  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.
