'Work stealing' diaporamas de présentation

Laboratoire Informatique de Grenoble

Laboratoire Informatique de Grenoble. Parallel algorithms and scheduling: adaptive parallel programming and applications. Bruno Raffin, Jean-Louis Roch, Denis Trystram Projet MOAIS [ INRIA / CNRS / INPG / UJF ] moais.imag.fr.

1.21k views • 93 slides

Overview

Parallel Algorithms Design and Implementation Jean-Louis.Roch at imag.fr MOAIS / Lab. Informatique Grenoble, INRIA , France. Overview. Machine model and work-stealing Work and depth Fundamental theorem : Work-stealing theorem Parallel divide & conquer Examples Accumulate

866 views • 70 slides

The ConCert Project Peter Lee Carnegie Mellon University

The ConCert Project Peter Lee Carnegie Mellon University. MRG Workshop May 2002. ConCert Project. Collaborators Karl Crary Robert Harper Peter Lee Frank Pfenning Began in fall of 2001. Peter Lee. ConCert project

747 views • 59 slides

Parallel Programming with Swan

701 views • 57 slides

Overview

Processor-oblivious parallel algorithms with provable performances - Applications Jean-Louis Roch Lab. Informatique Grenoble, INRIA , France. Overview. Introduction : interactive computation, parallelism and processor oblivious Overhead of parallelism : parallel prefix

722 views • 52 slides

Computer Systems Principles Concurrency Patterns

Computer Systems Principles Concurrency Patterns. Emery Berger and Mark Corner University of Massachusetts Amherst. Web Server. web server. Client (browser) Requests HTML, images Server Caches requests Sends to client. not found. http://server/Easter-bunny/ 200x100/75.jpg. client.

558 views • 47 slides

Dynamic Load Balancing

Dynamic Load Balancing. Rashid Kaleem and M Amber Hassaan. Scheduling for parallel processors. Story so far Machine model: PRAM Program representation control-flow graph basic blocks are DAGs nodes are tasks (arithmetic or memory ops) weight on node = execution time of task

666 views • 45 slides

SimMatrix: SIMulator for MAny -Task computing execution fabRIc at eXascales

SimMatrix: SIMulator for MAny -Task computing execution fabRIc at eXascales. Ke Wang Data-Intensive Distributed Systems Laboratory Computer Science Department Illinois Institute of Technology February 14 th , 2012. Acknowledgements. DataSys Laboratory Dr. Ioan Raicu

593 views • 44 slides

A Survey on Scheduling Methods of Task-Parallel Processing

A Survey on Scheduling Methods of Task-Parallel Processing. Chikayama and Taura Lab M1 48-096415 Jun Nakashima. Agenda. Introduction Basic Scheduling Methods Challenges and solutions Consideration Summary. Motivation. Thread and task have many in common Both are unit of execution

523 views • 41 slides

Next Generation Job Management System for Extreme Scales

Next Generation Job Management System for Extreme Scales. Speaker: Ke Wang Advisor: Ioan Raicu Datasys Lab, Illinois Institute of Technology November 25 th , 2013 at Datasys Mini-Workshop, Fall 2013. Contents.

585 views • 41 slides

15-853:Algorithms in the Real World

15-853:Algorithms in the Real World. Parallelism: Lecture 4 Dynamic Programming Scheduling. Edit Distance: Dynamic Programming. B. Note: can be filled in any order as long as the cells to the left and above are filled. Can follow path back through matrix to construct edits. insert.

315 views • 31 slides

moais.imag.fr

383 views • 27 slides

Adaptive, hybrids, oblivious : what do those terms mean ?

382 views • 27 slides

Atlas: An Infrastructure for Global Computing

Atlas: An Infrastructure for Global Computing. People. Eric Baldeschwieler (UC Berkeley) Bobby Blumofe (UT Austin) Eric Brewer (UC Berkeley). Outline. Introduction Programming model Architecture Examples Discussion Limitations & Conclusion. Introduction.

323 views • 25 slides

Atlas: An Infrastructure for Global Computing

Atlas: An Infrastructure for Global Computing. People. Eric Baldeschwieler (UC Berkeley) Bobby Blumofe (UT Austin) Eric Brewer (UC Berkeley). Outline. Introduction Programming model Architecture Examples Discussion Limitations & Conclusion. Introduction.

259 views • 25 slides

The Implementation of the Cilk-5 Multithreaded Language (Frigo, Leiserson, and Randall)

The Implementation of the Cilk-5 Multithreaded Language (Frigo, Leiserson, and Randall). Alistair Dundas Department of Computer Science University of Massachusetts. Outline. What is Cilk? Cilk example: the Fibonacci algorithm. The work-first principle. Work Stealing. The T.H.E. Protocol.

411 views • 24 slides

On-line adaptative parallel prefix computation

On-line adaptative parallel prefix computation. Jean-Louis Roch , Daouda Traore, Julien Bernard INRIA-CNRS Moais team - LIG Grenoble, France. Contents I. Motivation II. Work-stealing scheduling of parallel algorithms III. Processor-oblivious parallel prefix computation.

409 views • 24 slides

Processor-oblivious parallel algorithms and scheduling Illustration on parallel prefix

Processor-oblivious parallel algorithms and scheduling Illustration on parallel prefix. Jean-Louis Roch , Daouda Traore INRIA-CNRS Moais team - LIG Grenoble, France. Contents I. What is a processor-oblivious parallel algorithm ? II. Work-stealing scheduling of parallel algorithms

397 views • 24 slides

Scheduling Multithreaded Computations B y Work-Stealing

Scheduling Multithreaded Computations B y Work-Stealing. Robert D. Blumofe The University of Texas, Austin Charles E. Leiserson , MIT Laboratory for Computer Science. Motivation. Strict binding of multi-threaded computations on parallel computers.

156 views • 15 slides

Work Stealing and Persistence-based Load Balancers for Iterative Overdecomposed Applications

Work Stealing and Persistence-based Load Balancers for Iterative Overdecomposed Applications Jonathan Lifflander, Sriram Krishnamoorthy, Laxmikant V. Kale. Presentation: Session 9: Thursday, June 21 @ 10:20am. Introduction. Persistence-based Load Balancing.

192 views • 1 slides