I converted the double barrier option pricing code from my last post to run on the GPU, using C++ AMP, and got an 80% speedup.
This is running on a low powered Acer V5-122p laptop with an AMD A6-1450 processor with an integrated Radeon HD 8250 GPU.
The gist is here: https://gist.github.com/taumuon/bbeeb9e2c1f5082a2699
To be fair, I converted the CPU code to be otherwise identical to the gpu code. Instead of populating an array of the sample path, it instead for each point just determines whether the value breaches the upper or lower barriers and uses the last value for the payoff.
This reduced the runtime from the code in my last blog post, of 2540ms, to 1250ms, i.e. a 2x speedup.
The GPU code was ran twice, the first time it ran in 140ms, the second run (after all shaders already compiled etc) was 15.6ms, i.e. a very impressive 80x speedup from the CPU code.
If anything, it shows that AMDs strategy of cheap low powered laptop chips will payoff if people start taking advantage of the relatively strong GPU.
Labels: C++, GPGPU, Monte Carlo, QuantFinance