'Data dependency' diaporamas de présentation

Supercomputing and Science

Supercomputing and Science. An Introduction to High Performance Computing Part IV: Dependency Analysis and Stupid Compiler Tricks Henry Neeman, Director OU Supercomputing Center for Education & Research. Outline. Dependency Analysis What is Dependency Analysis? Control Dependencies

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Different parallel processing architectures

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High Performance Computing

High Performance Computing. Introduction to classes of computing SISD MISD SIMD MIMD Conclusion. Classes of computing. Computation Consists of : Sequential Instructions (operation) Sequential dataset We can then abstractly classify into following classes of computing

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Different parallel processing architectures

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CSCE 230, Fall 2013 Chapter 6: Pipelining

Mehmet Can Vuran , Instructor University of Nebraska-Lincoln. CSCE 230, Fall 2013 Chapter 6: Pipelining. Acknowledgement: Overheads adapted from those provided by the authors of the textbook. Chapter Outline. Pipelining: overlapped instruction execution

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CSE 8383 - Advanced Computer Architecture

CSE 8383 - Advanced Computer Architecture. Week-3 Week of Jan 26, 2004 engr.smu.edu/~rewini/8383. Contents. Linear Pipelines Nonlinear pipelines Instruction Pipelines Arithmetic Operations Design of Multifunction Pipeline. Linear Pipeline. Processing Stages are linearly connected

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Wen-Hsiao Peng Chun-Chi Chen

An Inter-Frame Prediction Technique Combining Template Matching Prediction and Block Motion Compensation for High Ef?ciency Video Coding. Circuits and Systems for Video Technology, 2013 IEEE Transactions on . Wen-Hsiao Peng Chun-Chi Chen. Outline. Introduction Background

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Threads

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COMP 630E Group Project

COMP 630E Group Project. An Illustration of Data Dependencies. Group 2. Ko Wai Sun, Eric Leung Cheuk Yung, Victor Ng Ching Yu, Cedric Wong Yee Man, Shirley. Outline. The Example Functional Dependency (FD) Inclusion Dependency (IND) Multivalued Dependency (MVD)

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Hongtao Du

Hongtao Du. AICIP Research Mar 9, 2006. Motivation. Image processing Complicated algorithms Large data sets Pipelined and parallel computing Speedup? Not Necessary! Solution: Efficiently Allocate process Distribute data. Outline. Pipelined and parallel computing overview

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Highly Parallel Framework for HEVC Motion Estimation on Many-core Platform

Data Compression Conference 2013. Highly Parallel Framework for HEVC Motion Estimation on Many-core Platform. Chenggang Yan, Yongdong Zhang, Feng Dai and Liang Li. Outline. Introduction Related Work Proposed Method Experimental Results Conclusion. Introduction (1/2). HEVC

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A new exact test to globally assess a population PK and/or PD model C. Laffont & D. Concordet

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Introduction to Pipelining

Introduction to Pipelining. Adapted from the lecture notes of Dr. John Kubiatowicz (UC Berkeley). A. B. C. D. Pipelining is Natural!. Laundry Example Ann, Brian, Cathy, Dave each have one load of clothes to wash, dry, and fold Washer takes 30 minutes Dryer takes 40 minutes

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Highly Parallel Mode Decision Method for HEVC

Highly Parallel Mode Decision Method for HEVC. Jun Zhang, Feng Dai, Yike Ma, and Yongdong Zhang. Picture Coding Symposium (PCS), 2013. Outline. Introduction Data dependency analysis and removing Proposed method Implementation and results Conclusion. Introduction #1.

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Computer Architecture

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Data Management in Cloud Workflow Systems Dong Yuan

Data Management in Cloud Workflow Systems Dong Yuan Faculty of Information and Communication Technology Swinburne University of Technology. Outline. Cloud Computing & Cloud Workflow Systems Introduction to cloud workflow systems. A brief overview of grid workflow systems.

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L8 : A Survey on Low Power Multiplication / Accumulation

L8 : A Survey on Low Power Multiplication / Accumulation. Contents. Introduction [1] Interlaced Accumulation Programming [2] Operand Swapping [3] Selective Coefficient Negation [4] Coefficient Optimization [5] Coefficient Reordering Conclusion & Future Works. Power Distribution of a DSP.

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ADG: Annotated Dependency Graphs

ADG: Annotated Dependency Graphs. Ahmed Hassan and Richard Holt. University Of Waterloo, Canada. Motivating Example. A Year Later. ??!. ??!. Unexpected Dependencies. What? New data dependency New functional dependency Why? Is it a bug fix? Developer laziness / ignorance? When?

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Real-Time Multi-core Scheduling With Power, Thermal And Reliability Awareness

Real-Time Multi-core Scheduling With Power, Thermal And Reliability Awareness. Advanced Real-time and Computing Systems (ARCS) Lab Electrical and Computer Engineering Florida International University. Ming Fan. Problem Formulation.

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