NDLI: Execution Drafting: Energy Efficiency Through Computation Deduplication

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Execution Drafting: Energy Efficiency Through Computation Deduplication

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Execution Drafting: Energy Efficiency Through Computation Deduplication

Content Provider	ACM Digital Library
Author	Wentzlaff, David Balkind, Jonathan Mckeown, Michael
Abstract	Computation is increasingly moving to the data enter. Thus, the energy used by CPUs in the data centeris gaining importance. The centralization of computation in the data center has also led to much commonality between the applications running there. For example, there are many instances of similar or identical versions of the Apache web server running in a large data center. Many of these applications, such as bulk image resizing or video Transco ding, favor increasing throughput over single stream performance. In this work, we propose Execution Drafting, an architectural technique for executing identical instructions from different programs or threads on the same multithreaded core, such that they flow down the pipe consecutively, or draft. Drafting reduces switching and removes the need to fetch and decode drafted instructions, thereby saving energy. Drafting can also reduce the energy of the execution and commit stages of a pipeline when drafted instructions have similar operands, such as when loading constants. We demonstrate Execution Drafting saving energy when executing the same application with different data, as well as different programs operating on different data, as is the case for different versions of the same program. We evaluate hardware techniques to identify when to draft and analyze the hardware overheads of Execution Drafting implemented in an Open SPARC T1 core. We show that Execution Drafting can result in substantial performance per energy gains (up to 20%) in a data center without decreasing throughput or dramatically increasing latency.
Starting Page	432
Ending Page	444
Page Count	13
File Format	PDF
ISBN	9781479969982
ISSN	10724451
DOI	10.1109/MICRO.2014.43
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-12-13
Access Restriction	Subscribed
Subject Keyword	Cloud computing Microarchitecture Multithreading Energy efficiency Energy efficient computing Computation deduplication Data center computing
Content Type	Text
Resource Type	Article

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