Load Balancing & Termination

Size: px
Start display at page:

Download "Load Balancing & Termination"

Transcription

1 Load Load & Termination Lecture 7 Load and Termination Detection

2 Load Load Want all processors to operate continuously to minimize time to completion. Load balancing determines what work will be done by which processor. Static Dynamic Lecture 7 Load and Termination Detection

3 Load Approaches already discussed: Round Robin Random Recursive Bisection Simulated Annealing Genetic Algorithm Lecture 7 Load and Termination Detection

4 Load Bin Packing for Homogeneous Systems P boxes of equal size Minimize the size of the boxes, s.t. every piece of work goes in one and only one box the work in any given box will be assigned to one processor put work that requires the most communication on the same processor if possible Lecture 7 Load and Termination Detection

5 Load Let s take a very simple example 2 homogeneous processors 8 homogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 300 How close can we come to perfect load balance? Lecture 7 Load and Termination Detection

6 Load Extend our example w/communication 2 homogeneous processors 8 homogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 300 Does the communication change how good we can make our load balance? Lecture 7 Load and Termination Detection

7 Load Extend example w/more communication 2 homogeneous processors 8 homogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 Lecture 7 Load and Termination Detection 300 big yellow blue means lots of communication Does the communication change our total runtime and/or balance?

8 Load 300 Extend example w/more communication 2 homogeneous processors 8 homogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 Here the communication changed our total runtime and/or balance. Lecture 7 Load and Termination Detection big big yellow blue means lots lots of of communication

9 Load Bin Packing for Heterogeneous Systems P boxes of variable size representing the capability of the associated processor relative to the total capability of the system Minimize the imbalance, s.t. every piece of work goes in one and only one box put work that requires the most communication on the same processor if possible each box is the same % full Lecture 7 Load and Termination Detection

10 Load Let s extend our example 2 heterogeneous processors 8 homogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 How do heterogeneous processors change what we do? Lecture 7 Load and Termination Detection

11 Load Let s extend our example 2 homogeneous processors 8 heterogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 How do heterogeneous meshes change what we do? Lecture 7 Load and Termination Detection

12 Load Let s extend our example 2 heterogeneous processors 8 heterogeneous meshes with sizes 15x10 11x3 10x10 8x10 9x9 8x9 7x7 6x6 How do heterogeneous meshes and processors change what we do? Lecture 7 Load and Termination Detection

13 Load Problems with How do we know for sure what the computation per mesh element is? How do we know for sure what the capabilities of each processor will be? How do we know what the load on each processor will be (shared resources)? Similar questions for the communication... Given these questions may be impossible to answer for some problems, we move to dynamic load balancing. Lecture 7 Load and Termination Detection

14 Load Approaches to Balance Centralized a master process hold the collection of tasks to perform and determines when the job is complete Distributed the tasks are distributed and the decision process for determining termination is distributed Lecture 7 Load and Termination Detection

15 Load Centralized Balance How can we improve on this process? Lecture 7 Load and Termination Detection

16 Load Distributed Balance How can we improve on this process? Lecture 7 Load and Termination Detection

17 Load Distributed Balance processes transferring tasks Lecture 7 Load and Termination Detection

18 Load Distributed Balance processes transferring tasks How selected? Lecture 7 Load and Termination Detection

19 Load Distributed Balance processes transferring tasks How selected? Lecture 7 Load and Termination Detection

20 Load Distributed Balance Multiple threads for Lecture 7 Load and Termination Detection

21 Load Recognition of termination conditions for distributed computations is more difficult than sequential termination. Conditions [Bertsekas & Tsitsiklis, 89] local termination reached by all no communication in progress Lecture 7 Load and Termination Detection

22 Load Bertsekas & Tsitsiklis Lecture 7 Load and Termination Detection

23 Load Single-Pass Ring Termination Lecture 7 Load and Termination Detection

24 Load Dual-pass Ring Termination Dijkstra, Feijen, and Gasteren 1983 Lecture 7 Load and Termination Detection

25 Load Dual-pass Ring Termination Dijkstra, Feijen, and Gasteren 1983 Lecture 7 Load and Termination Detection

26 Load Fixed Energy Termination Start with all energy assigned to the master Send a bit of energy with each task assigned Return the energy when the task is finished When all energy is returned to the master and it has no more work to farm out, termination has been reached. Lecture 7 Load and Termination Detection

27 Load Phase Parallelism C C C C Synchronous Interaction C C C C Synchronous Interaction ideallecture 7 Load and Termination Detection

28 Load C C C C Phase Parallelism C Synchronous Interaction C C C real Synchronous Interaction Lecture 7 Load and Termination Detection

