'Vector register' diaporamas de présentation

Unit-5: Cocurrent Processors

Unit-5: Cocurrent Processors. Vector & Multiple Instruction Issue Processors. Concurrent Processors. Processors that can execute multiple instructions at the same time ( Concurrently)

1.23k views • 106 slides

Problems with Superscalar approach

Problems with Superscalar approach. Limits to conventional exploitation of ILP: 1) Pipelined clock rate : Each increase in clock rate has corresponding CPI increase (branches, other hazards). (pipeline latency)

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CS252 Graduate Computer Architecture Lecture 10 Vector Processing (Continued) Branch Prediction

CS252 Graduate Computer Architecture Lecture 10 Vector Processing (Continued) Branch Prediction. October 4, 2000 Prof. John Kubiatowicz. Review: Vector Processing. Vector Processing represents an alternative to complicated superscalar processors. Primitive operations on large vectors of data

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Data-Level Parallelism in Vector and GPU Architectures

Data-Level Parallelism in Vector and GPU Architectures. Muhamed Mudawar Computer Engineering Department King Fahd University of Petroleum and Minerals. Introduction. SIMD architectures can exploit significant data-level parallelism for: matrix-oriented scientific computing

1.25k views • 61 slides

777 views • 60 slides

Problems with Superscalar approach

Problems with Superscalar approach. Limits to conventional exploitation of ILP: 1) pipelined clock rate : at some point, each increase in clock rate has corresponding CPI increase (branches, other hazards)

668 views • 59 slides

Vector Computers

Vector Computers. Muhamed Mudawar Computer Engineering Department King Fahd University of Petroleum and Minerals. SCALAR (1 operation). VECTOR (N operations). v2. v1. r2. r1. +. +. r3. v3. vector length. addv v3, v1, v2. add r3, r1, r2. Vector Processing.

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EE (CE) 6304 Computer Architecture Lecture #18 (11/29/17)

EE (CE) 6304 Computer Architecture Lecture #18 (11/29/17). Yiorgos Makris Professor Department of Electrical Engineering University of Texas at Dallas. Course Web-site: http://www.utdallas.edu/~gxm112130/EE6304FA17. Supercomputers. Definition of a supercomputer:

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Multiprocessors

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CS252 Graduate Computer Architecture Lecture 12 Vector Processing

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Vector Processing

Vector Processing. Ben Helmer Matt Sagerstrand Daniel Yingling. EARLY VECTOR PROCESSING. Vector Processing was used in supercomputers of the 1970's.

1.68k views • 33 slides

A. Sazegari AltiVec Technical Lead

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EECS 252 Graduate Computer Architecture Lec. 12: Vector Computers

EECS 252 Graduate Computer Architecture Lec. 12: Vector Computers. Krste Asanovic ( krste@mit.edu ) Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Definition of a supercomputer: Fastest machine in world at given task

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Asanovic/DevadasSpring 2002 6.823

Asanovic/DevadasSpring 2002 6.823. Vector Computers. Krste Asanovic Laboratory for Computer Science Massachusetts Institute of Technology. Asanovic/DevadasSpring 2002 6.823. Supercomputers. Definition of a supercomputer: Fastest machine in world at given task Any machine costing $30M+

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CPE 631: Vector Processing

CPE 631: Vector Processing. Electrical and Computer Engineering University of Alabama in Huntsville Aleksandar Milenkovi? milenka@ece.uah.edu http://www.ece.uah.edu/~milenka. Outline. Properties of Vector Processing Components of a Vector Processor Vector Execution Time

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CPE 631 Lecture 24: Vector Processing

CPE 631 Lecture 24: Vector Processing. Aleksandar Milenkovi ? , milenka@ece.uah.edu Electrical and Computer Engineering University of Alabama in Huntsville. Outline. Properties of Vector Processing Components of a Vector Processor Vector Execution Time

319 views • 31 slides

Vector Optimizations

Vector Optimizations. Sam Williams CS 265 samw@cs.berkeley.edu. Topics. Introduction to vector architectures Overview of data dependence analysis Loop transformations Other optimizations. Introduction. Goal is to exploit the processing capabilities of vector machines. e.g. Transform.

450 views • 30 slides

Vector Optimizations

Vector Optimizations. Sam Williams CS 265 samw@cs.berkeley.edu. Topics. Introduction to vector architectures Overview of data dependence analysis Loop transformations Other optimizations. Introduction. Goal is to exploit the processing capabilities of vector machines. e.g. Transform.

310 views • 30 slides

Krste Asanovic Electrical Engineering and Computer Sciences University of California at Berkeley

156 views • 15 slides