SlideShare une entreprise Scribd logo
1  sur  21
Connection MachineArchitecture Greg Faust, Mike Gibson, Sal Valente CS-6354 Computer Architecture Fall 2009 1
Historic Timeline 1981: MIT AI-Lab Technical Memo on CM 1982: Thinking Machines Inc. Founded  1985: Danny Hillis wins ACM “Best PhD” Award 1986: CM-1 Ships 1987: CM-2 Ships 1991: CM-5 Announced 1991: CM-5 Ships 1994: TMI Chapter 11 – Sun/Oracle pick bones Heavily DARPA funded/backed $16M+ Direct Contracts plus subsidized CM sales 2
Involved Notables Danny Hillis – CM inventor and TMI Founder Charles Leiserson – Fat tree inventor Richard Feynman – Noble Prize winning Physicist Marvin Minsky – MIT AI Lab “Visionary” Guy Steele – Common Lisp, Grace Hopper Award Stephen Wolfram – Mathematica inventor Doug Lenat – Mind/Body problem philosopher Greg Papadopoulos – MIT Media lab, Sun CTO various others 3
CM-1 and CM-2 Architecture Original design goal to support neuron like simulations Up to 64K single bit processors (actually 3 bits in and 2 out) 16 Processors/chip, 32chips/PCB, 16 PCBs/cube, 8cubes/hypercube Hypercube architecture – Each 16-Proc chip a hyper-node Each proc has 4K bits of bit addressable RAM Distributed Physical Memory  Global Memory Addresses Up to 4 front-end computers talk to sequencers via 4x4 crossbar “Sequencers” issue SIMD instructions over a Broadcast Network Bit procs communicate via 2D local HW grid connections (“NEWS”) Bit procs communicate via hypercube network using MSG passing Lots of Twinkling Lights!! 4
CM-1 CM-2 Architecture 5
CM-1 and CM-2 Programming ISA supports: Bit-oriented operations Arbitrary precision multi-bit scalar Ops using bit-serial implementation on bit procs Full Multi-Dimensional Vector Ops “Virtual Processor” idea similar to CUDA threadsbut they are statically allocated OS and Programming Tools run on front-ends *Lisp as the initial programming language Later C* and CM-Fortran 6
CM-2 Improvements 1 Weitek IEEE FP coprocessor per 32 1-bit procs Up to 256K bits of memory per processor Added ECC to Memory Implemented the IO subsystem Up to 80 GByte RAID array called “Data Vault”uses 39 Striped Disks and ECC, plus spare disks on standby High Speed Graphics Output En-route MSG combining in H-Cube router New implementation of Multi-DimensionalNEWS on top of H-Cube (special addressing mode) 7
CM-1 Photo 8
CM-5 vs CM-1 and CM-2 Significant departure from CM-1 and CM-2 Targeted at more scientific and business applications  More Commercial Off-The-Shelf components  (“COTS”) Large Array of SPARC Processing Nodes 1-bit processors are abandoned Abandoned “NEWS” Grid and Hyper-Cube Networks Delivered 1024 node machine, with claims 16K nodes possible Even More Twinkling Lights! 9
CM-5 Photo – Watch it Blink 10
CM-5 Overall Architecture "Coordinated Homogeneous Array of RISC Processors“  or “CHARM” Asymmetric CoProcessors Model Large Array of Processor Nodes Small Collection of Control Nodes 2 Separate scalable networks One for data One for control and synchronization Still uses striped RAID for high disk BandWidth 11
Division of Labor Processor Nodes can be assigned to a “Partition” One Control Node per Partition Control Node runs scalar code, then broadcasts parallel work to Processor Nodes Processor Nodes receive a program, not an instruction stream, have own Program Counter Processor nodes can access other node's memory by reading or writing a global memory address Processor Nodes also communicate via MSG passing Processor Nodes cannot issue system calls 12
Control Nodes Full Sun Workstations Running UNIX Connected to the “Outside World” Handles Partition Time Sharing Connected to both data and control networks Performs System Diagnostics 13
Processor Nodes Nodes are a 5-chip microprocessor Off the Shelf SPARC processor @ 40 MHz 32MBytes local node memory Multi-port memory controller for added BW “Caching  techniques do not perform as well on large parallel machines” Proprietary 4-FPU Vector coprocessor Proprietary network controller 14
CM-5 Processor Node Diagram 15
Data Network Architecture Point to Point Inter-node communication and I/O Implemented as a Fat Tree Fat Trees invented by TMI employee Charles Leiserson Claim: Onsite BandWidth Expandable Delivering 5GB/sec Bisection BW on 1024 node machine Data router chip is a 8x8 crossbar switch Faulty nodes are mapped out of network Programs can not assume a network topology Network can be flushed when Time Share swaps occur Network, not processors, guarantee end to end delivery 16
Fat Tree Structure 17
Separate Control Network Synchronization & control network Complete Binary Tree organization Provides broadcast capability Implements barrier operations Implements interrupts for timesharing Performs reduction operators (Sum, Max, AND, OR, Count, etc) 18
CM-5 Programming Supports multiple Parallel High Level Languages and Programming Styles Including Data Parallel Model from CM-1 and CM-2 Goal: Hide many decisions from programmers CM-1, CM-2 vs CM-5 ISA changes Use of Processor Node CPU vs Vector CoProcessors Partition Wide Synchronizations generate by Compiler Is it MIMD, SPMD, SIMD?   “Globally Synchronized MIMD” 19
Sample CM Apps Machine Learning Neural Nets, concept clustering, genetic algorithms VLSI Design Geophysics (Oil Exploration), Plate Tectonics Particle Simulation Fluid Flow Simulation Computer Vision Computer Graphics , Animation Protein Sequence Matching Global Climate Model Simulation 20
References Danny Hillis PhD: The Connection Machine Inc: The Rise and Fall of Thinking Machines Wiki: Connection Machine ACM: The CM-5 Connection Machine ACM: The Network Architecture of the CM-5 IEEE: Architecture and Applications of the Connection Machine IEEE: Fat-trees: universal networks for hardware-efficient supercomputing Encyclopedia of Computer Science and Technology 21

