A parallel design of computer Go engine on CUDA-enabled GPU
Qifei Zhang, Zhiqing Liu
Abstract
Qifei Zhang, Zhiqing Liu
Abstract
With the rapid growth of Graphics Processing Unit (GPU) processing capability, using GPU as a coprocessor to assist the CPU in parallel computing has become indispensable. CUDA (Compute Unified Device Architecture) programming model also gives C/C++ language support which makes programming easily. This paper details how to design an engine of computer Go with Monte-Carlo algorithm which is based on GPU with Fermi architecture. We analyze the characteristics of Monte-Carlo algorithm, combined with the CUDA architecture features, divide the algorithm into various sub-modules for GPU computing fast and easily.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
With the rapid growth of Graphics Processing Unit (GPU) processing capability, using GPU as a coprocessor to assist the CPU in parallel computing has become indispensable. CUDA (Compute Unified Device Architecture) programming model also gives C/C++ language support which makes programming easily. This paper details how to design an engine of computer Go with Monte-Carlo algorithm which is based on GPU with Fermi architecture. We analyze the characteristics of Monte-Carlo algorithm, combined with the CUDA architecture features, divide the algorithm into various sub-modules for GPU computing fast and easily.
Key concepts: CUDA, Coprocessor, Computer science, Graphics processing unit, Parallel computing, General-purpose computing on graphics processing units, Graphics, Architecture