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E-raamat: Energy-Efficient High Performance Computing: Measurement and Tuning

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In this work, the unique power measurement capabilities of the Cray XT architecture were exploited to gain an understanding of power and energy use, and the effects of tuning both CPU and network bandwidth. Modifications were made to deterministically halt cores when idle. Additionally, capabilities were added to alter operating P-state. At the application level, an understanding of the power requirements of a range of important DOE/NNSA production scientific computing applications running at large scale is gained by simultaneously collecting current and voltage measurements on the hosting nodes. The effects of both CPU and network bandwidth tuning are examined, and energy savings opportunities without impact on run-time performance are demonstrated. This research suggests that next-generation large-scale platforms should not only approach CPU frequency scaling differently, but could also benefit from the capability to tune other platform components to achieve more energy-efficient performance.
1 Introduction
1(4)
1.1 Motivation
1(2)
1.2 Overview
3(2)
References
4(1)
2 Platforms
5(6)
2.1 Hardware Architecture
5(2)
2.1.1 Red Storm
6(1)
2.1.2 Jaguar
6(1)
2.2 Operating System
7(1)
2.3 Reliability Availability and Serviceability System
8(3)
References
9(2)
3 Measuring Power
11(6)
3.1 Leveraging the Hardware
11(2)
3.2 Software Instrumentation
13(2)
3.3 Post Processing Measurement Data
15(2)
4 Applications
17(4)
4.1 High Performance Computing Applications
17(1)
4.2 Synthetic Benchmarks
18(3)
References
19(2)
5 Reducing Power During Idle Cycles
21(10)
5.1 Operating System Modifications
21(1)
5.2 Results and Analysis
22(9)
5.2.1 Idle Power: Before and After
22(4)
5.2.2 Application Power Signature
26(1)
5.2.3 Power and Noise
26(4)
References
30(1)
6 Tuning CPU Power During Application Runtime
31(12)
6.1 Static CPU Frequency Tuning
31(5)
6.1.1 Operating System Modifications
32(3)
6.1.2 Library Interface
35(1)
6.2 Results and Analysis: CPU Frequency Tuning
36(7)
References
42(1)
7 Network Bandwidth Tuning During Application Runtime
43(8)
7.1 Enabling Bandwidth Tuning
43(3)
7.2 Results and Analysis: Network Bandwidth Tuning
46(5)
References
49(2)
8 Energy Delay Product
51(6)
8.1 A Fused Metric
51(6)
References
55(2)
9 Conclusions
57(4)
References
59(2)
References 61(4)
Index 65