Hyperloom v1.0.0a1

Highlights

Unified macro-cycle orchestration and budget accounting

Short and long sessions now share the same cyclic optimization model. Phase budgets use consistent charge-back accounting, short runs stop dispatching after their phase budget is exhausted, and new macro-cycles only start when at least three hours remain. This removes legacy cyclic-mode branches and makes phase progression more predictable across bounded and long-horizon runs.

Opt-in Ray serving and GPU execution

The opt-in Ray path now places all serving and GPU-specialist operations under the whole-machine serving_slot mutex, including framework-agent benchmarks, integrate_patch, and concurrency sweeps. GPU specialists can queue without blocking the Coordinator, serving receives scheduling priority, and stale AITER JIT locks are cleaned before server launch. Local subprocess execution remains the default; multi-node behavior is unchanged.

vLLM and serving-environment reliability

Hyperloom now isolates co-located Ray heads, uses per-session free ports for persistent serving processes, and reaps orphaned vLLM/SGLang process groups safely. Package-root MAGPIE_PATH entries are kept out of PYTHONPATH, preventing main-environment Torch packages from shadowing isolated vLLM environments. TraceLens patching and dependency discovery also support isolated vLLM/AITER installations more reliably.

GEAK-first kernel optimization

GEAK is now the default owner of the complete KERNEL phase. Forge remains an explicit opt-in and runs only when KERNEL_OPT_BACKEND_ORDER=forge is set. GEAK candidates remain provisional until Hyperloom revalidates them with its benchmark harness; successful revalidation can now complete before SWEEP begins, while failed or inconclusive validation exits cleanly without blocking the session.

Baseline, evaluation, and reporting integrity

Relative evaluation-result paths are resolved against the benchmark output directory, preventing false baseline-accuracy failures. Persistent servers use unique ports across retries, framework-phase gains are attributed correctly in session breakdowns, and concurrency-sweep internal tasks are no longer rejected by their own singleton policy.

Security and policy hardening

Multi-node restart arguments are validated and shell-quoted before execution. Explicit framework source roots must remain inside the configured allowlist, and queued tasks are revalidated by PolicyGate before dispatch to prevent forged task rows from bypassing normal authorization and Critic gates.

CI and release engineering

Every PR targeting main now runs a single-GPU Qwen3 smoke test on the dedicated Hyperloom E2E runner. The sharded Python 3.10/3.11 test suite has stronger failure visibility and completeness checks. Release version reporting now comes from installed package metadata, keeping hyperloom.inference_optimizer.__version__, wheel metadata, and the release version aligned.

What's included

Orchestration and phase behavior

• Unify short/long macro-cycle behavior and charge-back phase budgeting — #954
• Expand Ray serving_slot coverage and improve eval/JIT reliability — #955
• Invoke the Framework Agent through python -m instead of PATH lookup — #964
• Preserve queued GEAK win revalidation before SWEEP — #999

vLLM, serving, and installation

• Isolate vLLM Python paths, recover stale Ray state, and harden serving lifecycle behavior — #968
• Use per-session free ports for persistent server reuse — #971
• Refresh compatibility guidance and architecture documentation — #966, #969, #970, #1001

Security and policy

• Validate multi-node restart arguments and replay policy checks before task dispatch — #959

Reporting

• Attribute FRAMEWORK_AGENT and integrate_patch gains correctly — #975

CI and dependencies

• Add mandatory single-GPU PR smoke testing — #991
• Update GitHub Actions dependencies — #960, #961, #962, #963, #995
• Reduce internal complexity and remove dead paths — #965

Release

• Set the packaged version to 1.0.0a1 — #996
• Read the runtime version from package metadata — #1002

Requirements

ROCm platform with a supported AMD Instinct GPU; Docker with AMD ROCm support, Kubernetes with AMD GPU nodes, or the supported bare-metal setup; Cursor IDE with Remote SSH; an Anthropic API key or compatible Anthropic gateway; tmux, jq, Node.js >= 18, and Claude CLI.

Alpha notice

v1.0.0a1 is an alpha release. Configuration surfaces, orchestration policies, and installation workflows may continue to evolve before the final v1.0.0 release.