Affiliation:
1. Georgia Institute of Technology, Atlanta, GA
2. Intel Corporation, Santa Clara, CA
Abstract
Traditionally, architectural innovations designed to boost single-threaded performance incur overhead costs which significantly increase power consumption. In many cases the increase in power exceeds the improvement in performance, resulting in a net increase in energy consumption. Thus, it is reasonable to assume that modern attempts to improve singlethreaded performance will have a negative impact on energy efficiency. This has led to the belief that "Big Cores" are inherently inefficient. To the contrary, we present a study which finds that the increased complexity of the core microarchitecture in recent generations of the IntelR Core™ processor have reduced both the time and energy required to run various workloads. Moreover, taking out the impact of process technology changes, our study still finds the architecture and microarchitecture changes ---such as the increase in SIMD width, addition of the frontend caches, and the enhancement to the out-of-order execution engine--- account for 1.2x improvement in energy efficiency for these processors. This paper provides real-world examples of how architectural innovations can mitigate inefficiencies associated with "Big Cores" ---for example, micro-op caches obviate the costly decode of complex x86 instructions--- resulting in a core architecture that is both high performance and energy efficient. It also contributes to the understanding of how microarchitecture affects performance, power and energy efficiency by modeling the relationship between them
Funder
Defense Advanced Research Projects Agency
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Cited by
5 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. Coarse-Grained Reconfigurable Architectures;The Frontiers Collection;2020
2. Power-Constrained Optimal Quality for High Performance Servers;Proceedings of the 47th International Conference on Parallel Processing Companion;2018-08-13
3. Effect of frequency scaling granularity on energy-saving strategies;The International Journal of High Performance Computing Applications;2018-05-15
4. An Incremental Methodology for Energy Measurement and Modeling;Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering;2017-04-17
5. Single-Instruction Multiple-Data Execution;Synthesis Lectures on Computer Architecture;2015-05-27