PPT-Parallel & GPU computing in MATLAB
Author : luanne-stotts | Published Date : 2016-06-13
ITS Research Computing Lani Clough Mark Reed markreeduncedu Objectives Introductory level MATLAB course for people who want to learn parallel and GPU computing
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Parallel & GPU computing in MATLAB: Transcript
ITS Research Computing Lani Clough Mark Reed markreeduncedu Objectives Introductory level MATLAB course for people who want to learn parallel and GPU computing in MATLAB Help participants . P. arallel . P. rocessing. G. uy . T. el-. Z. ur. L. ecture 8. The Course Roadmap. Introduction. Message Passing. HTC. HPC. Shared Memory. Condor. Cloud Computing. MPI. OpenMP. T. oday. Today. Next week. Goals for Rest of Course. Learn how to program massively parallel processors and achieve. high performance. functionality and maintainability. scalability across future generations. Acquire technical knowledge required to achieve the above goals. mei. W. . Hwu. , 2007-2012 . University . of Illinois, Urbana-Champaign. 1. CS/EE 217. GPU Architecture and Parallel . Programming. Project . Kickoff. Two flavors. Application. Implement/optimize an realistic application on GPGPUs. Lecture 2: more basics. Recap. Can use GPU to solve highly parallelizable problems. Straightforward extension to C++. Separate CUDA code into .cu and .. cuh. files and compile with . nvcc. to create object files (.o files). Going Beyond Serial MATLAB Applications. MATLAB . Desktop (Client). Worker. Worker. Worker. Worker. Worker. Worker. Programming Parallel Applications (CPU). Built-in support. with t. oolboxes. Ease of Use. Add GPUs: Accelerate Science Applications. © NVIDIA 2013. Small Changes, Big Speed-up. Application Code. . GPU. C. PU. Use GPU to Parallelize. Compute-Intensive Functions. Rest of Sequential. CPU Code. Wendy Thomas. Associate Professor of Bioengineering . University of Washington. 1. My Teaching Experience. . Bioen. 201 (2008 – 2010) sophomore core: intro to mathematical programming (5 weeks) and circuits (5 weeks). Department of Geography and Planning. University at Albany. What is a GPU?. A GPU is a . graphics processing unit. Modern GPUs are composed of multiple processors. Each of these processors can perform operations similar to those of CPUs. CS 179: GPU Programming Lecture 7 Week 3 Goals: Advanced GPU- accelerable algorithms CUDA libraries and tools This Lecture GPU- accelerable algorithms: Reduction Prefix sum Stream compaction Sorting (quicksort) A Tale of Two Cities: GPU Computing and Machine Learning Dr. Xiaowen Chu Department of Computer Science, Hong Kong Baptist University Outline 2 Some Stories of “Two Cities” Evolution of CPUs/ Waters. Introduction to GPU Computing. Brief History of GPU Computing. Technical Issues. Social Impact. Marketing and Ethical . Issues. Project Management. Conclusion. Table of Contents. A . GPU is . Patrick Cozzi. University of Pennsylvania. CIS 565 - Fall 2013. Lectures. Monday and Wednesday. 6-7:30pm. Towne . 307. Fall. and . Spring. 2012 lectures were recorded. Attendance is required for guest lectures. Mark Reed . Lani Clough. Objectives. Intermediate. level MATLAB course for people . already using. . MATLAB.. Help participants . go past the basics . and improve the performance their MATLAB code. . Jerry Adams. 1. , Bradley Hittle. 2. , Eliot Prokop. 3. , . Ronny Antequera. 3. , Dr.Prasad Calyam. 3. University of Hawaii-West Oahu. 1. , . The . Ohio State University. 2. , University of Missouri-Columbia.
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