Electrical static random memory (E-SRAM) is the current standard for internal static memory in Field Programmable Gate Array (FPGA). Despite the dramatic improvement in E-SRAM technology over the past decade, the goal of ultra-fast, energy-efficient static random memory has yet to be achieved with E-SRAM technology. However, preliminary research into optical static random access memory (O-SRAM) has shown promising results in creating energy-efficient ultra-fast static memories. This paper investigates the advantage of O-SRAM over E-SRAM in access speed and energy performance while executing sparse Matricized Tensor Times Khatri-Rao Product (spMTTKRP). spMTTKRP is an essential component of tensor decomposition algorithms which is heavily used in data science applications. The evaluation results show O-SRAMs can achieve speeds of 1.1x - 2.9x while saving 2.8x - 8.1x energy compared to conventional E-SRAM technology.
@article{arxiv.2208.10593,
title = {Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGA},
author = {Sasindu Wijeratne and Akhilesh Jaiswal and Ajey P. Jacob and Bingyi Zhang and Viktor Prasanna},
journal= {arXiv preprint arXiv:2208.10593},
year = {2022}
}