Large-scale Analysis of Chess Games with Chess Engines: A Preliminary
  Report
  The strength of chess engines together with the availability of numerous
chess games have attracted the attention of chess players, data scientists, and
researchers during the last decades. State-of-the-art engines now provide an
authoritative judgement that can be used in many applications like cheating
detection, intrinsic ratings computation, skill assessment, or the study of
human decision-making. A key issue for the research community is to gather a
large dataset of chess games together with the judgement of chess engines.
Unfortunately the analysis of each move takes lots of times. In this paper, we
report our effort to analyse almost 5 millions chess games with a computing
grid. During summer 2015, we processed 270 millions unique played positions
using the Stockfish engine with a quite high depth (20). We populated a
database of 1+ tera-octets of chess evaluations, representing an estimated time
of 50 years of computation on a single machine. Our effort is a first step
towards the replication of research results, the supply of open data and
procedures for exploring new directions, and the investigation of software
engineering/scalability issues when computing billions of moves.
