“Matrix multiplication (MatMul) typically dominates the overall ... should be optimized for in processing the next generation of lightweight LLMs. Our code implementation is available at this https ...

This is a very efficient matrix multiplication calculator built using Java and its concurrency libraries. It can be used to multiply matrices populated using a random seed, but it can also be modified ...

Abstract: We present Modular Polynomial (MP) Codes for Secure Distributed Matrix Multiplication (SDMM). The construction is based on the observation that one can decode certain proper subsets of the ...

The computation of dense matrix-matrix products (GEMMs) is central to many modeling and simulation workloads as well as AI/ML deep learning campaigns. In fact, millions of dollars are spent annually ...

This has motivated the development of several algorithms that seek to speed up matrix-vector multiplication by distributing the computation across multiple computing nodes. The individual nodes (the ...

Abstract: A novel fault-tolerant computation technique based on array Belief Propagation (BP)-decodable XOR (BP-XOR) codes is proposed for distributed matrix-matrix multiplication. The proposed scheme ...

She is sceptical of the current AI efficiency hype, emphasizing that real value of generative AI tools lies in solving complex problems like legacy code comprehension rather than just writing code ...

the Intel MKL DGEMM function for matrix-matrix multiplication is highly tuned for small matrices. To eliminate overhead, Intel MKL provides a compiler flag to guarantee that the fastest code path is ...

The most widely used matrix-matrix multiplication routine is ... data into a packed format internally first and then perform the multiplication over smaller blocks using highly optimized code and ...