Active disks

Author:

Acharya Anurag1,Uysal Mustafa2,Saltz Joel2

Affiliation:

1. Dept. of Computer Science, University of California, Santa Barbara

2. Dept. of Computer Science, University of Maryland, College Park

Abstract

Several application and technology trends indicate that it might be both profitable and feasible to move computation closer to the data that it processes. In this paper, we evaluate Active Disk architectures which integrate significant processing power and memory into a disk drive and allow application-specific code to be downloaded and executed on the data that is being read from (written to) disk. The key idea is to offload bulk of the processing to the diskresident processors and to use the host processor primarily for coordination, scheduling and combination of results from individual disks. To program Active Disks, we propose a stream-based programming model which allows disklets to be executed efficiently and safely. Simulation results for a suite of six algorithms from three application domains (commercial data warehouses, image processing and satellite data processing) indicate that for these algorithms, Active Disks outperform conventional-disk architectures.

Publisher

Association for Computing Machinery (ACM)

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. TH-iSSD: Design and Implementation of a Generic and Reconfigurable Near-Data Processing Framework;ACM Transactions on Embedded Computing Systems;2023-11-09

2. KV-CSD: A Hardware-Accelerated Key-Value Store for Data-Intensive Applications;2023 IEEE International Conference on Cluster Computing (CLUSTER);2023-10-31

3. NASCENT2: Generic Near-Storage Sort Accelerator for Data Analytics on SmartSSD;ACM Transactions on Reconfigurable Technology and Systems;2022-01-28

4. NDS: N-Dimensional Storage;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17

5. In-/Near-Memory Computing;Synthesis Lectures on Computer Architecture;2021-08-11

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