Sraman Choudhury, Srikar Chundury, Subramaniam Kalambur, D. Sitaram
{"title":"软件栈版本对微架构的影响","authors":"Sraman Choudhury, Srikar Chundury, Subramaniam Kalambur, D. Sitaram","doi":"10.1145/3302541.3311963","DOIUrl":null,"url":null,"abstract":"Open source Big Data frameworks such as Spark have been evolvingquite rapidly. Many of the changes have addressed improvement inperformance mainly focusing on the performance of the entire job executing on a distributed system. Past studies have reported micro-architectural performance characteristics of benchmarks based onthese Big Data frameworks. Given the rapid changes to these frame-works, it is expected that some of these code changes will also have amicro-architectural impact. In this paper, we present a comparativestudy of performance of Apache Spark across two major revisions and demonstrate that there are micro-architectural differences in the way the applications use the hardware.","PeriodicalId":231712,"journal":{"name":"Companion of the 2019 ACM/SPEC International Conference on Performance Engineering","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Poster Paper Impact Of Software Stack Version On Micro-architecture\",\"authors\":\"Sraman Choudhury, Srikar Chundury, Subramaniam Kalambur, D. Sitaram\",\"doi\":\"10.1145/3302541.3311963\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Open source Big Data frameworks such as Spark have been evolvingquite rapidly. Many of the changes have addressed improvement inperformance mainly focusing on the performance of the entire job executing on a distributed system. Past studies have reported micro-architectural performance characteristics of benchmarks based onthese Big Data frameworks. Given the rapid changes to these frame-works, it is expected that some of these code changes will also have amicro-architectural impact. In this paper, we present a comparativestudy of performance of Apache Spark across two major revisions and demonstrate that there are micro-architectural differences in the way the applications use the hardware.\",\"PeriodicalId\":231712,\"journal\":{\"name\":\"Companion of the 2019 ACM/SPEC International Conference on Performance Engineering\",\"volume\":\"127 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Companion of the 2019 ACM/SPEC International Conference on Performance Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3302541.3311963\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Companion of the 2019 ACM/SPEC International Conference on Performance Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3302541.3311963","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Poster Paper Impact Of Software Stack Version On Micro-architecture
Open source Big Data frameworks such as Spark have been evolvingquite rapidly. Many of the changes have addressed improvement inperformance mainly focusing on the performance of the entire job executing on a distributed system. Past studies have reported micro-architectural performance characteristics of benchmarks based onthese Big Data frameworks. Given the rapid changes to these frame-works, it is expected that some of these code changes will also have amicro-architectural impact. In this paper, we present a comparativestudy of performance of Apache Spark across two major revisions and demonstrate that there are micro-architectural differences in the way the applications use the hardware.