PPT-CS 240A: Shared Memory & Multicore Programming with Cilk

Author : myesha-ticknor | Published Date : 2018-03-17

Multicore and NUMA architectures Multithreaded Programming Cilk as a concurrency platform Work and Span Thanks to Charles E Leiserson for some of these slides Multicore

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CS 240A: Shared Memory & Multicore Programming with Cilk: Transcript

Multicore and NUMA architectures Multithreaded Programming Cilk as a concurrency platform Work and Span Thanks to Charles E Leiserson for some of these slides Multicore Architecture. Message Passing Sharedmemory single copy of shared data in memory threads communicate by readingwriting to a shared location Messagepassing each thread has a copy of data in its own private memory that other threads cannot access threads communicate Breadth-first search in . Cilk. ++. Thanks to . Charles E. . Leiserson. for . some of . these slides. Breadth First Search. Level-by-level graph traversal. Serially complexity:. . Θ. (m+n). 1. 2. 3. Multicore and NUMA architectures. Multithreaded Programming. Cilk++ as a concurrency platform. Work and Span. Thanks to . Charles E. Leiserson for some of these slides. Multicore Architecture. People. Project at MIT & now at UT Austin. Bobby Blumofe (now UT Austin, Akamai). Chris Joerg. Brad Kuszmaul (now Yale). Charles Leiserson (MIT, Akamai). Keith Randall (Bell Labs) . Yuli Zhou (Bell Labs) . Based heavily on a slide set by Colin Ponce. Rethinking Operating System Designs for a . Multicore World. Multicore computer: A computer with more than one CPU.. 1960-1990. : Multicore existed in mainframes . Lecture 3. MADALGO Summer School 2012. Algorithms for Modern Parallel and Distributed Models . Phillip B. Gibbons. Intel Labs Pittsburgh. August 22, 2012. Multi-core Computing Lectures: . Progress-to-date on Key Open Questions. Feb 2, 2015. Multicore (and Shared Memory) Programming with . Cilk. Plus. Multicore and s. hared . m. emory. . Cilk. . Plus and the divide & conquer . p. aradigm. Data races. Analyzing performance in . Matrix multiplication I : parallel issues. Matrix multiplication II: cache issues. Thanks to Jim Demmel and Kathy Yelick (UCB) for some of these slides. Matrix-Matrix . Multiplication (“DGEMM”). Multicore Panel at eScience 2008. December . 11 2008. Geoffrey Fox. Community Grids Laboratory. , . School of informatics . Indiana University. gcf@indiana.edu. , . http://www.infomall.org. Lessons. Not surprising . Hakim Weatherspoon. CS 3410, Spring 2015. Computer Science. Cornell University. P&H Chapter 2.11, 5.10,. and 6.5. Announcements. HW2 Review Sessions!. TODAY, Tue, . April 21st. , . Hollister B14@7pm. Yao Wang, Andrew . Ferraiuolo. , G. Edward . Suh. Feb 17. th. 2014. Executive Summary. Observation:. Modern computing systems are vulnerable to . timing channel attacks. Problem: . No hardware techniques exist to eliminate timing channels through . The Desired Brand Effect Stand Out in a Saturated Market with a Timeless Brand

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