29 Load Divide and Conquer C C C C C C C C C ideal C Lecture 7 Load and Termination Detection

30 Load Divide and Conquer real C C C C C 3 C C 1 C 2 C C Lecture 7 Load and Termination Detection

31 Load P Q Pipelined ideal R Z Lecture 7 Load and Termination Detection

32 Load P Q Pipelined real R Z Lecture 7 Load and Termination Detection

33 Load Master Slave Master S S S S ideal Lecture 7 Load and Termination Detection

34 Load Master Slave real S S Master S S Lecture 7 Load and Termination Detection

35 Load Work Pool Work Pool P Q R Z ideal Lecture 7 Load and Termination Detection

36 Load Work Pool P Q Work Pool R Z real Lecture 7 Load and Termination Detection

37 Load Load Centralized Distributed Termination Paradigms phase pipelined master slave work pool Static Dynamic Lecture 7 Load and Termination Detection

Load Balancing Techniques

Load Balancing Techniques Load Balancing Techniques 1 Lecture Outline Following Topics will be discussed Static Load Balancing Dynamic Load Balancing Mapping for load balancing Minimizing Interaction 2 1 Load Balancing Techniques

More information

Load balancing Static Load Balancing

Load balancing Static Load Balancing Chapter 7 Load Balancing and Termination Detection Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination detection

More information

Load Balancing and Termination Detection

Load Balancing and Termination Detection Chapter 7 Load Balancing and Termination Detection 1 Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination detection

More information

Chapter 7 Load Balancing and Termination Detection

Chapter 7 Load Balancing and Termination Detection Chapter 7 Load Balancing and Termination Detection Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination detection

More information

Load Balancing and Termination Detection

Load Balancing and Termination Detection Chapter 7 slides7-1 Load Balancing and Termination Detection slides7-2 Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination

More information

Load Balancing and Termination Detection

Load Balancing and Termination Detection Chapter 7 Slide 1 Slide 2 Load Balancing and Termination Detection Load balancing used to distribute computations fairly across processors in order to obtain the highest possible execution speed. Termination

More information

Praktikum Wissenschaftliches Rechnen (Performance-optimized optimized Programming)

Praktikum Wissenschaftliches Rechnen (Performance-optimized optimized Programming) Praktikum Wissenschaftliches Rechnen (Performance-optimized optimized Programming) Dynamic Load Balancing Dr. Ralf-Peter Mundani Center for Simulation Technology in Engineering Technische Universität München

More information

Load balancing; Termination detection

Load balancing; Termination detection Load balancing; Termination detection Parallel and Distributed Computing Department of Computer Science and Engineering (DEI) Instituto Superior Técnico November 14, 2013 CPD (DEI / IST) Parallel and Distributed

More information

Static Load Balancing

Static Load Balancing Load Balancing Load Balancing Load balancing: distributing data and/or computations across multiple processes to maximize efficiency for a parallel program. Static load-balancing: the algorithm decides

More information

Asynchronous Computations

Asynchronous Computations Asynchronous Computations Asynchronous Computations Computations in which individual processes operate without needing to synchronize with other processes. Synchronizing processes is an expensive operation

More information

Partitioning and Divide and Conquer Strategies

Partitioning and Divide and Conquer Strategies and Divide and Conquer Strategies Lecture 4 and Strategies Strategies Data partitioning aka domain decomposition Functional decomposition Lecture 4 and Strategies Quiz 4.1 For nuclear reactor simulation,

More information

Load balancing; Termination detection

Load balancing; Termination detection Load balancing; Termination detection Parallel and Distributed Computing Department of Computer Science and Engineering (DEI) Instituto Superior Técnico November 13, 2014 CPD (DEI / IST) Parallel and Distributed

More information

Load Balancing. Load Balancing 1 / 24

Load Balancing. Load Balancing 1 / 24 Load Balancing Backtracking, branch & bound and alpha-beta pruning: how to assign work to idle processes without much communication? Additionally for alpha-beta pruning: implementing the young-brothers-wait

More information

Performance of Dynamic Load Balancing Algorithms for Unstructured Mesh Calculations

Performance of Dynamic Load Balancing Algorithms for Unstructured Mesh Calculations Performance of Dynamic Load Balancing Algorithms for Unstructured Mesh Calculations Roy D. Williams, 1990 Presented by Chris Eldred Outline Summary Finite Element Solver Load Balancing Results Types Conclusions

More information

Experiments on the local load balancing algorithms; part 1

Experiments on the local load balancing algorithms; part 1 Experiments on the local load balancing algorithms; part 1 Ştefan Măruşter Institute e-austria Timisoara West University of Timişoara, Romania maruster@info.uvt.ro Abstract. In this paper the influence

More information

LOAD BALANCING TECHNIQUES

LOAD BALANCING TECHNIQUES LOAD BALANCING TECHNIQUES Two imporatnt characteristics of distributed systems are resource multiplicity and system transparency. In a distributed system we have a number of resources interconnected by

More information

A number of tasks executing serially or in parallel. Distribute tasks on processors so that minimal execution time is achieved. Optimal distribution

A number of tasks executing serially or in parallel. Distribute tasks on processors so that minimal execution time is achieved. Optimal distribution Scheduling MIMD parallel program A number of tasks executing serially or in parallel Lecture : Load Balancing The scheduling problem NP-complete problem (in general) Distribute tasks on processors so that

