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Show HN: A free, GPU-accelerated Texas Hold'em GTO solver in C++/CUDA (bupticybee.github.io)

1 points by bupticybee ↗ HN
I built this mostly because I love the intersection of game AI, high-performance computing, and poker.

I’d love for anyone interested in game theory or CUDA optimization to tear it apart, test the accuracy, and give me feedback. Happy to answer any questions about the algorithms, the transition from CPU to GPU, or poker AI in general!

5 comments

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rh94
I’ve done good deal of cfr/deepstack work my self, can you tell us bit more details how it works under the hood?

In particular, what is the gpu part?

bupticybee
GPU is good at doing parallel task that in nature is the same. So it fit perfectly in CFR context. CFR is basically doing a lot of similar work across nodes. So if you implememnt a cuda kernel for regret matching, it will accelerate the solving process a lot.
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visox
how much work would it be to make it work on some other card game? :D