PPT-ECE 757 Review: Parallel Processors

Prof Mikko Lipasti Lecture notes based in part on slides created by John Shen Mark Hill David Wood Guri Sohi Jim Smith Erika Gunadi Mitch Hayenga Vignyan Reddy . Sathish. . Vadhiyar. PRAM Model - Introduction. Parallel Random Access Machine. Allows parallel-algorithm designers to treat processing power as unlimited. Ignores complexity of inter-process communication. 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.. vs. Sequential Algorithms. Design of efficient algorithms. A parallel computer is of little use unless efficient parallel algorithms are available.. The issue in designing parallel algorithms are very different from those in designing their sequential counterparts.. of Parallel Neuronal Models on Triton Cluster. Anita . Bandrowski. , . Prithvi. . Sundararaman. , Subhashini Sivagnanam, Kenneth Yoshimoto, . Amitava. . Majumdar. and Maryann . Martone. University of California , San Diego, CA. Performance Theory - 1. Parallel Computing. CIS . 410/. 510. Department of Computer and Information Science. Outline. Performance scalability. Analytical performance measures. Amdahl. ’. s. law and Gustafson-. 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 . Anthony Waterman. Topics to Discuss. Are online games . c. onceptually. . p. arallel?. What portions of a game benefit from parallelization?. Graphics Processing Units (GPUs) . General-Purpose . C. omputing . Thread Level Parallelism. Chapter 4, Appendix H. CS448. 2. The Greed for Speed. Two general approaches to making computers faster. Faster uniprocessor. All the techniques we’ve been looking at so far, plus others…. Computing. Jie Liu. , . Ph.D.. Professor. Computer Science Division. Western Oregon University. Monmouth, Oregon, USA. liuj@wou.edu. outline. The . fastest computers. The PRAM model. The O(1) algorithm that finds the max. By:. Atena. . Daneshmandi. Outline. Introduction. Typology of Parallel . Tasks. Task . Graphs. A Deterministic module . A Deterministic module by Gantt . Chart. C# Example(Three Tasks in Parallel). Complexity . Sathish. . Vadhiyar. PRAM Model - Introduction. Parallel Random Access Machine. Allows parallel-algorithm designers to treat processing power as unlimited. Ignores complexity of inter-process communication. Quarter: Summer 2017. CSE 373: Data Structures and Algorithms. Lecture . 23: Parallelism: Map, Reduce, Analysis. Today. More on parallelism. Map & Reduce . Analysis of Efficiency. Reminder: . C. ome visit my office hours to pick up midterm. Tennessee State University. 2017. 年. 6. 月. at. 法政大学. 1. Lectures on Parallel and Distributed Computing . 2. Lecture . 1: Introduction to parallel . computing . Lecture 2: Parallel . computational models. Massively Parallel Processors. Instructor:Mikko. H . Lipasti. Spring 2017. University of Wisconsin-Madison. Lecture notes based on slides created by John . Shen. , Mark Hill, David Wood, . Guri. . Sohi.