Matlab Support for float32/single and float16/half datatypes in GPU Sparse Matrix Multiplication

Question

Anthony 2024-8-30

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https://ww2.mathworks.cn/matlabcentral/answers/2149204-matlab-support-for-float32-single-and-float16-half-datatypes-in-gpu-sparse-matrix-multiplication

回答： Joss Knight 2024-8-31

Is there a timeline for Matlab support for single (float32) and half (float16) datatypes for the non-zero values in GPU sparse matrices and for compatible float32/float16 gpu-accelerated sparse matrix multiplication?

This functionality exists in the underlying sparse CUDA libraries, and I believe it would be possible for users to compile their own MEX files to perform this task. However, considering the computational and memory efficiency that could be achieved by widening the functionality of sparse GPU matrices to float32/float16 non-zero values, I believe there exists a significant enough underlying demand for this functionality in Matlab to justify adding it in a future release. This is especially relevant when using very large GPU sparse matrices, which ultimately overwhelm the VRAM of most commercial GPUs.