'Speedup' diaporamas de présentation

Andrei Maslennikov CASPUR Consortium May 2004

ADIC / CASPUR / CERN / DataDirect / ENEA / IBM / RZ Garching / SGI New results from CASPUR Storage Lab . Andrei Maslennikov CASPUR Consortium May 2004. Participated : ADIC Software : E.Eastman CASPUR : A.Maslennikov (*) , M.Mililotti, G.Palumbo

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Geometric methods in image processing, networks, and machine learning

Andrea Bertozzi University of California, Los Angeles. Geometric methods in image processing, networks, and machine learning. Diffuse interface methods. Total variation. Ginzburg-Landau functional. W is a double well potential with two minima

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Statistical Analysis and Modeling for Error Composition in Approximate Computation Circuits

Statistical Analysis and Modeling for Error Composition in Approximate Computation Circuits. Wei-Ting Jonas Chan 1 , Andrew B. Kahng 1 , Seokhyeong Kang 1 , Rakesh Kumar 2 , and John Sartori 3 1 VLSI CAD LABORATORY, UC San Diego 2 PASSAT GROUP, Univ. of Illinois 3 Univ. of Minnesota.

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Improving Parallel Performance

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TA Tom Magrino

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Head TA Scott Beamer cs.berkeley/ ~sbeamer

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CpE 442 Introduction to Computer Architecture The Role of Performance

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Read-Write Lock Allocation in Software Transactional Memory

Read-Write Lock Allocation in Software Transactional Memory. Amir Ghanbari Bavarsad and Ehsan Atoofian Lakehead University. Transactional Memory. Software transactional memory (STM) exploits a global clock to validate transactional data Pros: reduces validation overhead Cons: contention

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Designing and Evaluating Parallel Programs

Designing and Evaluating Parallel Programs. Anda Iamnitchi Federated Distributed Systems Fall 2006 Textbook (on line): Designing and Building Parallel Programs by Ian Foster (http://www-unix.mcs.anl.gov/dbpp/). Parallel Machines. Flynn's Taxonomy.

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Computer Science 320

Computer Science 320. Measuring Speedup. What Is Running Time?. T ( N , K ) says that the running time T is a function of the problem size N and the number of processors K

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Parallelizing METIS

A Graph Partitioning Algorithm Zardosht Kasheff. Parallelizing METIS. Sample Graph. Goal : Partition graph into n equally weighted subsets such that edge cut is minimized Edge-cut: Sum of weights of edges whose nodes lie in different partitions

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Speeding Up Algorithms for Hidden Markov Models by Exploiting Repetitions

Speeding Up Algorithms for Hidden Markov Models by Exploiting Repetitions. Shay Mozes Oren Weimann (MIT) Michal Ziv-Ukelson (Tel-Aviv U.). Shortly:. Hidden Markov Models are extensively used to model processes in many fields

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Communication Networks

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CS 584

CS 584. Logic. The art of thinking and reasoning in strict accordance with the limitations and incapacities of the human misunderstanding. The basis of logic is the syllogism, consisting of a major and minor premise and a conclusion. Example.

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CS 584

CS 584. Logic. The art of thinking and reasoning in strict accordance with the limitations and incapacities of the human misunderstanding. The basis of logic is the syllogism, consisting of a major and minor premise and a conclusion. Example.

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Boundary Element Analysis at Caterpillar

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Co-Processor Architectures Fermi vs. Knights Ferry

Co-Processor Architectures Fermi vs. Knights Ferry. Roger Goff Dell Senior Global CERN/LHC Technologist +1.970.672.1252 | Roger_Goff@dell.com. nVidia Fermi Architecture. Up to 512 cores 16 Streaming multiprocessors each with 32 cores @ 1.3GHz Parallel DataCache 64 KB Shmem/L1 Cache

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Scientific Management

Scientific Management. I. Scientific Management movement A. Leaders B. Principles C. Implementation II. Production in the Progressive Era A. The Divided Economy B. The Labor Problem C. Progressive Values III. Issues A. Breakdown of craft B. Restructuring of pay

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Hadoop-Harp Applications Performance Analysis on Big Red II

Hadoop-Harp Applications Performance Analysis on Big Red II. Notes. For K-Means Clustering and FR Graph Drawing Algorithm, I use execution time and speedup to explain the performance because T hey can be drawn in one picture.

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