Contenu connexe

Tendances

Lecture 6.1
Lecture  6.1Lecture  6.1
Lecture 6.1Mr SMAK
 
File replication
File replicationFile replication
File replicationKlawal13
 
Processes and Processors in Distributed Systems
Processes and Processors in Distributed SystemsProcesses and Processors in Distributed Systems
Processes and Processors in Distributed SystemsDr Sandeep Kumar Poonia
 
Pipelining and vector processing
Pipelining and vector processingPipelining and vector processing
Pipelining and vector processingKamal Acharya
 
Sistemi Operativi: Processi - Lezione 07
Sistemi Operativi: Processi - Lezione 07Sistemi Operativi: Processi - Lezione 07
Sistemi Operativi: Processi - Lezione 07Majong DevJfu
 
Real-Time Scheduling Algorithms
Real-Time Scheduling AlgorithmsReal-Time Scheduling Algorithms
Real-Time Scheduling AlgorithmsAJAL A J
 
advanced computer architesture-conditions of parallelism
advanced computer architesture-conditions of parallelismadvanced computer architesture-conditions of parallelism
advanced computer architesture-conditions of parallelismPankaj Kumar Jain
 
Parallel programming model, language and compiler in ACA.
Parallel programming model, language and compiler in ACA.Parallel programming model, language and compiler in ACA.
Parallel programming model, language and compiler in ACA.MITS Gwalior
 
multiprocessors and multicomputers
 multiprocessors and multicomputers multiprocessors and multicomputers
multiprocessors and multicomputersPankaj Kumar Jain
 
Parallel computing
Parallel computingParallel computing
Parallel computingVinay Gupta
 
Lec 4 (program and network properties)
Lec 4 (program and network properties)Lec 4 (program and network properties)
Lec 4 (program and network properties)Sudarshan Mondal
 
System interconnect architecture
System interconnect architectureSystem interconnect architecture
System interconnect architectureGagan Kumar
 
