Within the next two years, 80% of AI compute is projected to be devoted to inference and just 20% to training.

An improved variant of the precise-integration time-domain (PITD) method is proposed to eliminate the inverse matrix calculation and optimize the storage burden with the help of sparse computation.

The effect of tapering is to create a sparse approximate linear system that can then be solved using sparse matrix algorithms. Monte Carlo simulations support the theoretical results. An application ...

Recent commercial incarnations of processing-in-memory (PIM) maintain the standard DRAM interface and employ the all-bank mode execution to maximize bank-level memory bandwidth. Such a synchronized ...