Performance analysis of a 240 thread tournament level MCTS Go program on the Intel Xeon Phi
S. Ali Mirsoleimani, Aske Plaat, Jos Vermaseren, and Jaap van den, Herik

TL;DR
This study evaluates the performance of a multi-threaded Monte Carlo Tree Search Go program on the Intel Xeon Phi, revealing good scalability up to 32 threads and challenges beyond that due to architectural and scheduling complexities.
Contribution
First empirical analysis of a complex AI application on the Xeon Phi, providing insights into its scalability and performance challenges for multi-threaded programs.
Findings
Performance scales well up to 32 threads
Performance deteriorates between 32 and 240 threads
Performance anomalies observed between Xeon Phi and Xeon CPU for small problems
Abstract
In 2013 Intel introduced the Xeon Phi, a new parallel co-processor board. The Xeon Phi is a cache-coherent many-core shared memory architecture claiming CPU-like versatility, programmability, high performance, and power efficiency. The first published micro-benchmark studies indicate that many of Intel's claims appear to be true. The current paper is the first study on the Phi of a complex artificial intelligence application. It contains an open source MCTS application for playing tournament quality Go (an oriental board game). We report the first speedup figures for up to 240 parallel threads on a real machine, allowing a direct comparison to previous simulation studies. After a substantial amount of work, we observed that performance scales well up to 32 threads, largely confirming previous simulation results of this Go program, although the performance surprisingly deteriorates…
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Taxonomy
TopicsArtificial Intelligence in Games · Video Analysis and Summarization · Digital Games and Media
