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ROCm AMD Infinity Context

MIT Platform ROCm vLLM LMCache NIXL hsa-snoop Spelling Lint Export Tarball Nightly Dist Build Nightly Smoke Test Nightly Tiny Test Nightly Cliff Nightly Wheels Nightly Patch Validation Monitoring CPU Smoke Metrics Reference Cliff Perf Dashboard

Caution

This release is an early-access software technology preview. Running production workloads is not recommended.

ROCm(tm) AMD Infinity Context (AIC) is a disaggregated KV-cache inference stack for large language models on AMD Instinct GPUs. It combines an LLM serving framework with a KV Cache block manager to offload KV tensors across a tiered memory hierarchy. GPU VRAM, CPU DRAM, local NVMe and NFS-over-RDMA.

It focuses on enabling a low-latency, shared level of KV Cache that can be accessed by O(1000) GPUs.

ROCm AIC enables long-context serving at scale without recomputation. This repository provides a Docker image build and test harness, benchmarking harness, and Slurm/Spur automation used to validate and demonstrate the platform.

Stack Overview

Component Source Ref
Base OS rocm/dev-ubuntu-24.04:7.14.0-full Ubuntu 24.04, ROCm 7.14, Python 3.12
vLLM github.com/vllm-project/vllm (source build) v0.27.1 + 2 AMD patches
LMCache LMCache/LMCache (upstream) v0.5.4 + 14 AMD patches
NIXL ai-dynamo/nixl (upstream) v1.3.2 + nixl-rocm-ais-mt.patch
hsa-snoop sbates130272/hsa-snoop (source build) v1.0.0
hipFile ROCm 7.14 base image GA in ROCm 7.14 — no separate source build

Pip Nightly Wheels

See docs/PIP_WHEELS.md for installation instructions and compatibility notes. Wheels are rebuilt nightly from main and published to the nightly release.

Prerequisites

  • ROCm-capable host. Pass ROCM_ARCH as a ;-separated list (e.g. gfx90a;gfx942;gfx950) to build a multi-arch image, or a single arch (e.g. ROCM_ARCH=gfx942) for a faster build. The vLLM source build compiles GPU kernels for exactly the archs specified.
  • Docker with BuildKit and the docker compose (v2) plugin (Docker 23+). On a node that lacks it, make ensure-compose installs the plugin user-locally (~/.docker/cli-plugins); the Slurm cliff / smoke / tiny-test jobs self-install it automatically.
  • Host mounts: local NVMe (NVME_DATA) and NFS-over-RDMA (NFS_DATA) pre-mounted
  • HuggingFace token with access to the target model
  • Python 3.10+ for host-side benchmarks

Quick Start

See docs/QUICK_START.md for the full step-by-step guide (build, start, benchmark, plot). For Slurm / SPUR cluster usage see docs/SLURM_SPUR.md.

Metrics & Observability

See docs/METRICS_TELEMETRY.md for the full Prometheus scrape config, exporter details, NIXL telemetry, hsa-snoop, and NFS caveats.

Key Environment Variables

See docs/ENVIRONMENT.md for the full reference.

License

MIT

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ROCm AMD Infinity Context - a distributed, shared, low-latency KV Cache tier for AI Infernence.

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