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Title: A Compute Capable SSD Architecture for Next-Generation Non-volatile Memories

Abstract

Existing storage technologies (e.g., disks and ash) are failing to cope with the processor and main memory speed and are limiting the overall perfor- mance of many large scale I/O or data-intensive applications. Emerging fast byte-addressable non-volatile memory (NVM) technologies, such as phase-change memory (PCM), spin-transfer torque memory (STTM) and memristor are very promising and are approaching DRAM-like performance with lower power con- sumption and higher density as process technology scales. These new memories are narrowing down the performance gap between the storage and the main mem- ory and are putting forward challenging problems on existing SSD architecture, I/O interface (e.g, SATA, PCIe) and software. This dissertation addresses those challenges and presents a novel SSD architecture called XSSD. XSSD o oads com- putation in storage to exploit fast NVMs and reduce the redundant data tra c across the I/O bus. XSSD o ers a exible RPC-based programming framework that developers can use for application development on SSD without dealing with the complication of the underlying architecture and communication management. We have built a prototype of XSSD on the BEE3 FPGA prototyping system. We implement various data-intensive applications and achieve speedup and energy ef- ciency of 1.5-8.9 and 1.7-10.27 respectively. Thismore » dissertation also compares XSSD with previous work on intelligent storage and intelligent memory. The existing ecosystem and these new enabling technologies make this system more viable than earlier ones.« less

Authors:
 [1]
  1. Univ. of California, San Diego, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1136169
Report Number(s):
LLNL-TH-655198
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Thesis/Dissertation
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

De, Arup. A Compute Capable SSD Architecture for Next-Generation Non-volatile Memories. United States: N. p., 2014. Web. doi:10.2172/1136169.
De, Arup. A Compute Capable SSD Architecture for Next-Generation Non-volatile Memories. United States. doi:10.2172/1136169.
De, Arup. Wed . "A Compute Capable SSD Architecture for Next-Generation Non-volatile Memories". United States. doi:10.2172/1136169. https://www.osti.gov/servlets/purl/1136169.
@article{osti_1136169,
title = {A Compute Capable SSD Architecture for Next-Generation Non-volatile Memories},
author = {De, Arup},
abstractNote = {Existing storage technologies (e.g., disks and ash) are failing to cope with the processor and main memory speed and are limiting the overall perfor- mance of many large scale I/O or data-intensive applications. Emerging fast byte-addressable non-volatile memory (NVM) technologies, such as phase-change memory (PCM), spin-transfer torque memory (STTM) and memristor are very promising and are approaching DRAM-like performance with lower power con- sumption and higher density as process technology scales. These new memories are narrowing down the performance gap between the storage and the main mem- ory and are putting forward challenging problems on existing SSD architecture, I/O interface (e.g, SATA, PCIe) and software. This dissertation addresses those challenges and presents a novel SSD architecture called XSSD. XSSD o oads com- putation in storage to exploit fast NVMs and reduce the redundant data tra c across the I/O bus. XSSD o ers a exible RPC-based programming framework that developers can use for application development on SSD without dealing with the complication of the underlying architecture and communication management. We have built a prototype of XSSD on the BEE3 FPGA prototyping system. We implement various data-intensive applications and achieve speedup and energy ef- ciency of 1.5-8.9 and 1.7-10.27 respectively. This dissertation also compares XSSD with previous work on intelligent storage and intelligent memory. The existing ecosystem and these new enabling technologies make this system more viable than earlier ones.},
doi = {10.2172/1136169},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2014},
month = {1}
}

Thesis/Dissertation:
Other availability
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