How to Port a CPU Conjugate Gradient Solver to CUDA: A Step-by-Step Guide

A developer has published a detailed walkthrough on migrating HPCCG, a Conjugate Gradient mini-application from the Mantevo project, from CPU to GPU using CUDA. Rather than a full rewrite, the approach is incremental: profiling the CPU code first, then moving the most expensive operations to the GPU one at a time. On a one-million-row test problem, sparse matrix-vector multiplication (SpMV) consumed over 83% of total CPU runtime, making it the clear first target for GPU offloading. The tutorial also ports the same code to Kokkos, enabling a direct comparison between hand-written CUDA and a performance-portable programming model. All intermediate code and commits are publicly available on GitHub, allowing readers to reproduce each porting stage independently.