Setting Up HIP with CUDA
Some notes on setting up CUDA and HIP for a system with an NVIDIA GPU or with an AMD GPU.
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HPCG: 3. Sparse Matrix Formats and Memory Access Optimization
Understanding sparse matrix formats with simple python code. By using ELLPACK format for representing sparse matrices, we can optimize the memory access pattern of the HPCG benchmark.
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HPCG: 2. Multi-coloring for Parallelization
In the reference implementation of HPCG, SYMGS computation cannot be fully parallelized. However, we can use multi-coloring technique to parallelize the computation at the cost of relaxation of the algorithm.
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HPCG: 1. The Specification
HPCG is a benchmark like LINPACK but with a different focus. Conceptually, it emphasizes sparse linear algebra, and practically, it is aimed at optimizing memory access patterns, communication, and parallelization.