5918

High performance finite difference PDE solvers on GPUs

Daniel Egloff
QuantAlea GmbH
Technical report, QuantAlea GmbH, February 2010

@techreport{egloff2010high,

   title={High performance finite difference PDE solvers on GPUs},

   author={Egloff, D.},

   year={2010},

   institution={Technical Report, QuantAlea Gmbh}

}

Download Download (PDF)   View View   Source Source   

3216

views

We show how to implement highly efficient GPU solvers for one dimensional PDEs based on finite difference schemes. The typical use case is to price a large number of similar or related derivatives in parallel. Application scenarios include market making, real time pricing, and risk management. The tridiagonal systems in the backward propagation of a finite difference scheme are solved with parallel cyclic reduction. This is a fine-grained parallel tridiagonal solver, which is well adapted to the hierarchical architecture of a modern GPU. We explain in detail the calculation work flow and study the performance of the solver relative to a well optimized CPU implementation. Our timings demonstrate performance improvement factors 25 on a single GPU and 38 on two GPUs.
Rating: 4.0/5. From 1 vote.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: