{"id":64,"date":"2017-08-30T08:41:38","date_gmt":"2017-08-30T07:41:38","guid":{"rendered":"http:\/\/blogg.lnu.se\/disa\/?p=64"},"modified":"2017-08-30T08:41:38","modified_gmt":"2017-08-30T07:41:38","slug":"memaxes-visualization-and-analytics-for-characterizing-complex-memory-performance-behaviors","status":"publish","type":"post","link":"https:\/\/blogg.lnu.se\/disa\/?p=64","title":{"rendered":"MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors"},"content":{"rendered":"<p>A new publication in the journal:\u00a0<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=2945\" target=\"_blank\" rel=\"noopener noreferrer\">IEEE Transactions on Visualization and Computer Graphics<\/a> by our senior lecturer <a href=\"https:\/\/lnu.se\/en\/staff\/ilir.jusufi\/\" target=\"_blank\" rel=\"noopener noreferrer\">Ilir Jusufi<\/a> about\u00a0High-Performance Computing memory performance analysis through the use of Visual Analytics.<\/p>\n<p><strong>Abstract:<\/strong> Memory performance is often a major bottleneck for high-performance computing (HPC) applications. Deepening memory hierarchies, complex memory management, and non-uniform access times have made memory performance behavior\u00a0difficult to characterize, and users require novel, sophisticated tools to analyze and optimize this aspect of their codes. Existing tools target only specific factors of memory performance, such as hardware layout, allocations, or access\u00a0instructions. However, today&#8217;s tools do not suffice to characterize the complex relationships between these factors. Further, they require advanced expertise to be used effectively. We present MemAxes, a tool based on a novel approach for\u00a0analytic-driven visualization of memory performance data. MemAxes uniquely allows users to analyze the different aspects related to memory performance by providing multiple visual contexts for a centralized dataset. We define mappings of\u00a0sampled memory access data to new and existing visual metaphors, each of which enabling a user to perform different analysis tasks. We present methods to guide user interaction by scoring subsets of the data based on known performance\u00a0problems. This scoring is used to provide visual cues and automatically extract clusters of interest. We designed MemAxes in collaboration with experts in HPC and demonstrate its effectiveness in case studies.<\/p>\n<p><strong>Reference:<\/strong> A. Gimenez; T. Gamblin; <strong>I. Jusufi<\/strong>; A. Bhatele; M. Schulz; P. T. Bremer; B. Hamann, \u201cMemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors,\u201d in\u00a0IEEE Transactions on Visualization and Computer\u00a0Graphics.<\/p>\n<p><a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=7955092&amp;isnumber=4359476\" target=\"_blank\" rel=\"noopener noreferrer\">Download the full publication here.<\/a><\/p>\n<p>\/\/Diana Unander Nordle<\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new publication in the journal:\u00a0IEEE Transactions on Visualization and Computer Graphics by our senior lecturer Ilir Jusufi about\u00a0High-Performance Computing memory performance analysis through the use of Visual Analytics. Abstract: Memory performance is often a major bottleneck for high-performance computing (HPC) applications. Deepening memory hierarchies, complex memory management, and non-uniform access times have made memory [&hellip;]<\/p>\n","protected":false},"author":401,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27510,27496],"tags":[27511],"class_list":["post-64","post","type-post","status-publish","format-standard","hentry","category-publications","category-visual-analytics","tag-visualization"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\r\n<title>MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors - DISA<\/title>\r\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\r\n<link rel=\"canonical\" href=\"https:\/\/blogg.lnu.se\/disa\/?p=64\" \/>\r\n<meta property=\"og:locale\" content=\"en_US\" \/>\r\n<meta property=\"og:type\" content=\"article\" \/>\r\n<meta property=\"og:title\" content=\"MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors - DISA\" \/>\r\n<meta property=\"og:description\" content=\"A new publication in the journal:\u00a0IEEE Transactions on Visualization and Computer Graphics by our senior lecturer Ilir Jusufi about\u00a0High-Performance Computing memory performance analysis through the use of Visual Analytics. Abstract: Memory performance is often a major bottleneck for high-performance computing (HPC) applications. 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