Helps AI assistants optimize Linux workloads on Arm64 by parsing perf report output, recommending NEON SIMD intrinsics for hot loops, and auditing Python dependency manifests for arm64 wheel availability — all offline and structured.
Vendor-neutral local LLM inference benchmark and hardware-config advisor for mlx and llama.cpp. Exposes an MCP tool that measures real tokens/second on your own hardware.
Provides AI assistants with tools for Arm architecture development, migration, and optimization, including knowledge base search, code migration analysis, container inspection, assembly performance analysis, and workload performance testing.
LLM deployment planner: given a model and a GPU, answers will it fit, will it hit your SLO, and what will it cost. Sizes VRAM and KV-cache from the model's real architecture, and labels every number measured, estimated, or unknown.
An MCP server that autonomously optimizes ONNX ML models for Arm64 deployment, providing tools to analyze models, apply real INT8 quantization, benchmark performance, and generate Arm64-optimized Docker deployment packages.
