Release notes

AgentKernelArena 0.1.0

Initial release of AgentKernelArena, a standardized arena for evaluating AI
coding agents on GPU kernel optimization tasks on AMD GPUs.

Multi-agent arena: run Cursor, Claude Code, Codex, SWE-agent, OpenEvolve
(GEAK), GEAK HIP, GEAK OptimAgent v2, GEAK OurLLM kernel-to-kernel, and
single-LLM-call agents through a common evaluation pipeline.
Multi-model support: OpenAI, Anthropic, and additional models via
OpenRouter or a self-hosted vLLM server.
Task categories: hip2hip, cuda2hip, triton2triton,
instruction2triton, torch2hip, and flydsl2flydsl, with bundled suites
from gpumode, vLLM, and ROCmBench.
Objective metrics: automated evaluation of compilation, correctness, and
real GPU performance speedups, combined into a single comparable score.
Workspace isolation: each task runs in a timestamped duplicate workspace
for reproducibility.
Resumable runs: resume an interrupted run and skip completed tasks with
--resume-run or --resume-latest.
A/B testing: run the same task set with and without an agent-side
capability to measure its real impact.
Task validator: a dedicated agent that runs 10 automated quality checks on
tasks and emits a validation_report.yaml.
Visualization dashboard: a static dashboard for comparing run reports
across agents and models.
ROCm environment auto-detection: the Makefile detects ROCm 6.4, 7.0, or
7.1 and installs the matching PyTorch build.