AMD has demonstrated a significant performance improvement in optimizing a double-precision HIP kernel on an AMD Instinct™ MI250 Graphics Compute Die (GCD) using an AI code-assist tool. The workflow, which integrated the tool into the profiling process, resulted in a cumulative 28.3× speedup across 45 experiments while maintaining bit-identical results. The entire optimization process took approximately four working days, compared to weeks or months in a traditional manual workflow. The study highlights how structured AI-assisted workflows can compress the cycle of profiling, hypothesis formation, code edits, and validation, while maintaining developer control over correctness and measurement.
The optimization focused on a stiff ordinary-differential-equation (ODE) solver with a sparse update graph. The kernel, which integrates a system of coupled rate equations, was designed to run on 104 zones mapped to the 104 compute units (CUs) on the MI250 GCD. Each zone required thousands of time steps, with per-timestep operations involving coupling rates, state updates, and shared memory usage. The AI-assist tool, Cursor, was used in agent mode to automate tasks such as sbatch submissions, profiling, and numerical diffs against a reference output at a 1e-12 relative tolerance. The tool also maintained a shared log file to track experiment plans, results, and revert decisions, replacing the developer’s memory of prior steps.
The study emphasizes the broader implications of integrating AI code-assist tools into GPU optimization workflows. It outlines a practical template for developers already familiar with HIP and ROCm profiling tools, showing how AI can streamline the optimization process without compromising correctness. The workflow is designed to generalize across different kernels, projects, and GPU architectures, as long as the device supports the necessary instruction set architecture (ISA). The results underscore the potential of AI-assisted profiling to significantly reduce development time in high-performance computing (HPC) applications.
Source: amd
