2011/05/22 by Neil J. Gunther, Neil J. Günther, Shanti Subramanyam +4 · 4 citations
Computer Science · #B.8 #C.4 #C.5.5 #Cloud Computing and Resource Management #Computer architecture #Computer science #Core (optical fiber) #D.4.8 #Distributed #Distributed computing #F.1.2 #FOS: Computer and information sciences #Multi-core processor #Multithreading #Operating system #Parallel #Parallel Computing and Optimization Techniques #Performance (cs.PF) #Scalability #Software System Performance and Reliability #Telecommunications #Thread (computing) #and Cluster Computing (cs.DC) #cs.DC #cs.PF
paper · pdf · doi:10.48550/arxiv.1105.4301
published in arXiv (Cornell University) (Cornell University) · 21 pages, 11 figures. To appear in "Programming Multi-core and Many-core Computing Systems," eds. S. Pllana and F. Xhafa, Wiley Series on Parallel and Distributed Computing
arxiv created 2011/05/22 · openalex publication_date 2011/05/22 · arxiv updated 2011/05/24 · openalex created_date 2022/10/02 · openalex updated_date 2026/08/08
We show how to quantify scalability with the Universal Scalability Law (USL) by applying it to performance measurements of memcached, J2EE, and Weblogic on multi-core platforms. Since commercial multicores are essentially black-boxes, the accessible performance gains are primarily available at the application level. We also demonstrate how our methodology can identify the most significant performance tuning opportunities to optimize application scalability, as well as providing an easy means for exploring other aspects of the multi-core system design space.