ray-project / ray

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

mlcommons / ck

Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks.

microsoft / nvx

Cross-Platform Micro-VM Sandbox for Agentic Workloads

spark-arena / sparkrun

sparkrun - launch, manage, and stop LLM inference workloads on NVIDIA DGX Spark systems. Live support: https://discord.com/invite/GH5kRgv6ZD

apimart-66 / openai-compatible-api-migration-kit

OpenAI-compatible API migration kit: drop-in /v1/images/generations and chat examples, a compatibility matrix, rollback switches and a checklist for moving workloads between AI API gateways.

EmbrasureAI / spark-observability-skills

Open-source agent skills for debugging and optimizing Apache Spark workloads

OpenPerfAgent / who-ate-my-flops

A small plugin for Claude Code and Codex to optimize PyTorch workloads.

DocPang / qwen38-k100ai-int8-optimization

Qwen3.8-27B INT8/W8A8 optimization for Hygon K100AI: SGLang, TP1/TP4, DFlash2 and long-context Agent workloads

WestWaters / pollard-weights

A tiered-memory system design for workloads that don't fit in RAM: measure the working set, pin the hot tier, stream the cold tier from flash. Ships the residency calculator, measurement harnesses, and the build recipes behind it. Predictions validated against public benchmarks.