FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W130717962> ?p ?o ?g. }

• W130717962 endingPage "58" @default.
• W130717962 startingPage "33" @default.
• W130717962 abstract "Previous chapter Next chapter Software, Environments, and Tools Parallel Processing for Scientific Computing3. Approaches to Architecture-Aware Parallel Scientific ComputationJames D. Teresco, Joseph E. Flaherty, Scott B. Baden, Jamal Faik, Sébastien Lacour, Manish Parashar, Valerie E. Taylor, Carlos A. Varela, Xingfu Wu, Rick Stevens, Nicholas Karonis, Ian Foster, Luis G. Gervasio, Travis Desell, and Kaoutar El MaghraouiJames D. Teresco, Joseph E. Flaherty, Scott B. Baden, Jamal Faik, Sébastien Lacour, Manish Parashar, Valerie E. Taylor, Carlos A. Varela, Xingfu Wu, Rick Stevens, Nicholas Karonis, Ian Foster, Luis G. Gervasio, Travis Desell, and Kaoutar El Maghraouipp.33 - 58Chapter DOI:https://doi.org/10.1137/1.9780898718133.ch3PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutExcerpt Modern parallel scientific computation is being performed in a wide variety of computational environments that include clusters, large-scale supercomputers, grid environments, and metacomputing environments. This presents challenges for application and library developers, who must develop architecture-aware software if they wish to utilize several computing platforms efficiently. Architecture-aware computation can be beneficial in single-processor environments. It takes the form of something as common as an optimizing compiler, which will optimize software for a target computer. Application and library developers may adjust data structures or memory management techniques to improve cache utilization on a particular system [21]. Parallel computation introduces more variety and, with that, more need and opportunity for architecture-specific optimizations. Heterogeneous processor speeds at first seem easy to account for by simply giving a larger portion of the work to faster processors, but assumptions of homogeneous processor speeds may be well hidden. If all processor speeds are the same, differences between uniprocessor nodes and symmetric multiprocessing (SMP) nodes may be important. Computational and communication resources may not be dedicated to one job, and the external loads on the system may be highly dynamic and transient. Interconnection networks may be hierarchical, leading to nonuniform communication costs. Even if targeting only homogeneous systems, the relative speeds of processors, memory, and networks may affect performance. Heterogeneous processor architectures (e.g., Sparc, x86) present challenges for portable software development and data format conversions. Some operating systems may provide support for different programming paradigms (e.g., message passing, multithreading, priority thread scheduling, or distributed shared memory). Previous chapter Next chapter RelatedDetails Published:2006ISBN:978-0-89871-619-1eISBN:978-0-89871-813-3 https://doi.org/10.1137/1.9780898718133Book Series Name:Software, Environments, and ToolsBook Code:SE20Book Pages:xxiv + 383Key words:Parallel processing, scientific computing, parallel algorithms, high-performance computing, computational science and engineering" @default.
• W130717962 created "2016-06-24" @default.
• W130717962 creator A5017232258 @default.
• W130717962 creator A5020231199 @default.
• W130717962 creator A5028916710 @default.
• W130717962 creator A5032231503 @default.
• W130717962 creator A5034513925 @default.
• W130717962 creator A5039235248 @default.
• W130717962 creator A5043777072 @default.
• W130717962 creator A5053682943 @default.
• W130717962 creator A5060153432 @default.
• W130717962 creator A5061393608 @default.
• W130717962 creator A5065630093 @default.
• W130717962 creator A5066286796 @default.
• W130717962 creator A5072646801 @default.
• W130717962 creator A5078747474 @default.
• W130717962 creator A5081819871 @default.
• W130717962 date "2006-01-01" @default.
• W130717962 modified "2023-09-30" @default.
• W130717962 title "3. Approaches to Architecture-Aware Parallel Scientific Computation" @default.
• W130717962 cites W119531108 @default.
• W130717962 cites W1482691660 @default.
• W130717962 cites W1506225852 @default.
• W130717962 cites W1552895988 @default.
• W130717962 cites W1554500830 @default.
• W130717962 cites W1556439447 @default.
• W130717962 cites W1577931366 @default.
• W130717962 cites W1590493039 @default.
• W130717962 cites W1847278726 @default.
• W130717962 cites W190555601 @default.
• W130717962 cites W1972209410 @default.
• W130717962 cites W1973721022 @default.
• W130717962 cites W1995893174 @default.
• W130717962 cites W2001130603 @default.
• W130717962 cites W2005106218 @default.
• W130717962 cites W2008634671 @default.
• W130717962 cites W2010556856 @default.
• W130717962 cites W2016358147 @default.
• W130717962 cites W2018885404 @default.
• W130717962 cites W2020140168 @default.
• W130717962 cites W2031029830 @default.
• W130717962 cites W2043909673 @default.
• W130717962 cites W2052611150 @default.
• W130717962 cites W2060578420 @default.
• W130717962 cites W2070232376 @default.
• W130717962 cites W2072794470 @default.
• W130717962 cites W2073890622 @default.
• W130717962 cites W2077783617 @default.
• W130717962 cites W2080822323 @default.
• W130717962 cites W2083209848 @default.
• W130717962 cites W2091257550 @default.
• W130717962 cites W2096070062 @default.
• W130717962 cites W2096692833 @default.
• W130717962 cites W2106122510 @default.
• W130717962 cites W2109418429 @default.
• W130717962 cites W2111516947 @default.
• W130717962 cites W2112279714 @default.
• W130717962 cites W2114030927 @default.
• W130717962 cites W2116730320 @default.
• W130717962 cites W2118953734 @default.
• W130717962 cites W2121253712 @default.
• W130717962 cites W2121389697 @default.
• W130717962 cites W2122403196 @default.
• W130717962 cites W2133994512 @default.
• W130717962 cites W2135653967 @default.
• W130717962 cites W2136770272 @default.
• W130717962 cites W2138106552 @default.
• W130717962 cites W2139484845 @default.
• W130717962 cites W2140077020 @default.
• W130717962 cites W2153789397 @default.
• W130717962 cites W2161539186 @default.
• W130717962 cites W2164488397 @default.
• W130717962 cites W2164564100 @default.
• W130717962 cites W2166417226 @default.
• W130717962 cites W2167377545 @default.
• W130717962 cites W2171532807 @default.
• W130717962 cites W2405593948 @default.
• W130717962 cites W2467192254 @default.
• W130717962 cites W2533488875 @default.
• W130717962 cites W2988891856 @default.
• W130717962 cites W52205918 @default.
• W130717962 cites W81984058 @default.
• W130717962 cites W93743056 @default.
• W130717962 cites W96060697 @default.
• W130717962 cites W82159249 @default.
• W130717962 doi "https://doi.org/10.1137/1.9780898718133.ch3" @default.
• W130717962 hasPublicationYear "2006" @default.
• W130717962 type Work @default.
• W130717962 sameAs 130717962 @default.
• W130717962 citedByCount "0" @default.
• W130717962 crossrefType "book-chapter" @default.
• W130717962 hasAuthorship W130717962A5017232258 @default.
• W130717962 hasAuthorship W130717962A5020231199 @default.
• W130717962 hasAuthorship W130717962A5028916710 @default.
• W130717962 hasAuthorship W130717962A5032231503 @default.
• W130717962 hasAuthorship W130717962A5034513925 @default.
• W130717962 hasAuthorship W130717962A5039235248 @default.
• W130717962 hasAuthorship W130717962A5043777072 @default.

• next