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 ...
If \(A\) is a \(3\times 3\) matrix then we can apply a linear transformation to each rgb vector via matrix multiplication, where \([r,g,b]\) are the original values ...
A new technical paper titled “Experimental Assessment of Multilevel RRAM-Based Vector-Matrix Multiplication Operations for In-Memory Computing” was published by researchers at IHP (the Leibniz ...
A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements. For computer ...
A technical paper titled “A large-scale integrated vector-matrix multiplication processor based on monolayer molybdenum disulfide memories” was published by researchers at École Polytechnique Fédérale ...
Photonics is promising to handle extensive vector multiplications in AI applications. Scientists in China have promoted a programmable and reconfigurable photonic linear vector machine named SUANPAN, ...
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