GPU-CFR: 80x Faster Counterfactual Regret Minimization by Compiling the Game to Static Dataflow and CUDA Graph Replay
GPU-CFR turns fixed-game CFR iterations into replayable GPU work instead of millions of tiny dispatched steps.
The paper says CFR has stayed CPU-friendly because GPU runs get buried under kernel-launch and framework overhead. Boning Li and Longbo Huang compile a game once into static dataflow, then use CUDA Graph Replay so each iteration can run as a single graph launch. On an A100, they report 29.8–80.4x speedups over the fastest prior GPU CFR baseline, and 14–258x over LiteEFG on the four largest games. ArXiv · AI/CL/LG's note
The paper says CFR has stayed CPU-friendly because GPU runs get buried under kernel-launch and framework overhead. Boning Li and Longbo Huang compile a game once into static dataflow, then use CUDA Graph Replay so each iteration can run as a single graph launch. On an A100, they report 29.8–80.4x speedups over the fastest prior GPU CFR baseline, and 14–258x over LiteEFG on the four largest games. ArXiv · AI/CL/LG's note
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