Abstract: Exploiting the numeric symmetry in sparse matrices to reduce their memory footprint is very tempting for optimizing the memory-bound Sparse Matrix-Vector Multiplication (SpMV) kernel.
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Tiny silicon structures compute with heat, achieving 99% accurate matrix multiplication
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...
Abstract: Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the ...
This project implements an 8x8 systolic array for high-performance matrix multiplication, leveraging a parallel processing architecture optimized for efficiency and scalability. The workflow spans RTL ...
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