'Data dependencies' presentation slideshows

Parallel Processing with OpenMP

Parallel Processing with OpenMP. Doug Sondak Boston University Scientific Computing and Visualization Office of Information Technology sondak@bu.edu. Outline. Introduction Basics Data Dependencies A Few More Basics Caveats & Compilation Coarse-Grained Parallelization

1.19k views • 107 slides

Supercomputing in Plain English Stupid Compiler Tricks

Supercomputing in Plain English Stupid Compiler Tricks. PRESENTERNAME PRESENTERTITLE PRESENTERDEPARTMENT PRESENTERINSTITUTION DAY MONTH DATE YEAR. Your Logo Here. Slides by Henry Neeman, University of Oklahoma. Outline. Dependency Analysis What is Dependency Analysis?

1.07k views • 80 slides

ILP, Memory and Synchronization

ILP, Memory and Synchronization. Joseph B. Manzano. Instruction Level Parallelism . Parallelism that is found between instructions Dynamic and Static Exploitation Dynamic: Hardware related. Static: Software related (compiler and system software) VLIW and Superscalar

731 views • 68 slides

Topics

Topics. Basics of register-transfer design: data paths and controllers. High-level synthesis. Register-transfer design. A register-transfer system is a sequential machine.

634 views • 42 slides

Randal E. Bryant

CS:APP Chapter 4 Computer Architecture Pipelined Implementation Part II. Randal E. Bryant. Carnegie Mellon University. http://csapp.cs.cmu.edu. CS:APP2e. Overview. Make the pipelined processor work! Data Hazards

569 views • 41 slides

CS 6461: Computer Architecture Instruction Level Parallelism

CS 6461: Computer Architecture Instruction Level Parallelism. Instructor: M. Lancaster Corresponding to Hennessey and Patterson Fifth Edition Section 3.1. Instruction Level Parallelism.

596 views • 41 slides

Data/Thread Level Speculation (TLS) in the Stanford Hydra Chip Multiprocessor (CMP)

Data/Thread Level Speculation (TLS) in the Stanford Hydra Chip Multiprocessor (CMP).

482 views • 39 slides

Superscalar Processor

Superscalar Processor. Abdullah A Alasmari & Eid S. Alharbi. Outlines. Pipeline & Hazards Superscalar Instruction issue policy Register renaming MIPS R10000 Advanced Superscalar Summary. Pipeline & Hazards.

692 views • 39 slides

Pipelined Implementation Part I

Pipelined Implementation Part I. Overview. General Principles of Pipelining Goal Difficulties Creating a Pipelined Y86 Processor Rearranging SEQ Inserting pipeline registers Problems with data and control hazards. Idea Divide process into independent stages

532 views • 31 slides

Lecture Notes Taken from Slides of Randal E. Bryant

CS:APP Chapter 4 Computer Architecture Pipelined Implementation Part I. Lecture Notes Taken from Slides of Randal E. Bryant. CS:APP. Overview. General Principles of Pipelining Goal: Enhancing Performance Difficulties: Complex implementation, Non-deterministic behavior etc.

387 views • 31 slides

Data Dependencies

Data Dependencies Describes the normal situation that the data that instructions use depend upon the data created by other instructions, or data is stored in locations used by other instructions. Three types of data dependency between instructions, True data dependency Antidependency

799 views • 30 slides

Visual Programming Languages ICS 519 Paradigms

Visual Programming Languages ICS 519 Paradigms. ICS Department KFUPM Feb. 1, 2005. Paradigms. Imperative Languages: The features (Von Neumann architecture) are: Variables

383 views • 23 slides

Presented by Brian J. Greenberg briangreenberg bjg@acm

301 views • 22 slides

Pipelining

436 views • 20 slides

ITCS 4/5010 CUDA Programming, UNC-Charlotte, B. Wilkinson, March 13A, 2013, OpenACC

351 views • 19 slides

Computer Architecture Principles Dr. Mike Frank

Computer Architecture Principles Dr. Mike Frank. CDA 5155 Summer 2003 Module #18 Scheduling: Basic Static Scheduling & Loop Unrolling, Intro. To Dyn. Sched. Scheduling, Part I. Basic Scheduling Concepts Loop Unrolling. Basic Pipeline Scheduling.

302 views • 19 slides

Shawn Bowers Timothy McPhillips Bertram Ludaescher in collaboration with Ilkay Altintas

258 views • 15 slides

Pipelining(2)

CDA 3101 Discussion Section 09. Pipelining(2). Question 1. Identify all of the data dependencies and necessary forwarding in the following code. No branch prediction, No Delayed Slot. addi $t1,$0,0 addi $t2,$0,100 LOOP: lw $t4, 200($t2) add $t1, $t1, $t4 addi $t2, $t2, -4

232 views • 11 slides

Sources of Constraints in Computations

g. f. r(x). x. p2. h. p1. Sources of Constraints in Computations. Data dependencies in the computation Timing properties of the individual computations Number and kind of components are connected Constraints on the control structure Suppose we want to compute

260 views • 9 slides

Sources of Constraints in Computations

g. f. r(x). x. p2. h. p1. Sources of Constraints in Computations. Data dependencies in the computation Timing properties of the individual computations Number and kind of components are connected Constraints on the control structure Suppose we want to compute

225 views • 9 slides