Flynn's Classification .pptx
Flynn's Classification .pptxFlynn's Classification .pptx
Flynn's Classification .pptxNayan Gupta
 
Parallel computing and its applications
Parallel computing and its applicationsParallel computing and its applications
Parallel computing and its applicationsBurhan Ahmed
 
Distributed shared memory shyam soni
Distributed shared memory shyam soniDistributed shared memory shyam soni
Distributed shared memory shyam soniShyam Soni
 
Chapter 4 the processor
Chapter 4 the processorChapter 4 the processor
Chapter 4 the processors9007912
 
Processor allocation in Distributed Systems
Processor allocation in Distributed SystemsProcessor allocation in Distributed Systems
Processor allocation in Distributed SystemsRitu Ranjan Shrivastwa
 
System models in distributed system
System models in distributed systemSystem models in distributed system
System models in distributed systemishapadhy
 
Parallel programming model
Parallel programming modelParallel programming model
Parallel programming modeleasy notes
 

Tendances (20)

Lecture 6.1
Lecture  6.1Lecture  6.1
Lecture 6.1
 
File replication
File replicationFile replication
File replication
 
Processes and Processors in Distributed Systems
Processes and Processors in Distributed SystemsProcesses and Processors in Distributed Systems
Processes and Processors in Distributed Systems
 
Pipelining and vector processing
Pipelining and vector processingPipelining and vector processing
Pipelining and vector processing
 
Sistemi Operativi: Processi - Lezione 07
Sistemi Operativi: Processi - Lezione 07Sistemi Operativi: Processi - Lezione 07
Sistemi Operativi: Processi - Lezione 07
 
Real-Time Scheduling Algorithms
Real-Time Scheduling AlgorithmsReal-Time Scheduling Algorithms
Real-Time Scheduling Algorithms
 
advanced computer architesture-conditions of parallelism
advanced computer architesture-conditions of parallelismadvanced computer architesture-conditions of parallelism
advanced computer architesture-conditions of parallelism
 
Parallel programming model, language and compiler in ACA.
Parallel programming model, language and compiler in ACA.Parallel programming model, language and compiler in ACA.
Parallel programming model, language and compiler in ACA.
 
multiprocessors and multicomputers
 multiprocessors and multicomputers multiprocessors and multicomputers
multiprocessors and multicomputers
 
Advanced computer architecture
Advanced computer architectureAdvanced computer architecture
Advanced computer architecture
 
Parallel computing
Parallel computingParallel computing
Parallel computing
 
Lec 4 (program and network properties)
Lec 4 (program and network properties)Lec 4 (program and network properties)
Lec 4 (program and network properties)
 
System interconnect architecture
System interconnect architectureSystem interconnect architecture
System interconnect architecture
 
Flynn's Classification .pptx
Flynn's Classification .pptxFlynn's Classification .pptx
Flynn's Classification .pptx
 
Parallel computing and its applications
Parallel computing and its applicationsParallel computing and its applications
Parallel computing and its applications
 
Distributed shared memory shyam soni
Distributed shared memory shyam soniDistributed shared memory shyam soni
Distributed shared memory shyam soni
 
Chapter 4 the processor
Chapter 4 the processorChapter 4 the processor
Chapter 4 the processor
 
Processor allocation in Distributed Systems
Processor allocation in Distributed SystemsProcessor allocation in Distributed Systems
Processor allocation in Distributed Systems
 
System models in distributed system
System models in distributed systemSystem models in distributed system
System models in distributed system
 
Parallel programming model
Parallel programming modelParallel programming model
Parallel programming model
 

En vedette

Accesso ai dati con Azure Data Platform
Accesso ai dati con Azure Data PlatformAccesso ai dati con Azure Data Platform
Accesso ai dati con Azure Data PlatformLuca Di Fino
 
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...Particular Software
 
AI, A New Computing Model
AI, A New Computing ModelAI, A New Computing Model
AI, A New Computing ModelNVIDIA Taiwan
 
