2 papers
cs.CL2025
A3 : an Analytical Low-Rank Approximation Framework for Attention
Jeffrey T. H. Wong, Cheng Zhang, Xinye Cao +5
Large language models have demonstrated remarkable performance; however, their massive parameter counts make deployment highly expensive. Low-rank approximation offers a promising…
cs.AR2024
Exploring FPGA designs for MX and beyond
Ebby Samson, Naveen Mellempudi, Wayne Luk +1
A number of companies recently worked together to release the new Open Compute Project MX standard for low-precision computation, aimed at efficient neural network implementation.…