Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation

Understand

We evaluate the use of the open-source Llama-2 model for generating well-known, high-performance computing kernels (e.g., AXPY, GEMV, GEMM) on different parallel programming models and languages (e.g., C++: OpenMP, OpenMP Offload, OpenACC, CUDA, HIP; Fortran: OpenMP, OpenMP Offload, OpenACC; Python: numpy, Numba, pyCUDA, cuPy; and Julia: Threads, CUDA.jl, AMDGPU.jl).

• We built upon our previous work that is based on the OpenAI Codex, which is a descendant of GPT-3, to generate similar kernels with simple prompts via GitHub Copilot.
• Our goal is to compare the accuracy of Llama-2 and our original GPT-3 baseline by using a similar metric.
• Llama-2 has a simplified model that shows competitive or even superior accuracy.