A
Seminar on GPU-Accelerated Derivative Pricing and Risk Models
Frankfurt am Main, Wednesday,
January 20, 2010
Presented by SciComp Inc. and NVIDIA Corporation
SciFinance® automatically generates GPU-enabled pricing & risk model source code that runs up to 220x faster than serial code using NVIDIA® Tesla™ GPUs.
SciFinance® is a derivatives pricing and risk model development tool that automatically generates C/C++ and GPU-enabled source code from concise, high-level model specifications. No parallel computing or CUDA programming expertise is required.
Find out more about creating GPU-enabled pricing and risk models by signing up for this FREE seminar. Learn about:
Register to see how easy it is to get started on accelerating your derivative pricing models
A Seminar on
GPU-Accelerated Derivative Pricing and Risk Models in Frankfurt |
||
| When: | Wednesday, January 20, 2010 17.00-18.00 hour Reception to follow |
|
| Where: | Auditorium der Commerzbank AG Große Gallusstraße 19 D-60261 Frankfurt am Main |
|
| RSVP: | REGISTER
HERE.
|
|
![]()
For more information:
![]() |
![]() |
![]()
©2009 SciComp Inc. SciFinance is a registered trademark of SciComp Inc. NVIDIA, the NVIDIA logo, CUDA and Tesla are trademarks or registered trademarks of NVIDIA Corporation in the United States and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. All rights reserved.
SciFinance® automates pricing and risk model development
SciPDE™ and SciMC™ are the core SciFinance modules
SciGPU™ achieves blazing fast performance with CUDA and OpenMP
SciCalibrator™ provides pricing model calibration
SciIntegrator™ eases integration
A resource site with examples, documentation and more...
Watch the SciFinance Parallel Computing movie:
Webinar: Automatic GPU computing for derivative pricing models
NEWS
Reval Speeds Up Pricing Complex Instruments in the Cloud with SciFinance
"We were looking for a cost-effective and easy-to-deploy solution to improve the pricing of complex derivative instruments using PDEs or Monte Carlo simulation in our SaaS product. We found it with SciFinance and GPU-enabled models, without having to become experts in parallel coding or CUDA."
"...the only thing you need to add to get GPGPU acceleration is literally 'CUDA'; it's a single keyword, not a fundamentally different way to formulate the math equations. This allows SciComp's customers to save even more time while also improving accuracy."
Beyond 3D