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Chapter 6 Warehouse-Scale Computers to Exploit Request-Level and Data-Level Parallelism Topic 13 Using Energy Efficiently Inside the Server Prof. Zhang.

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Presentation on theme: "Chapter 6 Warehouse-Scale Computers to Exploit Request-Level and Data-Level Parallelism Topic 13 Using Energy Efficiently Inside the Server Prof. Zhang."— Presentation transcript:

1 Chapter 6 Warehouse-Scale Computers to Exploit Request-Level and Data-Level Parallelism Topic 13 Using Energy Efficiently Inside the Server Prof. Zhang Gang School of Computer Sci. & Tech. Tianjin University, Tianjin, P. R. China

2 Using Energy Efficiently Inside the Server
To improve the state of the art, Figure shows the Climate Savers Computing Initiative standards [2007] for rating power supplies and their goals over time. Note that the standard specifies requirements at 20% and 50% loading in addition to 100% loading. Figure 6.17 Efficiency ratings and goals for power supplies over time of the Climate Savers Computing Initiative. These ratings are for Multi-Output Power Supply Units, which refer to desktop and server power supplies in nonredundant systems. There is a slightly higher standard for single-output PSUs, which are typically used in redundant configurations (1U/2U single-, dual-, and four-socket and blade servers).

3 Using Energy Efficiently Inside the Server
In addition to the power supply, Barroso and Holzle [2007] said the goal for the whole server should be energy proportionality; that is, servers should consume energy in proportion to the amount of work performed. Figure 6.18 shows how far we are from achieving that ideal goal using SPECpower, a server benchmark that measures energy used at different performance levels

4 Using Energy Efficiently Inside the Server
Figure 6.18 The best SPECpower results as of July 2010 versus the ideal energy proportional behavior. The system was the HP ProLiant SL2x170z G6, which uses a cluster of four dual-socket Intel Xeon L5640s with each socket having six cores running at 2.27 GHz. The system had 64 GB of DRAM and a tiny 60 GB SSD for secondary storage. The software used was IBM Java Virtual Machine version 9 and Windows Server 2008, Enterprise Edition.


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