R. Iyer, M. Bhat, Li Zhao, R. Illikkal, S. Makineni, Michael Jones, K. Shiv, D. Newell
{"title":"探索商业Java服务器的小规模和大规模CMP体系结构","authors":"R. Iyer, M. Bhat, Li Zhao, R. Illikkal, S. Makineni, Michael Jones, K. Shiv, D. Newell","doi":"10.1109/IISWC.2006.302744","DOIUrl":null,"url":null,"abstract":"As we enter the era of chip multiprocessor (CMP) architectures, it is important that we explore the scaling characteristics of mainstream server workloads on these platforms. In this paper, we analyze the performance of an Enterprise Java workload (SPECjbb2005) on two important classes of CMP architectures. One class of CMP platforms comprise of \"small-scale\" CMP (SCMP) processors with a few large out-of order cores on the die. Another class of CMP platforms comprise of \"large-scale\" CMP (LCMP) processors) with several small in-order cores on the die. For these classes of CMP architectures to succeed, it is important that there are sufficient resources (cache, memory and interconnect) to allow for a balanced scalable platform. In this paper, we focus on evaluating the resource scaling characteristics (cores, caches and memory) of SPECjbb2005 on these two architectures and understanding architectural trade-offs that may be required in future CMP offerings. The overall evaluation is uniquely conducted using four different methodologies (measurements on latest platforms, trace-based cache simulation, trace-based platform simulation and execution-driven emulation). Based on our findings, we summarize the architectural recommendations for future CMP server platforms (e.g. the need for large DRAM caches)","PeriodicalId":222041,"journal":{"name":"2006 IEEE International Symposium on Workload Characterization","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Exploring Small-Scale and Large-Scale CMP Architectures for Commercial Java Servers\",\"authors\":\"R. Iyer, M. Bhat, Li Zhao, R. Illikkal, S. Makineni, Michael Jones, K. Shiv, D. Newell\",\"doi\":\"10.1109/IISWC.2006.302744\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As we enter the era of chip multiprocessor (CMP) architectures, it is important that we explore the scaling characteristics of mainstream server workloads on these platforms. In this paper, we analyze the performance of an Enterprise Java workload (SPECjbb2005) on two important classes of CMP architectures. One class of CMP platforms comprise of \\\"small-scale\\\" CMP (SCMP) processors with a few large out-of order cores on the die. Another class of CMP platforms comprise of \\\"large-scale\\\" CMP (LCMP) processors) with several small in-order cores on the die. For these classes of CMP architectures to succeed, it is important that there are sufficient resources (cache, memory and interconnect) to allow for a balanced scalable platform. In this paper, we focus on evaluating the resource scaling characteristics (cores, caches and memory) of SPECjbb2005 on these two architectures and understanding architectural trade-offs that may be required in future CMP offerings. The overall evaluation is uniquely conducted using four different methodologies (measurements on latest platforms, trace-based cache simulation, trace-based platform simulation and execution-driven emulation). Based on our findings, we summarize the architectural recommendations for future CMP server platforms (e.g. the need for large DRAM caches)\",\"PeriodicalId\":222041,\"journal\":{\"name\":\"2006 IEEE International Symposium on Workload Characterization\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Symposium on Workload Characterization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IISWC.2006.302744\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Symposium on Workload Characterization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISWC.2006.302744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring Small-Scale and Large-Scale CMP Architectures for Commercial Java Servers
As we enter the era of chip multiprocessor (CMP) architectures, it is important that we explore the scaling characteristics of mainstream server workloads on these platforms. In this paper, we analyze the performance of an Enterprise Java workload (SPECjbb2005) on two important classes of CMP architectures. One class of CMP platforms comprise of "small-scale" CMP (SCMP) processors with a few large out-of order cores on the die. Another class of CMP platforms comprise of "large-scale" CMP (LCMP) processors) with several small in-order cores on the die. For these classes of CMP architectures to succeed, it is important that there are sufficient resources (cache, memory and interconnect) to allow for a balanced scalable platform. In this paper, we focus on evaluating the resource scaling characteristics (cores, caches and memory) of SPECjbb2005 on these two architectures and understanding architectural trade-offs that may be required in future CMP offerings. The overall evaluation is uniquely conducted using four different methodologies (measurements on latest platforms, trace-based cache simulation, trace-based platform simulation and execution-driven emulation). Based on our findings, we summarize the architectural recommendations for future CMP server platforms (e.g. the need for large DRAM caches)