PPT-Starting Parallel Algorithm Design

David Monismith Based on notes from Introduction to Parallel Programming 2 nd Edition by Grama Gupta Karypis and Kumar Outline Decomposition Tasks and Interaction Load Balancing. We then consider the complications introduced by the introduction of parallelism and look at some proposed parallel frameworks Analysing Sequential Algorithms The design and analysis of sequential algorithms is a well developed 64257eld with a large Unlike sequential algorithms parallel algorithms cannot be analyzed very well in isolation One of our primary measures of goodness of a parallel system will be its scalability Scalability is the ability of a parallel system to take advantage of incr Burrows-Wheeler. Compression and Decompression. James A. Edwards. , Uzi Vishkin. University of Maryland. Introduction. Lossless data compression. Common tool . . better use of . memory (e.g., disk space). On . the development of numerical . parallel algorithms . for the insetting procedure. Master of Science in . Communication & Information Systems.  . Department of Informatics & Communications. Algorithms:. Graph . coloring. Created by: . . . Avdeev. . Alex,. . . Blakey Paul.. Criteria for good graph coloring algorithm:. Coloring Quality: . Number of colors needed . Number of colors ( . April 10, 2012. Parallel Graph Algorithms. Aydın . Buluç. ABuluc@lbl.gov. Lawrence Berkeley National Laboratory. Some slides from: . Kamesh. . Madduri. , John Gilbert, Daniel . Delling. . Graph Preliminaries. Jeremiah van Oosten. Reinier. van . Oeveren. Introduction. Related Works. Prefix Sums and Scans. Recursive Filtering. Summed-Area Tables. Problem Definition. Parallelization Strategies. Baseline (Algorithm RT). Time for Hardware Upgrade. Uzi Vishkin. . . The pompous version. After 40 years of “wandering in the desert”, general-purpose parallelism is very close to capturing the “promised land” of mainstream computing. Solving the SVP in the Ideal Lattice of 128 dimensions. Tsukasa Ishiguro (KDDI R&D Laboratories). Shinsaku Kiyomoto (KDDI R&D Laboratories) . Yutaka Miyake (KDDI R&D Laboratories). Tsuyoshi Takagi. Evaluation. . Sequential: runtime (execution time). . Ts. =T (. InputSize. ). . Parallel: runtime (. s. tart-->last PE ends). . Tp. =T (. InputSize,p,architecture. ). . Note: Cannot be Evaluated in Isolation from the Parallel architecture. 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. 2. 　. Turing machine. 　. RAM (. Figure . ). 　. Logic circuit model. . RAM . (Random Access Machine). Operations . supposed to be executed in one unit time. (1). 　. Control operations such as. Our Model. Task Analysis – results in a set of tasks and user personas that can be used to evaluate potential designs.. User Personas (Design for Hackers) are kind of like the personas in Task Analysis. . By:. Dasari Charithambika (210302). Divya Gupta(210353). Course Instructors:. Dr. Preeti Malakar. Dr. Soumya Dutta.. M. Larsen, S. Labasan, P. Navrátil,. J.S. Meredith, and H. Childs (2015). Various hardware architectures are used in supercomputers, including GPUs, many-core coprocessors, large multi-core CPUs, low-power architectures, hybrid designs, and experimental designs..