CS315B Parallel Computer Computing Research Project - PowerPoint PPT Presentation

1 / 14
About This Presentation
Title:

CS315B Parallel Computer Computing Research Project

Description:

From Hennessy and Patterson, Computer Architecture: A ... Jared Casper. E-mail cs315b-spr0607-staff_at_lists.stanford.edu. Course Support. Darlene Hadding ... – PowerPoint PPT presentation

Number of Views:90
Avg rating:3.0/5.0
Slides: 15
Provided by: kunleol
Category:

less

Transcript and Presenter's Notes

Title: CS315B Parallel Computer Computing Research Project


1
CS315BParallel Computer Computing
ResearchProject
Bill Dally, Christos Kozyrakis and Kunle
Olukotun Stanford University http//www.stanford.
edu/class/cs315b/
2
End of Uniprocessor Performance
3X
From Hennessy and Patterson, Computer
Architecture A Quantitative Approach, 4th
edition, October, 2006
The free lunch is over! Now in the multicore era
3
The Evolution in the Multicore Era
4
Life in the Multicore Era
  • The move to multicore will be a disruptive shift
  • Declining single thread performance
  • Heterogeneity many thin, few fat, few vector
  • A forced shift in the programming model
  • New Architecture Opportunities
  • A chance for radical redesign of the
    microprocessor
  • What are the innovations that will
    reduce/eliminate the extra burden placed on the
    programmer?

5
Novel Opportunities in Multicores
  • Dont have to contend with uniprocessors
  • Performance plateau
  • Perfect scalability not required
  • Not your same old multiprocessor problem
  • How does going from Multiprocessors to Multicores
    impact programs?
  • What changed?
  • Where is the Impact?
  • Communication Bandwidth
  • Communication Latency

6
Communication Bandwidth
  • How much data can be communicated between two
    cores?
  • What changed?
  • Number of Wires
  • Clock rate
  • Multiplexing
  • Impact on programming model?
  • Massive data communication is possible
  • Data movement is not the bottleneck ? processor
    affinity not that important

1,000X
100 Giga bits/sec
100 Tera bits/sec
7
Communication Latency
  • How long does it take for a round trip
    communication?
  • What changed?
  • Length of wire
  • Pipeline stages
  • Impact on programming model?
  • Fast synchronization communication
  • Finer grained parallelism
  • Can run real-time apps on multiple cores

10X
200 Cycles
20 cycles
8
Good News High Throughput
  • Sun Niagara 2
  • 8 cores x 8 threads 64 threads
  • Simple cores gt low power
  • High throughput/Watt
  • Commercial servers
  • Request level parallelism
  • Performance/Watt important
  • Scientific
  • Data-level parallelism
  • Dense and sparse matrix
  • Performance/Watt important

9
Bad News Parallel Programming Gap
  • By 2010, software developers will face
  • CPUs with
  • 20 cores
  • 100s hardware threads
  • Deep memory hierarchies
  • Integrated GPUs with general computing
    capabilities
  • 100s hardware threads
  • Parallel programming gap Growing divide between
    the capabilities of todays programmers,
    programming languages, models, and tools and the
    challenges of future parallel architectures and
    applications
  • MPI, Pthreads, OMP wont suffice
  • Automatic parallelization is not general or
    scalable
  • parallelism is the biggest challenge since
    high-level programming languages. Its the
    biggest thing in 50 years because industry is
    betting its future that parallel programming will
    be useful. David Patterson

10
Needed Innovations in Parallel Computing
  • New application areas that can take advantage of
    parallelism
  • Games and virtual worlds
  • Data mining
  • Cognitive reasoning and machine learning
  • New high-level programming models/languages
  • Domain specific gt just do it
  • Admit high performance implementations
  • New medium-level programming paradigms
  • Small increase in programming complexity
  • Easy to debug functionality and tune performance
  • 10 more effort for 90 of potential parallel
    performance
  • New architecture support for parallel computing
  • Beyond cache coherence
  • Easier programming
  • High performance
  • CS315B Goal generate new ideas

11
Schedule
12
Course Information
  • Instructors
  • Bill Dally
  • Christos Kozyrakis
  • Kunle Olukotun
  • E-mail cs315b-spr0607-staff_at_lists.stanford.edu
  • Office Hours After class or by appointment
  • CA
  • Jared Casper
  • E-mail cs315b-spr0607-staff_at_lists.stanford.edu
  • Course Support
  • Darlene Hadding

13
Course Information (cont)
  • Lectures
  • Thursday 415pm-530pm
  • Grading
  • Class participation 20
  • Midterm assignment 40
  • Final assignment 40
  • Assignments
  • 10-15 slides, subset for 5-10 minute
    presentation
  • Put slides on Wiki before presentation
  • Midterm
  • High-level programming languages/models
  • Groups of two
  • Final
  • Application or algorithm analysis
  • Individuals

14
What Will You Get Out of CS315B?
  • What you put into it
  • Research project course
  • You do the research
  • Little or no traditional lectures gt discussion
  • You should be engaged and ready to contribute to
    discussion
  • If you have opinions express them!
  • Brainstorming we wont be critical
Write a Comment
User Comments (0)
About PowerShow.com