PRE-BUD

Author:

Manzanares Adam1,Qin Xiao1,Ruan Xiaojun1,Yin Shu1

Affiliation:

1. Auburn University, Auburn, AL

Abstract

A critical problem with parallel I/O systems is the fact that disks consume a significant amount of energy. To design economically attractive and environmentally friendly parallel I/O systems, we propose an energy-aware prefetching strategy (PRE-BUD) for parallel I/O systems with disk buffers. We introduce a new architecture that provides significant energy savings for parallel I/O systems using buffer disks while maintaining high performance. There are two buffer disk configurations: (1) adding an extra buffer disk to accommodate prefetched data, and (2) utilizing an existing disk as the buffer disk. PRE-BUD is not only able to reduce the number of power-state transitions, but also to increase the length and number of standby periods. As such, PRE-BUD conserves energy by keeping data disks in the standby state for increased periods of time. Compared with the first prefetching configuration, the second configuration lowers the capacity of the parallel disk system. However, the second configuration is more cost-effective and energy-efficient than the first one. Finally, we quantitatively compare PRE-BUD with both disk configurations against three existing strategies. Empirical results show that PRE-BUD is able to reduce energy dissipation in parallel disk systems by up to 50 percent when compared against a non-energy aware approach. Similarly, our strategy is capable of conserving up to 30 percent energy when compared to the dynamic power management technique.

Funder

Division of Computer and Network Systems

Division of Computing and Communication Foundations

Division of Undergraduate Education

Office of Cyberinfrastructure

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture

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1. Towards Energy-Efficient and Thermal-Aware Data Placement for Storage Clusters;IEEE Transactions on Sustainable Computing;2024-07

2. TADRP: Toward Thermal-Aware Data Replica Placement in Data-Intensive Data Centers;IEEE Transactions on Network and Service Management;2023-12

3. Energy-Efficient Thermal-Aware Data Placement Strategy for Storage Clusters;2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys);2022-12

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