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ROCm Hyperloom

Tests Lint Version License: MIT Python

ROCm™ Hyperloom is an autonomous agentic system designed to optimize end-to-end inference workloads (targeting both host code and GPU kernels) on AMD GPUs. Using advanced AI agents and profiling tools, Hyperloom analyzes your workload, identifies performance bottlenecks, implements targeted optimizations, and validates the performance and correctness of the optimizations without requiring manual intervention.

The system operates through a sophisticated multi-stage pipeline. First TraceLens, the profiling brain of the workload understanding stage, consumes traces collected by Magpie (which in turn relies on IntelliKit for some low-level GPU profiling tools), captures bottlenecks, and derives the roofline targets that seed the optimization search tree.

Next, Hyperloom employs a self-evolving code optimization engine following an iterative agentic loop (Think → Decide → Implement → Benchmark). Arbor intelligently explores the optimization space using a Dynamic Specialist Agent and Knowledge Base. In parallel to Arbor, GEAK, a multi-agent GPU performance optimizer, optimizes hot kernels. Once optimizations are identified and validated, Hyperloom prepares the optimized code and generates a report with all proposed changes and expected performance improvements. This end-to-end automation enables developers to achieve significant performance improvements while maintaining code quality and reducing the manual effort traditionally required for GPU optimization.

Hyperloom architecture

Hyperloom combines:

  • Trace analysis, identifying bottleneck kernels and bridge planning through TraceLens Agent (backend support from Magpie and IntelliKit)
  • Kernel optimization through the GEAK backend.
  • Agentic search space exploration through Arbor, a tree-based cognition layer with dynamic agents, long-horizon campaigns, and self-evolving optimization guided by a curated knowledge base of hardware learnings, pitfalls, and prior campaign artifacts.

Supported Features

Feature Options
Workload Inference serving
Platform MI300X, MI325X, MI355X
Framework SGLang, vLLM
Kernel Language HIP, Triton, FlyDSL
LLM Backend Claude

Get Started

Goal Guide
Set up Hyperloom and run a demo Quickstart
Launch and monitor an optimization Run an optimization
Understand the algorithm Optimization loop

Documentation

Topic Link
ROCm Docs Hyperloom
Authentication and credentials Authentication & credentials
Environment variables Environment variables
Components Components
Compatibility Compatibility matrix
Troubleshooting Troubleshooting
Operations Operations & self-hosting
Session output schema session_breakdown.json

File Issues and Feedback

If you encounter any problem or bugs while running Hyperloom, feel free to open an issue, or provide us with feedback on how to improve Hyperloom by completing the beta survey.


Developer Entry Points

  • Runtime package: src/hyperloom/
  • Main agent instructions: src/hyperloom/inference_optimizer/SKILL.md
  • CLI entry point: python -m hyperloom.inference_optimizer.cli optimize
  • Operator tools: python -m hyperloom.inference_optimizer.tools.*
  • Platform tuning audit: python3 scripts/platform_audit.py — checks the host CPU tuning that silently changes benchmark results. Judges Core Performance Boost and the cpufreq governor against AMD's BIOS & Workload Tuning Guide for EPYC 9004; records determinism, SMT and NPS without a verdict, because chapter 5 varies those by workload or the OS layer can only infer them. Reads /sys, /proc and — as root — the HWCR MSR; no credentials, nothing written. Exit 0 on target, 1 a knob is wrong, 2 unresolved, which CI should treat as missing coverage rather than as a failure. The BIOS-only knobs are not reachable this way; see below.
  • BIOS audit over the BMC: sudo python3 scripts/platform_audit_bmc.py --bmc-user <ro> — covers the three knobs the OS cannot see (High Performance profile, APBDIS, DF C-states), targeted per 58011 §4.2.1, §4.4.3 and §4.4.4. Without --bmc-user it refuses to run unless --allow-account-creation is passed, because that path mints a temporary ADMINISTRATOR account on the BMC; exit 3 means such an account was left enabled or could not be confirmed revoked, and should page someone. The script's docstring has the account lifecycle and the rest of the exit codes.
  • Documentation source: docs/

For contribution workflow, testing, and linting, see CONTRIBUTING.md.


Licensing

Hyperloom is released under the MIT License. The full license text is in LICENSE.

You may use Hyperloom commercially, modify it, and distribute it under the terms of the MIT license, provided the copyright notice and the permission notice are retained in all copies or substantial portions of the software.

Third-party tools and agents (Cursor, Visual Studio, and Claude Code) that Hyperloom invokes are governed by their own separate license terms and are NOT covered by the MIT license above — see the "Third-Party Tools and Agents" section in LICENSE. You are responsible for reviewing and complying with each tool's individual license.

For security-relevant issues, see SECURITY.md. For contribution conventions, see CONTRIBUTING.md.

Release files for hyperloom-inference-optimizer 1.0.0

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