A team of researchers developed “parallel optical matrix-matrix multiplication” (POMMM), which could revolutionize tensor ...
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MIT’s new heat-powered silicon chips achieve 99% accuracy in math calculations
Scientists in the US have created a tiny silicon chip that can perform mathematical ...
At a recent Bengaluru mixer hosted by E2E Networks, NVIDIA, and YourStory, founders and ecosystem builders unpacked the real ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Researchers at Massachusetts Institute of Technology have demonstrated a surprising new way to compute—by using heat instead ...
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 ...
Abstract: Matrix multiplication is a fundamental computational operation widely used in various engineering applications. To accelerate large-scale matrix multiplication, computing tasks are commonly ...
This repository contains the artifact for the SC '25 paper submission "KAMI: Communication-Avoiding General Matrix Multiplication within a Single GPU." The NVIDIA GH200 is installed with Ubuntu 22.04 ...
Implementations are for learning purposes only. They may be less efficient than the implementations in the Python standard library. Use them at your discretion.
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