mlperc
mlperc is an open-source software project that provides benchmarking and profiling tools for machine learning workloads. It helps researchers and practitioners evaluate performance across models, datasets, hardware, and software stacks in a reproducible and transparent manner. Central to mlperc is collecting and analyzing latency, throughput, memory usage, and energy consumption, with percentile-based metrics (for example p50, p90, p95, and p99) to summarize tail behavior.
Key features include a benchmark harness to define workloads, support for common ML frameworks, configurable targets
Architecture is typically modular, with a workload driver, a measurement layer, and a results aggregator. It
Status and governance are community-driven; licensing and release cadence vary by distribution. See also MLPerf, ML
Notes: publicly available information on mlperc may be limited, and the term may refer to different tools