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 ...

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 ...

You can stop looking for glitches in the Matrix—it’s finally been proven that our universe is not merely a simulation running on some powerful alien civilization’s supercomputer. An international team ...

Researchers at DeepSeek on Monday released a new experimental model called V3.2-exp, designed to have dramatically lower inference costs when used in long-context operations. DeepSeek announced the ...

You can now order an “Iron Dome” for mosquitoes. Its name is the Photon Matrix, a black box about the size of a smartphone that can detect, track, and eliminate mosquitoes mid-flight using an ...

Abstract: Distributed computations, such as distributed matrix multiplication, can be vulnerable to significant security issues, notably Byzantine attacks. These attacks may target either worker nodes ...

Hand-tuned WebAssembly implementations for efficient execution of web-based sparse computations including Sparse Matrix-Vector Multiplication (SpMV), sparse triangular solve (SpTS) and other useful ...

An international criminal communications network, known as the Matrix, containing more than 2 million encrypted messages in 33 languages and spanning 40 servers, has been broken apart by a ...