ByteMLPerf is an AI accelerator benchmark suite designed to evaluate hardware from a practical production perspective, focusing on ease of use and versatility. It targets AI hardware vendors and researchers seeking to benchmark inference, training, and micro-operation performance, offering a more realistic assessment aligned with business use cases.

How It Works

The benchmark is structured into three categories: Inference (General Performance and Large Language Models), Micro (fundamental operations like Gemm, Softmax), and Training (currently under development). It emphasizes practical use cases and includes metrics beyond raw performance, such as compiler usability and coverage for ASIC hardware, providing a holistic evaluation.

Quick Start & Requirements

Vendor-specific guides are available for building inference (general and LLM) and micro-operation backends. A vendor list with hardware specifications and backend introduction links is provided.

Highlighted Details

• Evaluates AI accelerators from a practical production perspective.
• Includes metrics for compiler usability and coverage for ASIC hardware.
• Structured into Inference (General, LLM), Micro, and Training categories.
• Offers reference metrics using an open Model Zoo for ASIC hardware evaluation.

Maintenance & Community

Official website: bytemlperf.ai. A vendor list is maintained, showcasing hardware integrations.

Licensing & Compatibility

The README mentions an "ASF Statement on Compliance with US Export Regulations and Entity List," but no specific open-source license is stated. Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The Training category is still under development. The specific open-source license is not clearly stated in the README, which may impact commercial adoption or integration with closed-source projects.