PPT-Parallel Performance

6162010 Parallel Performance 1 Performance Considerations I parallelized my code and The code slower than the sequential version or I dont get enough speedup What should I do 6162010. When you use parallel structure you increase the readability of your writing by creating word patterns readers can follow easily Understanding Parallel Structure Parallel structure also called parallelism is the repe tition of a chosen grammatical f 1 WHY CHOOSE PARALLELISM Parallel construction also called parallelism shows that two or more ideas are equally important by stating them in grammatically parallel form noun lined up with noun verb with verb phrase Hardware Parallelism. Computing: execute instructions that operate on data.. Flynn’s . taxonomy (Michael Flynn, 1967) classifies computer architectures based on the number of instructions that can be executed and how they operate on data.. Parallel and Perpendicular Lines. Perpendicular lines. are two lines that intersect to form a 90º. . angle. . Parallel and Perpendicular Lines. Parallel lines. are two lines that, if extended indefinitely, would never cross or touch. Geo-Simulations. Saulo Henrique Cabral Silva. Tiago Garcia de Senna Carneiro*. TerraLAB. – . Laboratory. for . Earh. System . Modeling. . and. . Simulation. Computer. . Science. . Department. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . What is Multiprocessing?. Enables several programs to run concurrently. Coordinated processing of Programs by more than one processor. Use of 2 or more CPUs within a single computer system. Ability of a system to support more than one processor and to allocate tasks between them. Task Scheduling in Heterogeneous . Computing . Environments . Senior Design Students: Christopher . Blandin. . and Dylan . Machovec. Post-doctoral Scholar: Bhavesh Khemka. Faculty Advisor: H. J. Siegel. Parallel . Architectures. . & Performance Analysis. Parallel computer: multiple-processor system supporting parallel programming.. Three principle types of architecture. Vector computers, in particular processor arrays. CS453. Lecture 3. A sequential algorithm is evaluated by its runtime (in general, asymptotic runtime as a function of input size). . The asymptotic runtime of a sequential program is identical on any serial platform. . Workshops . on Dynamic . Data Driven Applications Systems(DDDAS) In conjunction . with: 22nd . International Conference on . High. . Performance . Computing (. HiPC. ), Bengaluru. , India . 12/16/2015. Dr Susan Cartwright. Dept of Physics and Astronomy. University of Sheffield. Parallel Universes. Are you unique?. Could there be another “you” differing only in what you had for breakfast this morning?. Data in the Cloud. AFOSR FA9550-13-1-0225: Cloud-Based Perception and Control of Sensor Nets and Robot Swarms . 01/27/2016. 1. Geoffrey Fox, David . Crandall,. Supun. . Kamburugamuve. , . Jangwon. Lee, . A View from Berkeley. Dave Patterson. Parallel Computing Laboratory. U.C. Berkeley. July, 2008. Outline. What Caused the Revolution?. Is it an Interesting, Important Research Problem or Just Doing Industry’s Dirty Work?.