  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 between 32 and 240 threads.
Furthermore, we report (1) unexpected performance anomalies between the Xeon
Phi and Xeon CPU for small problem sizes and small numbers of threads, and (2)
that performance is sensitive to scheduling choices. Achieving good performance
on the Xeon Phi for complex programs is not straightforward; it requires a deep
understanding of (1) search patterns, (2) of scheduling, and (3) of the
architecture and its many cores and caches. In practice, the Xeon Phi is less
straightforward to program for than originally envisioned by Intel.