More information

Study of Various Load Balancing Techniques in Cloud Environment- A Review

Study of Various Load Balancing Techniques in Cloud Environment- A Review International Journal of Computer Sciences and Engineering Open Access Review Paper Volume-4, Issue-04 E-ISSN: 2347-2693 Study of Various Load Balancing Techniques in Cloud Environment- A Review Rajdeep

More information

Job Scheduling Model

Job Scheduling Model Scheduling 1 Job Scheduling Model problem scenario: a set of jobs needs to be executed using a single server, on which only one job at a time may run for theith job, we have an arrival timea i and a run

More information

Spring 2011 Prof. Hyesoon Kim

Spring 2011 Prof. Hyesoon Kim Spring 2011 Prof. Hyesoon Kim Today, we will study typical patterns of parallel programming This is just one of the ways. Materials are based on a book by Timothy. Decompose Into tasks Original Problem

More information

Comparison on Different Load Balancing Algorithms of Peer to Peer Networks

Comparison on Different Load Balancing Algorithms of Peer to Peer Networks Comparison on Different Load Balancing Algorithms of Peer to Peer Networks K.N.Sirisha *, S.Bhagya Rekha M.Tech,Software Engineering Noble college of Engineering & Technology for Women Web Technologies

More information

Load balancing in a heterogeneous computer system by self-organizing Kohonen network

Load balancing in a heterogeneous computer system by self-organizing Kohonen network Bull. Nov. Comp. Center, Comp. Science, 25 (2006), 69 74 c 2006 NCC Publisher Load balancing in a heterogeneous computer system by self-organizing Kohonen network Mikhail S. Tarkov, Yakov S. Bezrukov Abstract.

More information

Various Schemes of Load Balancing in Distributed Systems- A Review

Various Schemes of Load Balancing in Distributed Systems- A Review 741 Various Schemes of Load Balancing in Distributed Systems- A Review Monika Kushwaha Pranveer Singh Institute of Technology Kanpur, U.P. (208020) U.P.T.U., Lucknow Saurabh Gupta Pranveer Singh Institute

More information

Scalability and Classifications

Scalability and Classifications Scalability and Classifications 1 Types of Parallel Computers MIMD and SIMD classifications shared and distributed memory multicomputers distributed shared memory computers 2 Network Topologies static

More information

Cloud Computing Simulation Using CloudSim

Cloud Computing Simulation Using CloudSim Cloud Computing Simulation Using CloudSim Ranjan Kumar #1, G.Sahoo *2 # Assistant Professor, Computer Science & Engineering, Ranchi University, India Professor & Head, Information Technology, Birla Institute

More information

Proposal of Dynamic Load Balancing Algorithm in Grid System

Proposal of Dynamic Load Balancing Algorithm in Grid System www.ijcsi.org 186 Proposal of Dynamic Load Balancing Algorithm in Grid System Sherihan Abu Elenin Faculty of Computers and Information Mansoura University, Egypt Abstract This paper proposed dynamic load

More information

Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment

Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment Design and Implementation of Efficient Load Balancing Algorithm in Grid Environment Sandip S.Patil, Preeti Singh Department of Computer science & Engineering S.S.B.T s College of Engineering & Technology,

More information

A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster

A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster Acta Technica Jaurinensis Vol. 3. No. 1. 010 A Simultaneous Solution for General Linear Equations on a Ring or Hierarchical Cluster G. Molnárka, N. Varjasi Széchenyi István University Győr, Hungary, H-906

More information

Services Provider License Agreement Cloud Platform Suite & Guest

Services Provider License Agreement Cloud Platform Suite & Guest Services Provider License Agreement Cloud Platform Suite & Guest Frequently Asked Questions (FAQ) Last modified February 2014 Table of Contents Q1. What is the Cloud Platform Suite?... 2 Q2. What is the

More information

Load Balancing In Concurrent Parallel Applications

Load Balancing In Concurrent Parallel Applications Load Balancing In Concurrent Parallel Applications Jeff Figler Rochester Institute of Technology Computer Engineering Department Rochester, New York 14623 May 1999 Abstract A parallel concurrent application

More information

Reliable Systolic Computing through Redundancy

Reliable Systolic Computing through Redundancy Reliable Systolic Computing through Redundancy Kunio Okuda 1, Siang Wun Song 1, and Marcos Tatsuo Yamamoto 1 Universidade de São Paulo, Brazil, {kunio,song,mty}@ime.usp.br, http://www.ime.usp.br/ song/

More information

ParFUM: A Parallel Framework for Unstructured Meshes. Aaron Becker, Isaac Dooley, Terry Wilmarth, Sayantan Chakravorty Charm++ Workshop 2008

ParFUM: A Parallel Framework for Unstructured Meshes. Aaron Becker, Isaac Dooley, Terry Wilmarth, Sayantan Chakravorty Charm++ Workshop 2008 ParFUM: A Parallel Framework for Unstructured Meshes Aaron Becker, Isaac Dooley, Terry Wilmarth, Sayantan Chakravorty Charm++ Workshop 2008 What is ParFUM? A framework for writing parallel finite element

