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Design Tradeoffs of SSDs: From Energy Consumption’s Perspective

Published:24 March 2015Publication History
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Abstract

In this work, we studied the energy consumption characteristics of various SSD design parameters. We developed an accurate energy consumption model for SSDs that computes aggregate, as well as component-specific, energy consumption of SSDs in sub-msec time scale. In our study, we used five different FTLs (page mapping, DFTL, block mapping, and two different hybrid mappings) and four different channel configurations (two, four, eight, and 16 channels) under seven different workloads (from large-scale enterprise systems to small-scale desktop applications) in a combinatorial manner. For each combination of the aforementioned parameters, we examined the energy consumption for individual hardware components of an SSD (microcontroller, DRAM, NAND flash, and host interface). The following are some of our findings. First, DFTL is the most energy-efficient address-mapping scheme among the five FTLs we tested due to its good write amplification and small DRAM footprint. Second, a significant fraction of energy is being consumed by idle flash chips waiting for the completion of NAND operations in the other channels. FTL should be designed to fully exploit the internal parallelism so that energy consumption by idle chips is minimized. Third, as a means to increase the internal parallelism, increasing way parallelism (the number of flash chips in a channel) is more effective than increasing channel parallelism in terms of peak energy consumption, performance, and hardware complexity. Fourth, in designing high-performance and energy-efficient SSDs, channel switching delay, way switching delay, and page write latency need to be incorporated in an integrated manner to determine the optimal configuration of internal parallelism.

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    • Published in

      cover image ACM Transactions on Storage
      ACM Transactions on Storage  Volume 11, Issue 2
      March 2015
      123 pages
      ISSN:1553-3077
      EISSN:1553-3093
      DOI:10.1145/2747982
      • Editor:
      • Darrell Long
      Issue’s Table of Contents

      Copyright © 2015 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 March 2015
      • Accepted: 1 July 2014
      • Revised: 1 April 2014
      • Received: 1 July 2013
      Published in tos Volume 11, Issue 2

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