AIRamp-Accel is a system-wide acceleration layer that improves end-to-end throughput and latency for AI, HPC, and engineering/simulation workloads on AMD Instinct GPUs. It requires no source changes to applications.
The solution works by preloading a shared library that:
Optimizes host↔device memory paths with optional pinned‑host staging and a device memory pool for repeated temporary allocations.
Accelerates machine learning workload transfers via a conservative, portable chunking layer for large (Read|Write)Buffer calls
Gates activation by allowlist to avoid impacting non‑target executables.
Includes a daemon (airampd) that seeds a runtime cost‑model and a CLI (airampctl) for activation, diagnostics, and system hygiene (preload “doctor”).
The net effect is better scaling and steadier performance on multi‑GPU nodes (training, all‑reduce/all‑gather heavy codes), improved transfer efficiency