More information

Expanding the CASEsim Framework to Facilitate Load Balancing of Social Network Simulations

Expanding the CASEsim Framework to Facilitate Load Balancing of Social Network Simulations Expanding the CASEsim Framework to Facilitate Load Balancing of Social Network Simulations Amara Keller, Martin Kelly, Aaron Todd 4 June 2010 Abstract This research has two components, both involving the

More information

PARALLEL PROGRAMMING

PARALLEL PROGRAMMING PARALLEL PROGRAMMING TECHNIQUES AND APPLICATIONS USING NETWORKED WORKSTATIONS AND PARALLEL COMPUTERS 2nd Edition BARRY WILKINSON University of North Carolina at Charlotte Western Carolina University MICHAEL

More information

OPERATING SYSTEMS SCHEDULING

OPERATING SYSTEMS SCHEDULING OPERATING SYSTEMS SCHEDULING Jerry Breecher 5: CPU- 1 CPU What Is In This Chapter? This chapter is about how to get a process attached to a processor. It centers around efficient algorithms that perform

More information

Parallel Scalable Algorithms- Performance Parameters

Parallel Scalable Algorithms- Performance Parameters www.bsc.es Parallel Scalable Algorithms- Performance Parameters Vassil Alexandrov, ICREA - Barcelona Supercomputing Center, Spain Overview Sources of Overhead in Parallel Programs Performance Metrics for

More information

Evaluation of Different Task Scheduling Policies in Multi-Core Systems with Reconfigurable Hardware

Evaluation of Different Task Scheduling Policies in Multi-Core Systems with Reconfigurable Hardware Evaluation of Different Task Scheduling Policies in Multi-Core Systems with Reconfigurable Hardware Mahyar Shahsavari, Zaid Al-Ars, Koen Bertels,1, Computer Engineering Group, Software & Computer Technology

More information

Real Time Scheduling Basic Concepts. Radek Pelánek

Real Time Scheduling Basic Concepts. Radek Pelánek Real Time Scheduling Basic Concepts Radek Pelánek Basic Elements Model of RT System abstraction focus only on timing constraints idealization (e.g., zero switching time) Basic Elements Basic Notions task

More information

System Interconnect Architectures. Goals and Analysis. Network Properties and Routing. Terminology - 2. Terminology - 1

System Interconnect Architectures. Goals and Analysis. Network Properties and Routing. Terminology - 2. Terminology - 1 System Interconnect Architectures CSCI 8150 Advanced Computer Architecture Hwang, Chapter 2 Program and Network Properties 2.4 System Interconnect Architectures Direct networks for static connections Indirect

More information

COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook)

COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook) COMP 422, Lecture 3: Physical Organization & Communication Costs in Parallel Machines (Sections 2.4 & 2.5 of textbook) Vivek Sarkar Department of Computer Science Rice University vsarkar@rice.edu COMP

More information

A Review of Customized Dynamic Load Balancing for a Network of Workstations

A Review of Customized Dynamic Load Balancing for a Network of Workstations A Review of Customized Dynamic Load Balancing for a Network of Workstations Taken from work done by: Mohammed Javeed Zaki, Wei Li, Srinivasan Parthasarathy Computer Science Department, University of Rochester

More information

A Novel Cloud Based Elastic Framework for Big Data Preprocessing

A Novel Cloud Based Elastic Framework for Big Data Preprocessing School of Systems Engineering A Novel Cloud Based Elastic Framework for Big Data Preprocessing Omer Dawelbeit and Rachel McCrindle October 21, 2014 University of Reading 2008 www.reading.ac.uk Overview

More information

A Comparative Performance Analysis of Load Balancing Algorithms in Distributed System using Qualitative Parameters

A Comparative Performance Analysis of Load Balancing Algorithms in Distributed System using Qualitative Parameters A Comparative Performance Analysis of Load Balancing Algorithms in Distributed System using Qualitative Parameters Abhijit A. Rajguru, S.S. Apte Abstract - A distributed system can be viewed as a collection

More information

Keywords Load balancing, Dispatcher, Distributed Cluster Server, Static Load balancing, Dynamic Load balancing.

