Matrix-vector multiplication (MVM) is a computational bottleneck for transformer inference workloads at resource-restricted edge applications. Efficient MVM accelerator design is crucial to optimizing ...
Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...
the Register Transfer Level (RTL) implementation of a Bit-Serial Matrix-Vector Multiplication Unit, inspired by the Stripes Accelerator architecture. This project was developed as the Second ...
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