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 Performance considerations. (CUDA best practices) . NVIDIA CUDA C programming best practices guide. ACK: CUDA teaching center Stanford (. Hoberrock. and . Tarjan. ).. Outline. Host to device memory transfer. – . From hardware prospective to software. Presenter: D96943001 . 電子所 陳泓輝. Why Moore’s Law is die. He is not CEO anymore!!. Walls => ILP, Frequency, Power, Memory walls. ILP – more cost less return. 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. 27 . – Feb 3, . 2010. Multicore. (and Shared Memory) Programming with . Cilk. ++. Multicore and NUMA architectures. Multithreaded Programming. Cilk++ as a concurrency platform. Divide and conquer paradigm for Cilk++. Parallel Processing (CS526) . Spring 2012(Week 8) . Shared Memory Architecture . Shared Memory Programming & PLs. Java Threads . Preparing the Environment . In This lecture . Shared Memory Architecture . 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. Performance considerations. (CUDA best practices) . NVIDIA CUDA C programming best practices guide. ACK: CUDA teaching center Stanford (. Hoberrock. and . Tarjan. ).. Outline. Host to device memory transfer. 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. Multicore and NUMA architectures. Multithreaded Programming. . Cilk. as a concurrency platform. . Work, Span, (potential) Parallelism. Thanks to . Charles E. Leiserson for some of these slides. modelS. CS 5802 . Monica Borra. Overview. Types of parallel programming models. Shared memory Model. OpenMP. POSIX Threads. Cilk. /. Cilk. Plus/. Cilk. Plus . Plus. Thread Building Blocks. Types of Parallel Programming Models:. ,. and . Cilk. screen. , are trademarks of . CILK. . ARTS.. including analysis and debugging. MAJOR SECTIONS. Cilk++ Syntax and Concepts. Races and Race Detection. Scalability Analysis. The Cilk++ Tool Set. Gyrokinetic. Particle-to-Grid Interpolation for Multicore Processors. Kamesh. . Madduri. , . Samuel Williams. , . Stephane. . Ethier. , . Leonid . Oliker. , John . Shalf. , Erich . Strohmaier. , Katherine Yelick .

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