'Simd instructions' diaporamas de présentation

Topic 4 Processor Performance

Topic 4 Processor Performance. AH Computing. Introduction. 6502 8 bit processor, 16 bit address bus Intel8086/88 (1979) IBM PC 16-bit data and address buses Motorola 68000 16-bit data and 24-bit address PowerPC (1992) Incorporated pipelining and superscaling. 8086. Introduction.

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CS 61C: Great Ideas in Computer Architecture SIMD II

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Instructor: Justin Hsia

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Android* on Intel platforms

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Native Signal Processing

Native Signal Processing. Ravi Bhargava Laboratory of Computer Architecture Electrical and Computer Engineering Department The University of Texas at Austin November 22, 1999. Motivation. Need new ways to support emerging applications Multimedia Signal processing 3D graphics

436 views • 28 slides

Native Signal Processing

Native Signal Processing. Ravi Bhargava Laboratory of Computer Architecture Electrical and Computer Engineering Department The University of Texas at Austin November 22, 1999. Motivation. Need new ways to support emerging applications Multimedia Signal processing 3D graphics

398 views • 28 slides

An Analysis of SIMD Instructions in the Pentium III Microprocessor

An Analysis of SIMD Instructions in the Pentium III Microprocessor. By Alexander J. Aved <aaved@cs.bsu.edu> 05 DEC 2000. CS689 Ball State University Muncie, Indiana. TOC. Problem Description Problem Statement Research Objectives Literature Review Importance Research Design

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Automatic Tuning Matrix Multiplication Performance on Graphics Hardware

Automatic Tuning Matrix Multiplication Performance on Graphics Hardware. Changhao Jiang (cjiang@cs.uiuc.edu) Marc Snir (snir@cs.uiuc.edu) University of Illinois Urbana Champaign. GPU becomes more powerful. NVIDIA GeForceFX 7800. 3.0 GHz dual-core Pentium4.

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Mauricio Breternitz Jr, Herbert Hum, Sanjeev Kumar Microprocessor Research Labs,

Compilation, Architectural Support, and Evaluation of SIMD Graphics Pipeline Programs on a General-Purpose CPU. Mauricio Breternitz Jr, Herbert Hum, Sanjeev Kumar Microprocessor Research Labs, Intel Corporation. Graphics Applications.

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Heterogeneous Computing in Charm++

Heterogeneous Computing in Charm++. David Kunzman. Motivations. Performance and Popularity of Accelerators Our work currently focuses on Cell (and Larrabee) Difficult to program accelerators Architecture specific code (not portable) Many asynchronous events (data movement, multiple cores)

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Platform based design

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