2010/04/26 by Jan Treibig, Treibig, Jan, Georg Hager +3 · 2 citations
Computer Science · #Advanced Data Storage Technologies #Cloud Computing and Resource Management #Distributed #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #Performance (cs.PF) #and Cluster Computing (cs.DC) #cs.DC #cs.PF
paper · pdf · doi:10.48550/arxiv.1004.4431
10 pages, 11 figures. Some clarifications and corrections
openalex publication_date 2010/04/26 · arxiv created 2010/06/30 · arxiv updated 2010/07/01 · openalex created_date 2022/10/07 · openalex updated_date 2026/07/28
Exploiting the performance of today's processors requires intimate knowledge of the microarchitecture as well as an awareness of the ever-growing complexity in thread and cache topology. LIKWID is a set of command-line utilities that addresses four key problems: Probing the thread and cache topology of a shared-memory node, enforcing thread-core affinity on a program, measuring performance counter metrics, and toggling hardware prefetchers. An API for using the performance counting features from user code is also included. We clearly state the differences to the widely used PAPI interface. To demonstrate the capabilities of the tool set we show the influence of thread pinning on performance using the well-known OpenMP STREAM triad benchmark, and use the affinity and hardware counter tools to study the performance of a stencil code specifically optimized to utilize shared caches on multicore chips.