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Bulk Synchronous Parallel Processing Model. Jamie Perkins. Overview. Four W’s – Who, What, When and Why Goals for BSP BSP Design and Program Cost Functions Languages and Machines. A Bridge for Parallel Computation. Von Neumann model Designed to insulate hardware and software

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Presentation Transcript
overview
Overview
  • Four W’s – Who, What, When and Why
  • Goals for BSP
  • BSP Design and Program
  • Cost Functions
  • Languages and Machines
a bridge for parallel computation
A Bridge for Parallel Computation
  • Von Neumann model
    • Designed to insulate hardware and software
  • BSP model (Bulk Synchronous Parallel)
    • Proposed by Leslie Valiant of Harvard University in 1990
    • Developed by W.F. McColl of Oxford
    • Designed to be a “bridge” for parallel computation
goals for bsp
Goals for BSP
  • Scalability – performance of HW & SW must be scalable from a single processor to thousands of processors
  • Portability – SW must run unchanged, with high performance, on any general purpose parallel architecture
  • Predictability – performance of SW on different architecture must be predictable in a straight forward way
bsp design
BSP Design
  • Three Components
    • Node
      • Processor and Local Memory
    • Router or Communication Network
      • Message Passing or Point-to-Point communication
    • Barrier or Synchronization Mechanism
      • Implemented in hardware
bsp design1
BSP Design
  • Fixed memory architecture
    • Hashing to allocate memory in “random” fashion
  • Fast access to local memory
  • Uniformly slow access to remote memory
illustration of bsp computer

P

P

P

M

M

M

Illustration of BSP Computer

Node

Node

Node

Barrier

Communication Network

http://peace.snu.ac.kr/courses/parallelprocessing/

bsp program
BSP Program
  • Composed of S supersteps
  • Superstep consists of:
    • A computation where each processor uses only locally held values
    • A global message transmission from each processor to any subset of the others
    • A barrier synchronization
strategies for programming on bsp
Strategies for programming on BSP
  • Balance the computation between processes
  • Balance the communication between processes
  • Minimize the number of supersteps
bsp program1
BSP Program

P1

P2

P3

P4

Superstep 1

Computation

Communication

Barrier

Superstep 2

http://peace.snu.ac.kr/courses/parallelprocessing/

advantages of bsp
Advantages of BSP
  • Eliminates need for programmers to manage memory, assign communication and perform low-level synchronization (w/ sufficient parallel slackness)
  • Synchronization allows automatic optimization of the communication pattern
  • BSP model provides a simple cost function for analyzing the complexity of algorithms
cost function
Cost Function
  • g – “gap” or bandwidth inefficiency
  • L – “latency”, minimum time needed for one superstep
  • w – largest amount of work performed (per processor)
  • h – largest number of packets sent or received

wi + ghi + L = execution time for the superstep i

languages machines
BSP ++

C

C++

Fortran

JBSP

Opal

IBM SP1

SGI Power Challenge

(Shared Memory)

Cray T3D

Hitachi SR2001

TCP/IP

Languages & Machines
thank you
Thank You

Any Questions

references
References
  • http://peace.snu.ac.kr/courses/parallelprocessing/
  • http://wwwcs.uni-paderborn.de/fachbereich/AG/agmad
  • http://www.cs.mu.oz.au/677/notes/node41.html
  • McColl, W.F. The BSP Approach to Architecture Independent Parallel Programming. Technical report, Oxford University Computing Laboratory, Dec. 1994
  • United States Patent 5083265
  • Valiant, L.G. A Bridging Model for Parallel Computation. Communications of the ACM 33,8 (1990), 103-111.