Triple-A: a Non-SSD based autonomic all-flash array for high performance storage systems

  • Authors:

  • Myoungsoo Jung;Wonil Choi;John Shalf;Mahmut Taylan Kandemir

  • Affiliations:

  • The University of Texas at Dallas, Richardson, TX, USA;The University of Texas at Dallas, Richardson, TX, USA;Lawrence Berkeley National Laboratory, Berkeley, CA, USA;The Pennsylvania State University, State College, PA, USA

  • Venue:
  • Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
  • Year:
  • 2014

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Abstract

Solid State Disk (SSD) arrays are in a position to (as least partially) replace spinning disk arrays in high performance computing (HPC) systems due to their better performance and lower power consumption. However, these emerging SSD arrays are facing enormous challenges, which are not observed in disk-based arrays. Specifically, we observe that the performance of SSD arrays can significantly degrade due to various array-level resource contentions. In addition, their maintenance costs exponentially increase over time, which renders them difficult to deploy widely in HPC systems. To address these challenges, we propose Triple-A, a non-SSD based Autonomic All-Flash Array, which is a self-optimizing, from-scratch NAND flash cluster. Triple-A can detect two different types of resource contentions and autonomically alleviate them by reshaping the physical data-layout on its flash array network. Our experimental evaluation using both real workloads and a micro-benchmark show that Triple-A can offer a 53% higher sustained throughput and a 80% lower I/O latency than non-autonomic SSD arrays.