How Google’s TPUs are reshaping the economics of large-scale AI

TPUv7 offers a viable alternative to the GPU-centric AI stack has already arrived — one with real implications for the economics and architecture of frontier-scale training.
IEEE

Accelerating Look-Up Table based Matrix Multiplication on GPUs

Abstract: Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Approximated Matrix Multiplication (AMM) based on table look-ups can significantly ...
IEEE

tubGEMM: Energy-Efficient and Sparsity-Effective Temporal-Unary-Binary Based Matrix Multiply Unit

Abstract: General Matrix Multiplication (GEMM) is a ubiquitous compute kernel in deep learning (DL). To support energy-efficient edge-native processing, new GEMM hardware units have been proposed that ...