Keywords Load balancing, Dispatcher, Distributed Cluster Server, Static Load balancing, Dynamic Load balancing. Volume 5, Issue 7, July 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Hybrid Algorithm

More information

Genetic Algorithm. Based on Darwinian Paradigm. Intrinsically a robust search and optimization mechanism. Conceptual Algorithm

Genetic Algorithm. Based on Darwinian Paradigm. Intrinsically a robust search and optimization mechanism. Conceptual Algorithm 24 Genetic Algorithm Based on Darwinian Paradigm Reproduction Competition Survive Selection Intrinsically a robust search and optimization mechanism Slide -47 - Conceptual Algorithm Slide -48 - 25 Genetic

More information

Load Balancing in Structured Overlay Networks. Tallat M. Shafaat tallat(@)kth.se

Load Balancing in Structured Overlay Networks. Tallat M. Shafaat tallat(@)kth.se Load Balancing in Structured Overlay Networks Tallat M. Shafaat tallat(@)kth.se Overview Background The problem : load imbalance Causes of load imbalance Solutions But first, some slides from previous

More information

Tools Page 1 of 13 ON PROGRAM TRANSLATION. A priori, we have two translation mechanisms available:

Tools Page 1 of 13 ON PROGRAM TRANSLATION. A priori, we have two translation mechanisms available: Tools Page 1 of 13 ON PROGRAM TRANSLATION A priori, we have two translation mechanisms available: Interpretation Compilation On interpretation: Statements are translated one at a time and executed immediately.

More information

The optimize load balancing in cluster computing..

The optimize load balancing in cluster computing.. The optimize load balancing in cluster computing.. Mr. Sunil Kumar Pandey, Prof. Rajesh Tiwari. Computer Science and Engineering Department, shri sankaracharya college Of Engineering & Technology Bhilai.

More information

Real-Time Systems Prof. Dr. Rajib Mall Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur

Real-Time Systems Prof. Dr. Rajib Mall Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur Real-Time Systems Prof. Dr. Rajib Mall Department of Computer Science and Engineering Indian Institute of Technology, Kharagpur Lecture No. # 06 Basics of Real-Time Task Scheduling Let us get started.

More information

Introduction to DISC and Hadoop

Introduction to DISC and Hadoop Introduction to DISC and Hadoop Alice E. Fischer April 24, 2009 Alice E. Fischer DISC... 1/20 1 2 History Hadoop provides a three-layer paradigm Alice E. Fischer DISC... 2/20 Parallel Computing Past and

More information

Load balancing. Prof. Richard Vuduc Georgia Institute of Technology CSE/CS 8803 PNA: Parallel Numerical Algorithms [L.26] Thursday, April 17, 2008

Load balancing. Prof. Richard Vuduc Georgia Institute of Technology CSE/CS 8803 PNA: Parallel Numerical Algorithms [L.26] Thursday, April 17, 2008 Load balancing Prof. Richard Vuduc Georgia Institute of Technology CSE/CS 8803 PNA: Parallel Numerical Algorithms [L.26] Thursday, April 17, 2008 1 Today s sources CS 194/267 at UCB (Yelick/Demmel) Intro

More information

Performance metrics for parallel systems

Performance metrics for parallel systems Performance metrics for parallel systems S.S. Kadam C-DAC, Pune sskadam@cdac.in C-DAC/SECG/2006 1 Purpose To determine best parallel algorithm Evaluate hardware platforms Examine the benefits from parallelism

More information

Multi-GPU Load Balancing for Simulation and Rendering

Multi-GPU Load Balancing for Simulation and Rendering Multi- Load Balancing for Simulation and Rendering Yong Cao Computer Science Department, Virginia Tech, USA In-situ ualization and ual Analytics Instant visualization and interaction of computing tasks

More information

A SURVEY ON LOAD BALANCING ALGORITHMS FOR CLOUD COMPUTING

A SURVEY ON LOAD BALANCING ALGORITHMS FOR CLOUD COMPUTING A SURVEY ON LOAD BALANCING ALGORITHMS FOR CLOUD COMPUTING Avtar Singh #1,Kamlesh Dutta #2, Himanshu Gupta #3 #1 Department of Computer Science and Engineering, Shoolini University, avtarz@gmail.com #2

More information

Perfect Load Balancing for Demand-Driven Parallel Ray Tracing

Perfect Load Balancing for Demand-Driven Parallel Ray Tracing Perfect Load Balancing for Demand-Driven Parallel Ray Tracing Tomas Plachetka University of Paderborn, Department of Computer Science, Fürstenallee 11, D-33095Paderborn, Germany Abstract. A demand-driven

More information

Chapter 12: Multiprocessor Architectures. Lesson 01: Performance characteristics of Multiprocessor Architectures and Speedup

Chapter 12: Multiprocessor Architectures. Lesson 01: Performance characteristics of Multiprocessor Architectures and Speedup Chapter 12: Multiprocessor Architectures Lesson 01: Performance characteristics of Multiprocessor Architectures and Speedup Objective Be familiar with basic multiprocessor architectures and be able to

More information

CHAPTER 1 INTRODUCTION

CHAPTER 1 INTRODUCTION 1 CHAPTER 1 INTRODUCTION 1.1 MOTIVATION OF RESEARCH Multicore processors have two or more execution cores (processors) implemented on a single chip having their own set of execution and architectural recourses.

More information

CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT

CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT 81 CHAPTER 5 WLDMA: A NEW LOAD BALANCING STRATEGY FOR WAN ENVIRONMENT 5.1 INTRODUCTION Distributed Web servers on the Internet require high scalability and availability to provide efficient services to

More information

Making Multicore Work and Measuring its Benefits. Markus Levy, president EEMBC and Multicore Association

Making Multicore Work and Measuring its Benefits. Markus Levy, president EEMBC and Multicore Association Making Multicore Work and Measuring its Benefits Markus Levy, president EEMBC and Multicore Association Agenda Why Multicore? Standards and issues in the multicore community What is Multicore Association?