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)Lowy Shin
 
H2O Open New York - Keynote, Sri Ambati, CEO H2O.ai
H2O Open New York - Keynote, Sri Ambati, CEO H2O.aiH2O Open New York - Keynote, Sri Ambati, CEO H2O.ai
H2O Open New York - Keynote, Sri Ambati, CEO H2O.aiSri Ambati
 
AI in Healthcare 2017
AI in Healthcare 2017AI in Healthcare 2017
AI in Healthcare 2017Peter Morgan
 
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arcNAVER D2
 
1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice
1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice
1.[d2 오픈세미나]on thearchitectureofsocialnetworkserviceNAVER D2
 
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐NAVER D2
 
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안NAVER D2
 
AI For Enterprise
AI For EnterpriseAI For Enterprise
AI For EnterpriseNVIDIA
 
An Overview of AI on the AWS Platform - February 2017 Online Tech Talks
An Overview of AI on the AWS Platform - February 2017 Online Tech TalksAn Overview of AI on the AWS Platform - February 2017 Online Tech Talks
An Overview of AI on the AWS Platform - February 2017 Online Tech TalksAmazon Web Services
 
Bank: Trends, Tech and Future
Bank: Trends, Tech and FutureBank: Trends, Tech and Future
Bank: Trends, Tech and FutureIvano Digital
 
Deep Learning and the state of AI / 2016
Deep Learning and the state of AI / 2016Deep Learning and the state of AI / 2016
Deep Learning and the state of AI / 2016Grigory Sapunov
 
Top 5 Deep Learning and AI Stories 3/9
Top 5 Deep Learning and AI Stories 3/9Top 5 Deep Learning and AI Stories 3/9
Top 5 Deep Learning and AI Stories 3/9NVIDIA
 

En vedette (20)

Accesso ai dati con Azure Data Platform
Accesso ai dati con Azure Data PlatformAccesso ai dati con Azure Data Platform
Accesso ai dati con Azure Data Platform
 
Aca 2
Aca 2Aca 2
Aca 2
 
161004 battle ai
161004 battle ai161004 battle ai
161004 battle ai
 
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...
Building a Highly Scalable File Processing Platform with NServiceBus NSBCon b...
 
AI, A New Computing Model
AI, A New Computing ModelAI, A New Computing Model
AI, A New Computing Model
 
Ai 150 architecture
Ai 150 architectureAi 150 architecture
Ai 150 architecture
 
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)
[giip] A.I. Infrastructure Advisor (인공지능 인프라 어드바이저)
 
H2O Open New York - Keynote, Sri Ambati, CEO H2O.ai
H2O Open New York - Keynote, Sri Ambati, CEO H2O.aiH2O Open New York - Keynote, Sri Ambati, CEO H2O.ai
H2O Open New York - Keynote, Sri Ambati, CEO H2O.ai
 
AI in Healthcare 2017
AI in Healthcare 2017AI in Healthcare 2017
AI in Healthcare 2017
 
Is Microservices SOA Done Right?
Is Microservices SOA Done Right?Is Microservices SOA Done Right?
Is Microservices SOA Done Right?
 
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc
3.[d2 오픈세미나]분산시스템 개발 및 교훈 n base arc
 
1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice
1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice
1.[d2 오픈세미나]on thearchitectureofsocialnetworkservice
 
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐
4.[d2 오픈세미나]LINE Rangers 게임 클라이언트/서버 아키텍쳐
 
Pi ai landscape
Pi ai landscapePi ai landscape
Pi ai landscape
 
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안
2.[d2 오픈세미나]네이버클라우드 시스템 아키텍처 및 활용 방안
 
AI For Enterprise
AI For EnterpriseAI For Enterprise
AI For Enterprise
 
An Overview of AI on the AWS Platform - February 2017 Online Tech Talks
An Overview of AI on the AWS Platform - February 2017 Online Tech TalksAn Overview of AI on the AWS Platform - February 2017 Online Tech Talks
An Overview of AI on the AWS Platform - February 2017 Online Tech Talks
 
Bank: Trends, Tech and Future
Bank: Trends, Tech and FutureBank: Trends, Tech and Future
Bank: Trends, Tech and Future
 
