PPT-A Tale of Two Cities: GPU Computing and Machine Learning Dr.

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. ITS Research Computing. Mark Reed . Objectives. Learn why computing with accelerators is important. Understand accelerator hardware. Learn what types of problems are suitable for accelerators. Survey the programming models available. Condor Week 2012. Bob Nordlund. Grid Computing @The Hartford…. Using Condor in our production environment since 2004. Computing Environment. Two pools (Hartford, CT and Boulder, CO). Linux central managers and schedulers. World: Then and Now. United States: Then and Now. First Great Depression. Second Great Depression. Barry . Eichengreen. , Kevin . Hjortshøj. O’Rourke, “A Tale of Two Depressions . Redux. ” . (6 March 2012. Alex Wade. CAP6938 Final Project. Introduction. GPU based implementation of . A Computational Approach to Edge Detection. by John Canny. Paper presents an accurate, localized edge detection method. Purpose. 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. The. French. Revolution. Jacques-Louis David (1748-1825). David was the foremost artist during the French Revolution and in the Neoclassical style. He lived through the entire French Revolution and the Napoleonic era. . 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. Hui. Li. Geoffrey Fox. Research Goal. provide . a uniform . MapReduce programming . model that works . on HPC . Clusters or . Virtual Clusters cores . on traditional Intel architecture chip, cores on . By: Bria Hicks and Rachel Franklin. Prologue. You are in poverty, but it is your fault that you will not ask for help. You blame God and your neighbors. If you’re poor, people will hate you and you will become jealous of your neighbor because he has more than you.. ITS Research Computing. Mark Reed . Objectives. Learn why computing with accelerators is important. Understand accelerator hardware. Learn what types of problems are suitable for accelerators. Survey the programming models available. 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) Scientific Computing and Visualization. Boston . University. GPU Programming. GPU – graphics processing unit. Originally designed as a graphics processor. Nvidia's. GeForce 256 (1999) – first GPU. Martin Burtscher. Department of Computer Science. High-end CPU-GPU Comparison. . Xeon 8180M. . Titan V. Cores 28 5120 (+ 640). Active threads 2 per core 32 per core. Frequency 2.5 (3.8) GHz 1.2 (1.45) GHz. Patrick Cozzi. University of Pennsylvania. CIS 565 - Fall 2014. Lectures. Monday. 6-9pm. Moore 212. Fall. and . Spring. 2012 lectures were recorded. Attendance is required for guest lectures. Image from .