document: HPCVIEW : a tool for top-down analysis of node performance It is increasingly difficult for complex scientific programs to attain a significant fraction of peak performance on systems that are based on microprocessors with substantial instruction-level parallelism and deep memory hierarchies . Despite this trend , performance analysis and tuning tools are still not used regularly by algorithm and application designers . To a large extent , existing performance tools fail to meet many user needs and are cumbersome to use . To address these issues , we developed HPCVIEW - a toolkit for combining multiple sets of program profile data , correlating the data with source code , and generating a database that can be analyzed anywhere with a commodity Web browser . We argue that HPCVIEW addresses many of the issues that have limited the usability and the utility of most existing tools . We originally built HPCVIEW to facilitate our own work on data layout and optimizing compilers . Now , in addition to daily use within our group , HPCVIEW is being used by several code development teams in DoD and DoE laboratories as well as at NCSA
doc_bio_tags: B O O O O O O O B I O O O O O B I I O O O O O O B I O O O O O O O O O O O O B I I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B I I O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O B I O B I O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O
extractive_keyphrases: hpcview node performance complex scientific programs peak performance deep memory hierarchies performance analysis source code commodity web browser data layout optimizing compilers
abstractive_keyphrases: top-down analysis instruction-level parallelism software tools binary analysis