance
> High-speed double precision operations
> Large dedicated memory
> High-speed bi-directional PCIe communication
> NVIDIA GPUDirect™ with InfiniBand
Most Reliable
> ECC memory
> Rigorous stress testing
Best Supported
> Professional support network
> OEM system integration
> Long-term product lifecycle
> 3 year warranty
> Cluster & system management tools
   (server products)
> Windows remote desktop support
 
Recommended Tesla & Quadro Configurations
High-End Workstation
> Two Tesla C2050/C2070/C2075
> NVIDIA Quadro Graphics Card
> Dual six-core or quad-core CPUs
> 12-24 GB system memory
Mid-Range Workstation
> Tesla C2050/C2070/C2075
> NVIDIA Quadro Graphics Card
> Single quad-core CPU
> 8-12 GB system memory
Entry Workstation
> Tesla C2050/C2070/C2075
> NVIDIA Quadro 600
> Single quado-core CPU
> 4-8 GB system memory

NVIDIA products are available from all major professional workstation OEMs. Only Tesla GPU computing products are designed and qualified for compute cluster deployment.

Other Featured Partners and Resellers

For a complete list of Tesla Preferred Providers, click here.