An FPGA-based Platform for Non Volatile Memory Emulation

被引：0

作者：

Lee, Taemin ^{[1
]}

Yoo, Sungjoo ^{[1
]}

机构：

[1] Seoul Natl Univ, Dept Comp Sci & Engn, Seoul, South Korea

来源：

2017 IEEE 6TH NON-VOLATILE MEMORY SYSTEMS AND APPLICATIONS SYMPOSIUM (NVMSA 2017) | 2017年

关键词：

NVM; FPGA Emulation; machine learning;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Non volatile memory (NVM) is expected to enrich the next generation computer system. However, designers have difficulties in exploring new software and hardware design ideas based on NVM due to the limitations of current simulation-based evaluation, e.g., slow runtime. In order to resolve this problem, we present an open, reliable, and versatile hardware platform for NVM emulation. We built Zynq FPGA-based boards where software programs can run on the emulated NVM having parameterized read/ write latency and non-volatility. They also support Linux-compatible OSs, Debian, Petalinux, and Ubuntu GUI. We report a case study where machine learning algorithms are evaluated while varying memory latency on the hardware platform.

引用

页数：4

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