Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGA

TL;DR

This paper explores the use of optical static RAM (O-SRAM) on FPGA to improve speed and energy efficiency in executing sparse MTTKRP, a key tensor operation in data science.

Contribution

It demonstrates that O-SRAM can significantly outperform E-SRAM in speed and energy consumption for spMTTKRP on FPGA.

Findings

O-SRAM achieves 1.1x - 2.9x faster speeds

O-SRAM reduces energy consumption by 2.8x - 8.1x

Optical memory offers promising advantages over traditional SRAM

Abstract

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.