This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.

SpMV-CNN: A set of convolutional neural nets for estimating the run time and energy consumption of the sparse matrix-vector product ...

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 ...

Abstract: We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GPU. An efficient k-way merge lies at the heart of finding a fast parallel SpMSpV algorithm.

Memristor-enabled in-memory computing provides an unconventional computing paradigm to surpass the energy efficiency of von Neumann computers. However, owing to the physical limitation of the crossbar ...

This post is in response to The Emerging Revival of Psychedelics in Neuroscience By Cami Rosso In honor of the long-awaited release of fourth movie in the Matrix series, ‘The Matrix Resurrections,’ it ...

Graduate School of Chinese Academy of Engineering Physics, Beijing, China. Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing,China. School of ...