Deep Learning and the state of AI / 2016
Deep Learning and the state of AI / 2016Deep Learning and the state of AI / 2016
Deep Learning and the state of AI / 2016
 
Top 5 Deep Learning and AI Stories 3/9
Top 5 Deep Learning and AI Stories 3/9Top 5 Deep Learning and AI Stories 3/9
Top 5 Deep Learning and AI Stories 3/9
 

Similaire à Connection Machine

Advanced Computer Architecture
Advanced Computer ArchitectureAdvanced Computer Architecture
Advanced Computer Architecturenibiganesh
 
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...BigDataEverywhere
 
Industrial trends in heterogeneous and esoteric compute
Industrial trends in heterogeneous and esoteric computeIndustrial trends in heterogeneous and esoteric compute
Industrial trends in heterogeneous and esoteric computePerry Lea
 
Comparison between computers of past and present
Comparison between computers of past and presentComparison between computers of past and present
Comparison between computers of past and presentMuhammad Danish Badar
 
Hardware and Software Architectures for the CELL BROADBAND ENGINE processor
Hardware and Software Architectures for the CELL BROADBAND ENGINE processorHardware and Software Architectures for the CELL BROADBAND ENGINE processor
Hardware and Software Architectures for the CELL BROADBAND ENGINE processorSlide_N
 
02 Computer Evolution And Performance
02  Computer  Evolution And  Performance02  Computer  Evolution And  Performance
02 Computer Evolution And PerformanceJeanie Delos Arcos
 
Lect-3 Evaluation of computer architecture.pptx.pdf
Lect-3 Evaluation of computer architecture.pptx.pdfLect-3 Evaluation of computer architecture.pptx.pdf
Lect-3 Evaluation of computer architecture.pptx.pdfharm4202
 
Sistem mikroprosessor
Sistem mikroprosessorSistem mikroprosessor
Sistem mikroprosessorfahmihafid
 
Technology trends Moore’s law
Technology trends Moore’s lawTechnology trends Moore’s law
Technology trends Moore’s lawSyed Zaid Irshad
 
Free Hardware & Networking Slides by ITE Infotech Private Limited
Free Hardware & Networking Slides by ITE Infotech Private LimitedFree Hardware & Networking Slides by ITE Infotech Private Limited
Free Hardware & Networking Slides by ITE Infotech Private LimitedHemraj Singh Chouhan
 
Microprocessor & microcontroller
Microprocessor & microcontroller Microprocessor & microcontroller
Microprocessor & microcontroller Nitesh Kumar
 
A New Golden Age for Computer Architecture
A New Golden Age for Computer ArchitectureA New Golden Age for Computer Architecture
A New Golden Age for Computer ArchitectureYanbin Kong
 
My ISCA 2013 - 40th International Symposium on Computer Architecture Keynote
My ISCA 2013 - 40th International Symposium on Computer Architecture KeynoteMy ISCA 2013 - 40th International Symposium on Computer Architecture Keynote
My ISCA 2013 - 40th International Symposium on Computer Architecture KeynoteDileep Bhandarkar
 
Parallel_and_Cluster_Computing.ppt
Parallel_and_Cluster_Computing.pptParallel_and_Cluster_Computing.ppt
Parallel_and_Cluster_Computing.pptMohmdUmer
 

Similaire à Connection Machine (20)

Advanced Computer Architecture
Advanced Computer ArchitectureAdvanced Computer Architecture
Advanced Computer Architecture
 
Computer Evolution
Computer EvolutionComputer Evolution
Computer Evolution
 
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...
Big Data Everywhere Chicago: High Performance Computing - Contributions Towar...
 
