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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 ...
Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.
Abstract: For many scientific applications, dense matrix multiplication is one of the most important and computation intensive linear algebra operations. An efficient matrix multiplication on high ...
This project is intended for research purposes only. Use it at your own risk and discretion. Triton is a language and compiler for writing highly efficient ML primitives, one of the most common ...
Abstract: Sparse General Matrix-Matrix Multiplication (SpGEMM) is a core operation in high-performance computing applications such as algebraic multigrid solvers, machine learning, and graph ...
This repository accompanies the research paper "Implications of Language Choice for Algorithmic Efficiency in Low-Power Computing." The study investigates how the choice of programming ...
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