'Cache blocking' diaporamas de présentation

Automatic Performance Tuning and Sparse-Matrix-Vector-Multiplication (SpMV)

Automatic Performance Tuning and Sparse-Matrix-Vector-Multiplication (SpMV). James Demmel www.cs.berkeley.edu/~demmel/cs267_Spr09. Berkeley Benchmarking and OPtimization (BeBOP). Prof. Katherine Yelick Current members

2.91k views • 267 slides

BeBOP: Berkeley Benchmarking and Optimization Automatic Performance Tuning of Numerical Kernels

BeBOP: Berkeley Benchmarking and Optimization Automatic Performance Tuning of Numerical Kernels. James Demmel EECS and Math UC Berkeley. Katherine Yelick EECS UC Berkeley. Support from DOE SciDAC, NSF, Intel. Performance Tuning Participants. Faculty

935 views • 93 slides

High Performance Information Retrieval and MEMS CAD on Intel Itanium

High Performance Information Retrieval and MEMS CAD on Intel Itanium. James Demmel Mathematics and EECS UC Berkeley www.cs.berkeley.edu/~demmel/Itanium_111201.ppt Joint work with David Culler, Michael Jordan, William Kahan, Katherine Yelick, Zhaojun Bai (UC Davis).

762 views • 76 slides

Automatic Performance Tuning of Sparse Matrix Kernels

Automatic Performance Tuning of Sparse Matrix Kernels. Berkeley Benchmarking and OPtimization (BeBOP) Project http://www.cs.berkeley.edu/~richie/bebop James Demmel, Katherine Yelick Richard Vuduc, Shoaib Kamil, Rajesh Nishtala, Benjamin Lee Atilla Gyulassy, Chris Hsu

852 views • 72 slides

Automatic Performance Tuning of Sparse Matrix Kernels

Automatic Performance Tuning of Sparse Matrix Kernels. Berkeley Benchmarking and OPtimization (BeBOP) Project http://www.cs.berkeley.edu/~richie/bebop James Demmel, Katherine Yelick Richard Vuduc, Shoaib Kamil, Rajesh Nishtala, Benjamin Lee Atilla Gyulassy, Chris Hsu

812 views • 67 slides

Memory Hierarchies and Optimizations: Case Study in Matrix Multiplication

1.06k views • 45 slides

Bandwidth Avoiding Stencil Computations

Bandwidth Avoiding Stencil Computations. By Kaushik Datta , Sam Williams, Kathy Yelick, and Jim Demmel, and others Be rkeley B enchmarking and Op timization Group UC Berkeley March 13, 2008 http://bebop.cs.berkeley.edu kdatta@cs.berkeley.edu. Outline. Stencil Introduction

429 views • 40 slides

Optimizing the Performance of Sparse Matrix-Vector Multiplication

Optimizing the Performance of Sparse Matrix-Vector Multiplication. Eun-Jin Im U.C.Berkeley. Overview. Motivation Optimization techniques Register Blocking Cache Blocking Multiple Vectors Sparsity system Related Work Contribution Conclusion. Motivation : Usage.

650 views • 38 slides

Optimizing the Performance of Sparse Matrix-Vector Multiplication

Optimizing the Performance of Sparse Matrix-Vector Multiplication. Eun-Jin Im U.C.Berkeley. Overview. Motivation Optimization techniques Register Blocking Cache Blocking Multiple Vectors Sparsity system Related Work Contribution Conclusion. Motivation : Usage.

430 views • 38 slides

Implicit and Explicit Optimizations for Stencil Computations

Implicit and Explicit Optimizations for Stencil Computations. Shoaib Kamil 1,2 , Kaushik Datta 1 , Samuel Williams 1,2 , Leonid Oliker 1,2 , John Shalf 2 and Katherine A. Yelick 1,2 1 University of California, Berkeley 2 Lawrence Berkeley National Laboratory. What are stencil codes?.

530 views • 34 slides

Benchmarking Sparse Matrix-Vector Multiply In 5 Minutes

Benchmarking Sparse Matrix-Vector Multiply In 5 Minutes. Hormozd Gahvari, Mark Hoemmen, James Demmel, and Kathy Yelick January 21, 2007. Outline. What is Sparse Matrix-Vector Multiply (SpMV)? Why benchmark it? How to benchmark it? Past approaches Our approach Results

569 views • 31 slides

When Cache Blocking of Sparse Matrix Vector Multiply Works and Why

When Cache Blocking of Sparse Matrix Vector Multiply Works and Why. By Rajesh Nishtala, Richard W. Vuduc, James W. Demmel, and Katherine A. Yelick BeBOP Project, U.C. Berkeley June, 2004 http://bebop.cs.berkeley.edu rajeshn@eecs.berkeley.edu. General Approach.

211 views • 20 slides

Mesh Generation and Load Balancing

Mesh Generation and Load Balancing. Stan Tomov Innovative Computing Laboratory Computer Science Department The University of Tennessee March 11, 2009. CS 594 03/11/2009. Outline. Motivation Reliable & efficient PDE simulations for high end computing systems Background

325 views • 19 slides

Mesh Generation and Load Balancing

Mesh Generation and Load Balancing. Stan Tomov Innovative Computing Laboratory Computer Science Department The University of Tennessee March 11, 2009. CS 594 03/11/2009. Outline. Motivation Reliable & efficient PDE simulations for high end computing systems Background

199 views • 19 slides

Enduring Linear Algebra Software Libraries

Enduring Linear Algebra Software Libraries. Fred Gustavson Adjunct Prof. Umea U. Umea, Sweden IBM Research, Emeritus, Ykt. Hgts., NY E-mail: fg2935@hotmail.com.

280 views • 14 slides