'Matrix multiply' presentation slideshows

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

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

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Recursion Unrolling for Divide and Conquer Programs

Recursion Unrolling for Divide and Conquer Programs. Radu Rugina and Martin Rinard Laboratory for Computer Science Massachusetts Institute of Technology. What This Talk Is About. Automatic generation of efficient large base cases for divide and conquer programs. Outline.

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CS 61C: Great Ideas in Computer Architecture (formerly called Machine Structures) Map Reduce

CS 61C: Great Ideas in Computer Architecture (formerly called Machine Structures) Map Reduce. Instructor: David A. Patterson http://inst.eecs.Berkeley.edu/~cs61c/sp12. Review.

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ECE 1747H: Parallel Programming

ECE 1747H: Parallel Programming. Lecture 2-3: More on parallelism and dependences -- synchronization. Synchronization. All programming models give the user the ability to control the ordering of events on different processors. This facility is called synchronization. Example 1.

688 views • 57 slides

Linear Filters in StreamIt

Linear Filters in StreamIt. Andrew A. Lamb MIT Laboratory for Computer Science Computer Architecture Group 8/29/2002. Outline. Introduction Dataflow Analysis Hierarchal Matrix Combinations Performance Optimizations. Basic Idea. Filter A a=pop(); b=pop(); c=(a+b)/2 + 1; push(c);.

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Cache Memories

Cache Memories. CS213. Topics Generic cache memory organization Direct mapped caches Set associative caches Impact of caches on performance. Cache Memories. Cache memories are small, fast SRAM-based memories managed automatically in hardware.

629 views • 40 slides

Advancing Computer Systems without Technology Progress

Advancing Computer Systems without Technology Progress. ISAT Outbrief , April 17-18, of DARPA/ISAT Workshop, March 26-27, 2012 Organized by: Mark Hill & Christos Kozyrakis w/ Serena Chan & Melanie Sineath

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Libraries and Program Performance

Libraries and Program Performance. NERSC User Services Group. An Embarrassment of Riches: Serial. Threaded Libraries (Threaded). Parallel Libraries (Distributed & Threaded). Elementary Math Functions. Three libraries provide elementary math functions: C/Fortran intrinsics

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In the News

In the News. Facebook gets OK to build 'Burger Shack' and 'BBQ House' at Menlo Park campus.

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Numerical Linear Algebra An Introduction

Numerical Linear Algebra An Introduction. Levels of multiplication . vector-vector a[i]*b[i] matrix-vector A[i,j]*b[j] matrix-matrix A[I,k]*B[k,j]. Matrix-Matrix. for (i=0; i<n; i++) for (j=0; j<n; j++) { C[i,j]=0.0; for (k=0; k<n; k++)

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CS 240A : Linear Algebra in Shared Memory with Cilk ++

CS 240A : Linear Algebra in Shared Memory with Cilk ++. Matrix-matrix multiplication Matrix-vector multiplication Hyperobjects. Thanks to Charles E. Leiserson for some of these slides. Square-Matrix Multiplication. b n1. b 21. b 11. a n1. a 21. a 11. c 11. c 21. c n1.

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CS 140 : Numerical Examples on Shared Memory with Cilk++

CS 140 : Numerical Examples on Shared Memory with Cilk++. Matrix-matrix multiplication Matrix-vector multiplication. Thanks to Charles E. Leiserson for some of these slides. Work and Span (Recap). T P = execution time on P processors. T 1 = work. T ? = span *.

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Optimizing for the Memory Hierarchy

Optimizing for the Memory Hierarchy. Systems I. Topics Impact of caches on performance Memory hierarchy considerations. Cache Performance Metrics. Miss Rate Fraction of memory references not found in cache (misses/references) Typical numbers: 3-10% for L1

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Code Optimization II CS429: Computer Organization, Architecture & Programming

Code Optimization II CS429: Computer Organization, Architecture & Programming . Haran Boral. Cache Performance Metrics. Miss Rate Fraction of memory references not found in cache (misses/references) Typical numbers: 3-10% for L1

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Formal Diagnosis of Hardware Transient Errors in Programs

Formal Diagnosis of Hardware Transient Errors in Programs. Layali Rashid , Karthik Pattabiraman and Sathish Gopalakrishnan The Electrical and Computer Engineering Department The University of British Columbia. Contributions. Software-driven diagnosis of hardware transient errors

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Sparse Matrix Solvers on the GPU: Conjugate Gradients and Multigrid

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Munin

Presented by Evan Yang. Munin. Overview of Munin. Distributed shared memory (DSM) system Unique features Multiple consistency protocols Release consistency Annotate data items according to how they are shared Implemented on the V kernel. Review.

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Writing Cache Friendly Code

Writing Cache Friendly Code. Two major rules: Repeated references to data are good ( temporal locality ) Stride-1 reference patterns are good ( spatial locality ). Slides derived from those by Randy Bryant. Writing Cache Friendly Code. Two major rules:

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Programming assignment

Programming assignment. You need to implement the following: Display basic mesh Information Find the number of vertices, edges, faces, boundaries, and compute Euler characteristic and number of genus Corresponding to function Mesh::DisplayMeshInfo() Compute normal at each vertex

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