  Currently, there is no consistent benchmarking across multi-disciplines. Even
no previous work tries to relate different categories of benchmarks in
multi-disciplines. This article investigates the origin and evolution of the
benchmark term. Five categories of benchmarks are summarized, including
measurement standards, standardized data sets with defined properties,
representative workloads, representative data sets, and best practices, which
widely exist in multi-disciplines. I believe there are two pressing challenges
in growing this discipline: establishing consistent benchmarking across
multi-disciplines and developing meta-benchmark to measure the benchmarks
themselves. I propose establishing benchmark science and engineering; one of
the primary goals is to set up a standard benchmark hierarchy across
multi-disciplines. It is the right time to launch a multi-disciplinary
benchmark, standard, and evaluation journal, TBench, to communicate the
state-of-the-art and state-of-the-practice of benchmark science and
engineering.
