AIBench Training: Balanced Industry-Standard AI Training Benchmarking

Understand

Earlier-stage evaluations of a new AI architecture/system need affordable benchmarks.

• Only using a few AI component benchmarks like MLPerfalone in the other stages may lead to misleading conclusions.
• Moreover, the learning dynamics are not well understood, and the benchmarks' shelf-life is short.
• This paper proposes a balanced benchmarking methodology.