More information

CPS122 Lecture: State and Activity Diagrams in UML

CPS122 Lecture: State and Activity Diagrams in UML CPS122 Lecture: State and Activity Diagrams in UML Objectives: last revised February 14, 2012 1. To show how to create and read State Diagrams 2. To introduce UML Activity Diagrams Materials: 1. Demonstration

More information

Cellular Computing on a Linux Cluster

Cellular Computing on a Linux Cluster Cellular Computing on a Linux Cluster Alexei Agueev, Bernd Däne, Wolfgang Fengler TU Ilmenau, Department of Computer Architecture Topics 1. Cellular Computing 2. The Experiment 3. Experimental Results

More information

Parallel Ray Tracing using MPI: A Dynamic Load-balancing Approach

Parallel Ray Tracing using MPI: A Dynamic Load-balancing Approach Parallel Ray Tracing using MPI: A Dynamic Load-balancing Approach S. M. Ashraful Kadir 1 and Tazrian Khan 2 1 Scientific Computing, Royal Institute of Technology (KTH), Stockholm, Sweden smakadir@csc.kth.se,

More information

Load balancing. David Bindel. 12 Nov 2015

Load balancing. David Bindel. 12 Nov 2015 Load balancing David Bindel 12 Nov 2015 Inefficiencies in parallel code Poor single processor performance Typically in the memory system Saw this in matrix multiply assignment Overhead for parallelism

More information

Comparative Study of Load Balancing Algorithms

Comparative Study of Load Balancing Algorithms IOSR Journal of Engineering (IOSRJEN) e-issn: 2250-3021, p-issn: 2278-8719 Vol. 3, Issue 3 (Mar. 2013), V2 PP 45-50 Comparative Study of Load Balancing Algorithms Jyoti Vashistha 1, Anant Kumar Jayswal

More information

A Parallel Processor for Distributed Genetic Algorithm with Redundant Binary Number

A Parallel Processor for Distributed Genetic Algorithm with Redundant Binary Number A Parallel Processor for Distributed Genetic Algorithm with Redundant Binary Number 1 Tomohiro KAMIMURA, 2 Akinori KANASUGI 1 Department of Electronics, Tokyo Denki University, 07ee055@ms.dendai.ac.jp

More information

Lecture Outline Overview of real-time scheduling algorithms Outline relative strengths, weaknesses

Lecture Outline Overview of real-time scheduling algorithms Outline relative strengths, weaknesses Overview of Real-Time Scheduling Embedded Real-Time Software Lecture 3 Lecture Outline Overview of real-time scheduling algorithms Clock-driven Weighted round-robin Priority-driven Dynamic vs. static Deadline

More information

HPC with Multicore and GPUs

HPC with Multicore and GPUs HPC with Multicore and GPUs Stan Tomov Electrical Engineering and Computer Science Department University of Tennessee, Knoxville CS 594 Lecture Notes March 4, 2015 1/18 Outline! Introduction - Hardware

More information

A REVIEW ON LOAD BALANCING TECHNIQUE IN THE PUBLIC CLOUD USING PARTITIONING METHOD

A REVIEW ON LOAD BALANCING TECHNIQUE IN THE PUBLIC CLOUD USING PARTITIONING METHOD A REVIEW ON LOAD BALANCING TECHNIQUE IN THE PUBLIC CLOUD USING PARTITIONING METHOD 1 G. DAMODAR, 2 D. BARATH KUMAR 1 M.Tech Student, Department of CSE. gdyadav509@gmail.com 2 Assistant Professor, Department

More information

Parameter Sweep and Resources Scaling Automation in Scalarm Data Farming Platform

Parameter Sweep and Resources Scaling Automation in Scalarm Data Farming Platform Parameter Sweep and Resources Scaling Automation in Scalarm Data Farming Platform J. Liput, M. Paciorek, M. Wrona, M. Orzechowski, R. Slota, and J. Kitowski ACC Cyfronet AGH Department of Computer Science,

More information

Program Optimization for Multi-core Architectures

Program Optimization for Multi-core Architectures Program Optimization for Multi-core Architectures Sanjeev K Aggarwal (ska@iitk.ac.in) M Chaudhuri (mainak@iitk.ac.in) R Moona (moona@iitk.ac.in) Department of Computer Science and Engineering, IIT Kanpur

More information

Introduction to Cloud Computing

Introduction to Cloud Computing Introduction to Cloud Computing Parallel Processing I 15 319, spring 2010 7 th Lecture, Feb 2 nd Majd F. Sakr Lecture Motivation Concurrency and why? Different flavors of parallel computing Get the basic