Industrial trends in heterogeneous and esoteric compute
Industrial trends in heterogeneous and esoteric computeIndustrial trends in heterogeneous and esoteric compute
Industrial trends in heterogeneous and esoteric compute
 
Comparison between computers of past and present
Comparison between computers of past and presentComparison between computers of past and present
Comparison between computers of past and present
 
Hardware and Software Architectures for the CELL BROADBAND ENGINE processor
Hardware and Software Architectures for the CELL BROADBAND ENGINE processorHardware and Software Architectures for the CELL BROADBAND ENGINE processor
Hardware and Software Architectures for the CELL BROADBAND ENGINE processor
 
Exascale Capabl
Exascale CapablExascale Capabl
Exascale Capabl
 
02 Computer Evolution And Performance
02  Computer  Evolution And  Performance02  Computer  Evolution And  Performance
02 Computer Evolution And Performance
 
Lect-3 Evaluation of computer architecture.pptx.pdf
Lect-3 Evaluation of computer architecture.pptx.pdfLect-3 Evaluation of computer architecture.pptx.pdf
Lect-3 Evaluation of computer architecture.pptx.pdf
 
Module 1 unit 3
Module 1  unit 3Module 1  unit 3
Module 1 unit 3
 
Computer components
Computer componentsComputer components
Computer components
 
Sistem mikroprosessor
Sistem mikroprosessorSistem mikroprosessor
Sistem mikroprosessor
 
Technology trends Moore’s law
Technology trends Moore’s lawTechnology trends Moore’s law
Technology trends Moore’s law
 
Free Hardware & Networking Slides by ITE Infotech Private Limited
Free Hardware & Networking Slides by ITE Infotech Private LimitedFree Hardware & Networking Slides by ITE Infotech Private Limited
Free Hardware & Networking Slides by ITE Infotech Private Limited
 
Hpc 2
Hpc 2Hpc 2
Hpc 2
 
Microprocessor & microcontroller
Microprocessor & microcontroller Microprocessor & microcontroller
Microprocessor & microcontroller
 
A New Golden Age for Computer Architecture
A New Golden Age for Computer ArchitectureA New Golden Age for Computer Architecture
A New Golden Age for Computer Architecture
 
My ISCA 2013 - 40th International Symposium on Computer Architecture Keynote
My ISCA 2013 - 40th International Symposium on Computer Architecture KeynoteMy ISCA 2013 - 40th International Symposium on Computer Architecture Keynote
My ISCA 2013 - 40th International Symposium on Computer Architecture Keynote
 
Parallel_and_Cluster_Computing.ppt
Parallel_and_Cluster_Computing.pptParallel_and_Cluster_Computing.ppt
Parallel_and_Cluster_Computing.ppt
 
L05 parallel
L05 parallelL05 parallel
L05 parallel
 

Plus de butest

EL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBEEL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBEbutest
 
1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同butest
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALbutest
 
Timeline: The Life of Michael Jackson
Timeline: The Life of Michael JacksonTimeline: The Life of Michael Jackson
Timeline: The Life of Michael Jacksonbutest
 
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...butest
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALbutest
 
Com 380, Summer II
Com 380, Summer IICom 380, Summer II
Com 380, Summer IIbutest
 
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet JazzThe MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazzbutest
 
MICHAEL JACKSON.doc
MICHAEL JACKSON.docMICHAEL JACKSON.doc
MICHAEL JACKSON.docbutest
 
Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1butest
 
Facebook
Facebook Facebook
Facebook butest
 
Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...butest
 
Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...butest
 
NEWS ANNOUNCEMENT
NEWS ANNOUNCEMENTNEWS ANNOUNCEMENT
NEWS ANNOUNCEMENTbutest
 
C-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.docC-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.docbutest
 
MAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.docMAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.docbutest
 
Mac OS X Guide.doc
Mac OS X Guide.docMac OS X Guide.doc
Mac OS X Guide.docbutest
 
WEB DESIGN!
WEB DESIGN!WEB DESIGN!
WEB DESIGN!butest
 

Plus de butest (20)

EL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBEEL MODELO DE NEGOCIO DE YOUTUBE
EL MODELO DE NEGOCIO DE YOUTUBE
 
1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同1. MPEG I.B.P frame之不同
1. MPEG I.B.P frame之不同
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
 
Timeline: The Life of Michael Jackson
Timeline: The Life of Michael JacksonTimeline: The Life of Michael Jackson
Timeline: The Life of Michael Jackson
 
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
Popular Reading Last Updated April 1, 2010 Adams, Lorraine The ...
 
LESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIALLESSONS FROM THE MICHAEL JACKSON TRIAL
LESSONS FROM THE MICHAEL JACKSON TRIAL
 
Com 380, Summer II
Com 380, Summer IICom 380, Summer II
Com 380, Summer II
 
PPT
PPTPPT
PPT
 
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet JazzThe MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
The MYnstrel Free Press Volume 2: Economic Struggles, Meet Jazz
 
MICHAEL JACKSON.doc
MICHAEL JACKSON.docMICHAEL JACKSON.doc
MICHAEL JACKSON.doc
 
Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1Social Networks: Twitter Facebook SL - Slide 1
Social Networks: Twitter Facebook SL - Slide 1
 
Facebook
Facebook Facebook
Facebook
 
Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...Executive Summary Hare Chevrolet is a General Motors dealership ...
Executive Summary Hare Chevrolet is a General Motors dealership ...
 
Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...Welcome to the Dougherty County Public Library's Facebook and ...
Welcome to the Dougherty County Public Library's Facebook and ...
 
NEWS ANNOUNCEMENT
NEWS ANNOUNCEMENTNEWS ANNOUNCEMENT
NEWS ANNOUNCEMENT
 
C-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.docC-2100 Ultra Zoom.doc
C-2100 Ultra Zoom.doc
 
MAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.docMAC Printing on ITS Printers.doc.doc
MAC Printing on ITS Printers.doc.doc
 
Mac OS X Guide.doc
Mac OS X Guide.docMac OS X Guide.doc
Mac OS X Guide.doc
 
hier
hierhier
hier
 
WEB DESIGN!
WEB DESIGN!WEB DESIGN!
WEB DESIGN!
 

