G. Papadimitriou, Athanasios Chatzidimitriou, D. Gizopoulos
{"title":"多核cpu上能量与性能平衡的自适应电压/频率缩放和核心分配","authors":"G. Papadimitriou, Athanasios Chatzidimitriou, D. Gizopoulos","doi":"10.1109/HPCA.2019.00033","DOIUrl":null,"url":null,"abstract":"Energy efficiency is a known major concern for computing system designers. Significant effort is devoted to power optimization of modern systems, especially in largescale installations such as data centers, in which both high performance and energy efficiency are important. Power optimization can be achieved through different approaches, several of which focus on adaptive voltage regulation. In this paper, we present a comprehensive exploration of how two server-grade systems behave in different frequency and core allocation configurations beyond nominal voltage operation. Our analysis, which is built on top of two state-of-the-art ARMv8 microprocessor chips (Applied Micro’s X-Gene 2 and X-Gene 3) aims (1) to identify the best performance per watt operation points when the servers are operating in various voltage/frequency combinations, (2) to reveal how and why the different core allocation options on the available cores of the microprocessor affect the energy consumption, and (3) to enhance the default Linux scheduler to take task allocation decisions for balanced performance and energy efficiency. Our findings, on actual servers’ hardware, have been integrated into a lightweight online monitoring daemon which decides the optimal combination of voltage, core allocation, and clock frequency to achieve higher energy efficiency. Our approach reduces on average the energy by 25.2% on X-Gene 2, and 22.3% on X-Gene 3, with a minimal performance penalty of 3.2% on X-Gene 2 and 2.5% on X-Gene 3, compared to the default system configuration. Keywords-Energy efficiency; voltage and frequency scaling; power consumption; multicore characterization; micro-servers;","PeriodicalId":102050,"journal":{"name":"2019 IEEE International Symposium on High Performance Computer Architecture (HPCA)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Adaptive Voltage/Frequency Scaling and Core Allocation for Balanced Energy and Performance on Multicore CPUs\",\"authors\":\"G. Papadimitriou, Athanasios Chatzidimitriou, D. Gizopoulos\",\"doi\":\"10.1109/HPCA.2019.00033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Energy efficiency is a known major concern for computing system designers. Significant effort is devoted to power optimization of modern systems, especially in largescale installations such as data centers, in which both high performance and energy efficiency are important. Power optimization can be achieved through different approaches, several of which focus on adaptive voltage regulation. In this paper, we present a comprehensive exploration of how two server-grade systems behave in different frequency and core allocation configurations beyond nominal voltage operation. Our analysis, which is built on top of two state-of-the-art ARMv8 microprocessor chips (Applied Micro’s X-Gene 2 and X-Gene 3) aims (1) to identify the best performance per watt operation points when the servers are operating in various voltage/frequency combinations, (2) to reveal how and why the different core allocation options on the available cores of the microprocessor affect the energy consumption, and (3) to enhance the default Linux scheduler to take task allocation decisions for balanced performance and energy efficiency. Our findings, on actual servers’ hardware, have been integrated into a lightweight online monitoring daemon which decides the optimal combination of voltage, core allocation, and clock frequency to achieve higher energy efficiency. Our approach reduces on average the energy by 25.2% on X-Gene 2, and 22.3% on X-Gene 3, with a minimal performance penalty of 3.2% on X-Gene 2 and 2.5% on X-Gene 3, compared to the default system configuration. 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Adaptive Voltage/Frequency Scaling and Core Allocation for Balanced Energy and Performance on Multicore CPUs
Energy efficiency is a known major concern for computing system designers. Significant effort is devoted to power optimization of modern systems, especially in largescale installations such as data centers, in which both high performance and energy efficiency are important. Power optimization can be achieved through different approaches, several of which focus on adaptive voltage regulation. In this paper, we present a comprehensive exploration of how two server-grade systems behave in different frequency and core allocation configurations beyond nominal voltage operation. Our analysis, which is built on top of two state-of-the-art ARMv8 microprocessor chips (Applied Micro’s X-Gene 2 and X-Gene 3) aims (1) to identify the best performance per watt operation points when the servers are operating in various voltage/frequency combinations, (2) to reveal how and why the different core allocation options on the available cores of the microprocessor affect the energy consumption, and (3) to enhance the default Linux scheduler to take task allocation decisions for balanced performance and energy efficiency. Our findings, on actual servers’ hardware, have been integrated into a lightweight online monitoring daemon which decides the optimal combination of voltage, core allocation, and clock frequency to achieve higher energy efficiency. Our approach reduces on average the energy by 25.2% on X-Gene 2, and 22.3% on X-Gene 3, with a minimal performance penalty of 3.2% on X-Gene 2 and 2.5% on X-Gene 3, compared to the default system configuration. Keywords-Energy efficiency; voltage and frequency scaling; power consumption; multicore characterization; micro-servers;