More information

Operating Systems, 6 th ed. Test Bank Chapter 7

Operating Systems, 6 th ed. Test Bank Chapter 7 True / False Questions: Chapter 7 Memory Management 1. T / F In a multiprogramming system, main memory is divided into multiple sections: one for the operating system (resident monitor, kernel) and one

More information

LOAD BALANCING ALGORITHMS IN CLOUD COMPUTING

LOAD BALANCING ALGORITHMS IN CLOUD COMPUTING International Journal of Advanced Computer and Mathematical Sciences ISSN 2230-9624. Vol4, Issue3, 2013, pp229-233 http://bipublication.com LOAD BALANCING ALGORITHMS IN CLOUD COMPUTING Doddini Probhuling

More information

Oracle Service Bus: - When to use, where to use and when not to use

Oracle Service Bus: - When to use, where to use and when not to use Oracle Service Bus: - When to use, where to use and when not to use Session ID#: 244 Prepared by: Abhay Kumar Senior Consultant AST Corporation REMINDER Check in on the COLLABORATE mobile app Specialized.

More information

Load Balancing Scheduling with Shortest Load First

Load Balancing Scheduling with Shortest Load First , pp. 171-178 http://dx.doi.org/10.14257/ijgdc.2015.8.4.17 Load Balancing Scheduling with Shortest Load First Ranjan Kumar Mondal 1, Enakshmi Nandi 2 and Debabrata Sarddar 3 1 Department of Computer Science

More information

reduction critical_section

reduction critical_section A comparison of OpenMP and MPI for the parallel CFD test case Michael Resch, Bjíorn Sander and Isabel Loebich High Performance Computing Center Stuttgart èhlrsè Allmandring 3, D-755 Stuttgart Germany resch@hlrs.de

More information

Index Terms : Load rebalance, distributed file systems, clouds, movement cost, load imbalance, chunk.

Index Terms : Load rebalance, distributed file systems, clouds, movement cost, load imbalance, chunk. Load Rebalancing for Distributed File Systems in Clouds. Smita Salunkhe, S. S. Sannakki Department of Computer Science and Engineering KLS Gogte Institute of Technology, Belgaum, Karnataka, India Affiliated

More information

A UML-based Approach to Design Parallel and Distributed Applications

A UML-based Approach to Design Parallel and Distributed Applications A UML-based Approach to Design Parallel and Distributed Applications Yasset Perez-Riverol a,b, Roberto Vera Álvarez c December 2013 a Department of Proteomics, Center for Genetic Engineering and Biotechnology.

More information

Recommendations for Performance Benchmarking

Recommendations for Performance Benchmarking Recommendations for Performance Benchmarking Shikhar Puri Abstract Performance benchmarking of applications is increasingly becoming essential before deployment. This paper covers recommendations and best

More information

Advances in Smart Systems Research : ISSN 2050-8662 : http://nimbusvault.net/publications/koala/assr/ Vol. 3. No. 3 : pp.

Advances in Smart Systems Research : ISSN 2050-8662 : http://nimbusvault.net/publications/koala/assr/ Vol. 3. No. 3 : pp. Advances in Smart Systems Research : ISSN 2050-8662 : http://nimbusvault.net/publications/koala/assr/ Vol. 3. No. 3 : pp.49-54 : isrp13-005 Optimized Communications on Cloud Computer Processor by Using

More information

BIS 3106: Business Process Management. Lecture Two: Modelling the Control-flow Perspective

BIS 3106: Business Process Management. Lecture Two: Modelling the Control-flow Perspective BIS 3106: Business Process Management Lecture Two: Modelling the Control-flow Perspective Makerere University School of Computing and Informatics Technology Department of Computer Science SEM I 2015/2016

More information

Load Balancing on Massively Parallel Networks: A Cellular Automaton Approach

Load Balancing on Massively Parallel Networks: A Cellular Automaton Approach Load Balancing on Massively Parallel Networks: A Cellular Automaton Approach by Brian Dickens at the Thomas Jefferson High School for Science and Technology supervising instructor: Donald Hyatt originally

More information

Pipelining and load-balancing in parallel joins on distributed machines

Pipelining and load-balancing in parallel joins on distributed machines NP-PAR 05 p. / Pipelining and load-balancing in parallel joins on distributed machines M. Bamha bamha@lifo.univ-orleans.fr Laboratoire d Informatique Fondamentale d Orléans (France) NP-PAR 05 p. / Plan

More information

Scheduling Task Parallelism" on Multi-Socket Multicore Systems"

Scheduling Task Parallelism on Multi-Socket Multicore Systems Scheduling Task Parallelism" on Multi-Socket Multicore Systems" Stephen Olivier, UNC Chapel Hill Allan Porterfield, RENCI Kyle Wheeler, Sandia National Labs Jan Prins, UNC Chapel Hill Outline" Introduction

More information

Introduction to Cluster Computing

Introduction to Cluster Computing Introduction to Cluster Computing Brian Vinter vinter@diku.dk Overview Introduction Goal/Idea Phases Mandatory Assignments Tools Timeline/Exam General info Introduction Supercomputers are expensive Workstations