Connection Machine

  • 1. Connection MachineArchitecture Greg Faust, Mike Gibson, Sal Valente CS-6354 Computer Architecture Fall 2009 1
  • 2. Historic Timeline 1981: MIT AI-Lab Technical Memo on CM 1982: Thinking Machines Inc. Founded 1985: Danny Hillis wins ACM “Best PhD” Award 1986: CM-1 Ships 1987: CM-2 Ships 1991: CM-5 Announced 1991: CM-5 Ships 1994: TMI Chapter 11 – Sun/Oracle pick bones Heavily DARPA funded/backed $16M+ Direct Contracts plus subsidized CM sales 2
  • 3. Involved Notables Danny Hillis – CM inventor and TMI Founder Charles Leiserson – Fat tree inventor Richard Feynman – Noble Prize winning Physicist Marvin Minsky – MIT AI Lab “Visionary” Guy Steele – Common Lisp, Grace Hopper Award Stephen Wolfram – Mathematica inventor Doug Lenat – Mind/Body problem philosopher Greg Papadopoulos – MIT Media lab, Sun CTO various others 3
  • 4. CM-1 and CM-2 Architecture Original design goal to support neuron like simulations Up to 64K single bit processors (actually 3 bits in and 2 out) 16 Processors/chip, 32chips/PCB, 16 PCBs/cube, 8cubes/hypercube Hypercube architecture – Each 16-Proc chip a hyper-node Each proc has 4K bits of bit addressable RAM Distributed Physical Memory Global Memory Addresses Up to 4 front-end computers talk to sequencers via 4x4 crossbar “Sequencers” issue SIMD instructions over a Broadcast Network Bit procs communicate via 2D local HW grid connections (“NEWS”) Bit procs communicate via hypercube network using MSG passing Lots of Twinkling Lights!! 4
  • 6. CM-1 and CM-2 Programming ISA supports: Bit-oriented operations Arbitrary precision multi-bit scalar Ops using bit-serial implementation on bit procs Full Multi-Dimensional Vector Ops “Virtual Processor” idea similar to CUDA threadsbut they are statically allocated OS and Programming Tools run on front-ends *Lisp as the initial programming language Later C* and CM-Fortran 6
  • 7. CM-2 Improvements 1 Weitek IEEE FP coprocessor per 32 1-bit procs Up to 256K bits of memory per processor Added ECC to Memory Implemented the IO subsystem Up to 80 GByte RAID array called “Data Vault”uses 39 Striped Disks and ECC, plus spare disks on standby High Speed Graphics Output En-route MSG combining in H-Cube router New implementation of Multi-DimensionalNEWS on top of H-Cube (special addressing mode) 7
  • 9. CM-5 vs CM-1 and CM-2 Significant departure from CM-1 and CM-2 Targeted at more scientific and business applications More Commercial Off-The-Shelf components (“COTS”) Large Array of SPARC Processing Nodes 1-bit processors are abandoned Abandoned “NEWS” Grid and Hyper-Cube Networks Delivered 1024 node machine, with claims 16K nodes possible Even More Twinkling Lights! 9
  • 10. CM-5 Photo – Watch it Blink 10
  • 11. CM-5 Overall Architecture "Coordinated Homogeneous Array of RISC Processors“ or “CHARM” Asymmetric CoProcessors Model Large Array of Processor Nodes Small Collection of Control Nodes 2 Separate scalable networks One for data One for control and synchronization Still uses striped RAID for high disk BandWidth 11
  • 12. Division of Labor Processor Nodes can be assigned to a “Partition” One Control Node per Partition Control Node runs scalar code, then broadcasts parallel work to Processor Nodes Processor Nodes receive a program, not an instruction stream, have own Program Counter Processor nodes can access other node's memory by reading or writing a global memory address Processor Nodes also communicate via MSG passing Processor Nodes cannot issue system calls 12
  • 13. Control Nodes Full Sun Workstations Running UNIX Connected to the “Outside World” Handles Partition Time Sharing Connected to both data and control networks Performs System Diagnostics 13
  • 14. Processor Nodes Nodes are a 5-chip microprocessor Off the Shelf SPARC processor @ 40 MHz 32MBytes local node memory Multi-port memory controller for added BW “Caching techniques do not perform as well on large parallel machines” Proprietary 4-FPU Vector coprocessor Proprietary network controller 14
  • 15. CM-5 Processor Node Diagram 15
  • 16. Data Network Architecture Point to Point Inter-node communication and I/O Implemented as a Fat Tree Fat Trees invented by TMI employee Charles Leiserson Claim: Onsite BandWidth Expandable Delivering 5GB/sec Bisection BW on 1024 node machine Data router chip is a 8x8 crossbar switch Faulty nodes are mapped out of network Programs can not assume a network topology Network can be flushed when Time Share swaps occur Network, not processors, guarantee end to end delivery 16
  • 18. Separate Control Network Synchronization & control network Complete Binary Tree organization Provides broadcast capability Implements barrier operations Implements interrupts for timesharing Performs reduction operators (Sum, Max, AND, OR, Count, etc) 18
  • 19. CM-5 Programming Supports multiple Parallel High Level Languages and Programming Styles Including Data Parallel Model from CM-1 and CM-2 Goal: Hide many decisions from programmers CM-1, CM-2 vs CM-5 ISA changes Use of Processor Node CPU vs Vector CoProcessors Partition Wide Synchronizations generate by Compiler Is it MIMD, SPMD, SIMD? “Globally Synchronized MIMD” 19
  • 20. Sample CM Apps Machine Learning Neural Nets, concept clustering, genetic algorithms VLSI Design Geophysics (Oil Exploration), Plate Tectonics Particle Simulation Fluid Flow Simulation Computer Vision Computer Graphics , Animation Protein Sequence Matching Global Climate Model Simulation 20
  • 21. References Danny Hillis PhD: The Connection Machine Inc: The Rise and Fall of Thinking Machines Wiki: Connection Machine ACM: The CM-5 Connection Machine ACM: The Network Architecture of the CM-5 IEEE: Architecture and Applications of the Connection Machine IEEE: Fat-trees: universal networks for hardware-efficient supercomputing Encyclopedia of Computer Science and Technology 21