M. Ferdman, Almutaz Adileh, Yusuf Onur Koçberber, Stavros Volos, M. Alisafaee, Djordje Jevdjic, Cansu Kaynak, Adrian Daniel Popescu, A. Ailamaki, B. Falsafi
{"title":"量化新兴的横向扩展应用程序和现代处理器之间的不匹配","authors":"M. Ferdman, Almutaz Adileh, Yusuf Onur Koçberber, Stavros Volos, M. Alisafaee, Djordje Jevdjic, Cansu Kaynak, Adrian Daniel Popescu, A. Ailamaki, B. Falsafi","doi":"10.1145/2382553.2382557","DOIUrl":null,"url":null,"abstract":"Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out workloads.\n In this work, we introduce CloudSuite, a benchmark suite of emerging scale-out workloads. We use performance counters on modern servers to study scale-out workloads, finding that today’s predominant processor microarchitecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the workload needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core microarchitecture. Moreover, while today’s predominant microarchitecture is inefficient when executing scale-out workloads, we find that continuing the current trends will further exacerbate the inefficiency in the future. In this work, we identify the key microarchitectural needs of scale-out workloads, calling for a change in the trajectory of server processors that would lead to improved computational density and power efficiency in data centers.","PeriodicalId":50918,"journal":{"name":"ACM Transactions on Computer Systems","volume":"10 1","pages":"15:1-15:24"},"PeriodicalIF":2.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"Quantifying the Mismatch between Emerging Scale-Out Applications and Modern Processors\",\"authors\":\"M. Ferdman, Almutaz Adileh, Yusuf Onur Koçberber, Stavros Volos, M. Alisafaee, Djordje Jevdjic, Cansu Kaynak, Adrian Daniel Popescu, A. Ailamaki, B. Falsafi\",\"doi\":\"10.1145/2382553.2382557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out workloads.\\n In this work, we introduce CloudSuite, a benchmark suite of emerging scale-out workloads. We use performance counters on modern servers to study scale-out workloads, finding that today’s predominant processor microarchitecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the workload needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core microarchitecture. Moreover, while today’s predominant microarchitecture is inefficient when executing scale-out workloads, we find that continuing the current trends will further exacerbate the inefficiency in the future. 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Quantifying the Mismatch between Emerging Scale-Out Applications and Modern Processors
Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out workloads.
In this work, we introduce CloudSuite, a benchmark suite of emerging scale-out workloads. We use performance counters on modern servers to study scale-out workloads, finding that today’s predominant processor microarchitecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the workload needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core microarchitecture. Moreover, while today’s predominant microarchitecture is inefficient when executing scale-out workloads, we find that continuing the current trends will further exacerbate the inefficiency in the future. In this work, we identify the key microarchitectural needs of scale-out workloads, calling for a change in the trajectory of server processors that would lead to improved computational density and power efficiency in data centers.
期刊介绍:
ACM Transactions on Computer Systems (TOCS) presents research and development results on the design, implementation, analysis, evaluation, and use of computer systems and systems software. The term "computer systems" is interpreted broadly and includes operating systems, systems architecture and hardware, distributed systems, optimizing compilers, and the interaction between systems and computer networks. Articles appearing in TOCS will tend either to present new techniques and concepts, or to report on experiences and experiments with actual systems. Insights useful to system designers, builders, and users will be emphasized.
TOCS publishes research and technical papers, both short and long. It includes technical correspondence to permit commentary on technical topics and on previously published papers.