More information

Enabling Multi-pipeline Data Transfer in HDFS for Big Data Applications

Enabling Multi-pipeline Data Transfer in HDFS for Big Data Applications Enabling Multi-pipeline Data Transfer in HDFS for Big Data Applications Liqiang (Eric) Wang, Hong Zhang University of Wyoming Hai Huang IBM T.J. Watson Research Center Background Hadoop: Apache Hadoop

More information

Industrial Ethernet How to Keep Your Network Up and Running A Beginner s Guide to Redundancy Standards

Industrial Ethernet How to Keep Your Network Up and Running A Beginner s Guide to Redundancy Standards Redundancy = Protection from Network Failure. Redundancy Standards WP-31-REV0-4708-1/5 Industrial Ethernet How to Keep Your Network Up and Running A Beginner s Guide to Redundancy Standards For a very

More information

Dynamic Load Balancing in a Network of Workstations

Dynamic Load Balancing in a Network of Workstations Dynamic Load Balancing in a Network of Workstations 95.515F Research Report By: Shahzad Malik (219762) November 29, 2000 Table of Contents 1 Introduction 3 2 Load Balancing 4 2.1 Static Load Balancing

More information

Parallel Programming at the Exascale Era: A Case Study on Parallelizing Matrix Assembly For Unstructured Meshes

Parallel Programming at the Exascale Era: A Case Study on Parallelizing Matrix Assembly For Unstructured Meshes Parallel Programming at the Exascale Era: A Case Study on Parallelizing Matrix Assembly For Unstructured Meshes Eric Petit, Loïc Thebault, Quang V. Dinh May 2014 EXA2CT Consortium 2 WPs Organization Proto-Applications

More information

Automotive Software Engineering

Automotive Software Engineering Automotive Software Engineering List of Chapters: 1. Introduction and Overview 1.1 The Driver Vehicle Environment System 1.1.1 Design and Method of Operation of Vehicle Electronic 1.1.2 Electronic of the

More information

Algorithm Visualization through Animation and Role Plays

Algorithm Visualization through Animation and Role Plays 76 Third Program Visualization Workshop Algorithm Visualization through Animation and Role Plays 1 Introduction Jarmo Rantakokko Uppsala University, Department of Information Technology Uppsala, Sweden

More information

College of information technology Department of software

College of information technology Department of software University of Babylon Undergraduate: third class College of information technology Department of software Subj.: Application of AI lecture notes/2011-2012 ***************************************************************************

More information

Performance Analysis of Load Balancing Algorithms in Distributed System

Performance Analysis of Load Balancing Algorithms in Distributed System Advance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 4, Number 1 (2014), pp. 59-66 Research India Publications http://www.ripublication.com/aeee.htm Performance Analysis of Load Balancing

More information

(Refer Slide Time: 01:52)

(Refer Slide Time: 01:52) Software Engineering Prof. N. L. Sarda Computer Science & Engineering Indian Institute of Technology, Bombay Lecture - 2 Introduction to Software Engineering Challenges, Process Models etc (Part 2) This

More information

Workflow Management Standards & Interoperability

Workflow Management Standards & Interoperability Management Standards & Interoperability Management Coalition and Keith D Swenson Fujitsu OSSI kswenson@ossi.com Introduction Management (WfM) is evolving quickly and expolited increasingly by businesses

More information

MapReduce and Hadoop. Aaron Birkland Cornell Center for Advanced Computing. January 2012

MapReduce and Hadoop. Aaron Birkland Cornell Center for Advanced Computing. January 2012 MapReduce and Hadoop Aaron Birkland Cornell Center for Advanced Computing January 2012 Motivation Simple programming model for Big Data Distributed, parallel but hides this Established success at petabyte

More information

Designing and Building Applications for Extreme Scale Systems CS598 William Gropp www.cs.illinois.edu/~wgropp

Designing and Building Applications for Extreme Scale Systems CS598 William Gropp www.cs.illinois.edu/~wgropp Designing and Building Applications for Extreme Scale Systems CS598 William Gropp www.cs.illinois.edu/~wgropp Welcome! Who am I? William (Bill) Gropp Professor of Computer Science One of the Creators of

More information

International Journal of Computer Science Trends and Technology (IJCST) Volume 2 Issue 4, July-Aug 2014

International Journal of Computer Science Trends and Technology (IJCST) Volume 2 Issue 4, July-Aug 2014 RESEARCH ARTICLE An Efficient Service Broker Policy for Cloud Computing Environment Kunal Kishor 1, Vivek Thapar 2 Research Scholar 1, Assistant Professor 2 Department of Computer Science and Engineering,

More information

The Design and Implementation of Scalable Parallel Haskell

The Design and Implementation of Scalable Parallel Haskell The Design and Implementation of Scalable Parallel Haskell Malak Aljabri, Phil Trinder,and Hans-Wolfgang Loidl MMnet 13: Language and Runtime Support for Concurrent Systems Heriot Watt University May 8,

More information