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.
Find out more about creating GPU-enabled pricing and risk models by signing up for this FREE seminar.
A Seminar on GPU-Accelerated
Derivative Pricing and Risk Models in Frankfurt am Main |
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| When: | Wednesday, January 20, 2010 17.00-18.00 hour Reception to follow |
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| Where: | Auditorium der Commerzbank AG Große Gallusstraße 19 D-60261 Frankfurt am Main, Germany |
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For more info:
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| SciComp
Inc., 5806 Mesa Drive, Suite 250, Austin TX 78731, 512-451-1050, www.scicomp.com NVIDIA Corporation, 2701 San Tomas Expressway, Santa Clara, CA 9505, 408-486-2000, www.nvidia.com ©2010 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."
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