COMP 422: Introduction To Parallel Computing
COMP 422: Introduction toParallel ComputingVivek SarkarDepartment of Computer ScienceRice Universityvsarkar@rice.eduCOMP 422 Lecture 1 8 January 2008
Acknowledgments for today’s lecture Jack Dongarra (U. Tennessee) --- CS 594 slides from -PAGES/cs594-2008.htm John Mellor-Crummey (Rice) --- COMP 422 slides from Spring2007 Kathy Yelick (UC Berkeley) --- CS 267 slides from Spring 2007—http://www.eecs.berkeley.edu/ yelick/cs267 sp07/lectures Slides accompanying course textbook—http://www-users.cs.umn.edu/ karypis/parbook/2COMP 422, Spring 2008 (V.Sarkar)
Course Information Meeting time: TTh 10:50-12:05 Instructor: Vivek SarkarMeeting place: DH 1046— vsarkar@rice.edu, x5304, DH 3131— office hours: Wednesdays 11am - 12noon, and by appointment TA: Raj Barik— rajbarik@rice.edu, x2738, DH 2070— Office hours: Tuesdays & Thursdays, 1pm - 2pm, and by appointment Web site: http://www.owlnet.rice.edu/ comp4223COMP 422, Spring 2008 (V.Sarkar)
Prerequisites Programming in C, Fortran, or JavaBasics of data structuresBasics of machine architectureRequired courses: Comp 212 and 320, or equivalentSee me if you have concerns!4COMP 422, Spring 2008 (V.Sarkar)
TextIntroduction to ParallelComputing, 2nd EditionAnanth Grama,Anshul Gupta,George Karypis,Vipin / karypis/parbook/5COMP 422, Spring 2008 (V.Sarkar)
Topics Introduction (Chapter 1) --- today’s lecture Principles of Parallel Algorithm Design (Chapter 3) Programming Shared Address Space Platforms (Chapter 7)— New material: new programming models (beyond threads and OpenMP) --- JavaConcurrency Utilities, Intel Thread Building Blocks, .Net Parallel Extensions (TaskParallel Library & PLINQ), Cilk, X10 Dense Matrix Operations (Chapter 8)Parallel Programming Platforms (Chapter 2)— New material: homogeneous & heterogeneous multicore platformsAnalytical Modeling of Parallel Programs (Chapter 5)— New material: theoretical foundations of task schedulingGraph Algorithms (Chapter 10)Programming Using the Message-Passing Paradigm (Chapter 6)— New material: Partitioned Global Address Space (PGAS) languages --- UnifiedParallel C (UPC), Co-array Fortran (CAF) New material: Programming Heterogeneous Processors and Accelerators New material: Problem Solving on Large Scale Clusters using MapReduce 6(Secondary references willbe assignedfor 2008new material)COMP422, Spring(V.Sarkar)
Parallel Machines for the Course Ada—316 dual-core Opteron processors—dual processor nodes—Infiniband interconnection network—no global shared memory Additional nodes on Ada—Quad-core AMD Barcelona (denali)—Sun T2000 (yellowstone) Google/IBM cluster—Accounts to be obtained later in semester7COMP 422, Spring 2008 (V.Sarkar)
Assignments and Exams Coursework will be weighted as follows:—Homeworks: 5%—Programming Assignments: 55%– to be done individually or in 2-person teams; the requirements willbe scaled accordingly—Midterm Exam: 20% (one-hour written exam)—Final Exam: 20% (one-hour multiple-choice exam)8COMP 422, Spring 2008 (V.Sarkar)
Why is Parallel ComputingImportant?9COMP 422, Spring 2008 (V.Sarkar)
Computing and Science “Computational modeling and simulation are among the most significantdevelopments in the practice of scientific inquiry in the 20th Century. Within thelast two decades, scientific computing has become an important contributor toall scientific disciplines.It is particularly important for the solution of research problems that areinsoluble by traditional scientific theoretical and experimental approaches,hazardous to study in the laboratory, or time consuming or expensive to solveby traditional means” — “Scientific Discovery through Advanced Computing”DOE Office of Science, 200010COMP
Department of Computer Science Rice University vsarkar@rice.edu COMP 422: Introduction to . Introduction to Parallel Computing, 2nd Edition Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar Addison-Wesley 2003 . Do theory or paper design. 2) .
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6 COMP 422, Spring 2008 (V.Sarkar) Tasks and Dependency Graphs The first step in developing a parallel algorithm is to decompose the problem into tasks that are candidates for parallel execution Task indivisible sequential unit of computation A decomposition can be illustrated in the form of a directed graph with nodes corresponding to tasks and edges
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May 10, 2016 · fmwasilewski@usfca.edu millerd@usfca.edu General Counsel Donna Davis 415.422.6822 mdavisdj@usfca.edu Human Resources Diane Nelson 415.422.2441 dnelson3@usfca.edu Payment Request Disbursement Services 415.422.2387 ap@usfca.edu Risk Management Melissa Diaz 415.422.5899 mddiaz2@usfca.edu RETURN TO TOP
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