A custom RISC-V vector instruction to accelerate structured-sparse matrix multiplications

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a predefined pattern of zero values in the matrix, unlike unstructured sparsity where zeros can occur anywhere. The research was conducted by Democritus University of Thrace (DUTH) in Greece and was sponsored by Codasip University Program.

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