@inproceedings{6fac72462e034959863f798210a38206,
title = "Exploiting free silicon for energy-efficient computing directly in NAND flash-based solid-state storage systems",
abstract = "Energy consumption is a fundamental issue in today's data centers as data continue growing dramatically. How to process these data in an energy-efficient way becomes more and more important. Prior work had proposed several methods to build an energy-efficient system. The basic idea is to attack the memory wall issue (i.e., the performance gap between CPUs and main memory) by moving computing closer to the data. However, these methods have not been widely adopted due to high cost and limited performance improvements. In this paper, we propose the storage processing unit (SPU) which adds computing power into NAND flash memories at standard solid-state drive (SSD) cost. By pre-processing the data using the SPU, the data that needs to be transferred to host CPUs for further processing are significantly reduced. Simulation results show that the SPU-based system can result in at least 100 times lower energy per operation than a conventional system for data-intensive applications.",
keywords = "NAND Flash, OpenCL, Parallel computing, SSD",
author = "Peng Li and Kevin Gomez and Lilja, {David J.}",
note = "Copyright: Copyright 2014 Elsevier B.V., All rights reserved.; 2013 IEEE High Performance Extreme Computing Conference, HPEC 2013 ; Conference date: 10-09-2013 Through 12-09-2013",
year = "2013",
doi = "10.1109/HPEC.2013.6670317",
language = "English (US)",
isbn = "9781479913657",
series = "2013 IEEE High Performance Extreme Computing Conference, HPEC 2013",
publisher = "IEEE Computer Society",
booktitle = "2013 IEEE High Performance Extreme Computing Conference, HPEC 2013",
}