Sumit Mittu Assistant Professor, CSE/ITLovely Professional University   sumit.12735@lpu.co.in www.tinyurl.com/askSumit
What is this course all about                and    Why study this course?Sumit Mittu, Assistant Professor, CSE/IT, Lovely...
CSE539: Advanced Computer Architecture                                       Chapter 1             Parallel Computer Model...
In this chapter…•     THE STATE OF COMPUTING•     MULTIPROCESSORS AND MULTICOMPUTERS•     MULTIVECTOR AND SIMD COMPUTERS• ...
THE STATE OF COMPUTING                 Computer Development Milestones• How it all started…     o 500 BC: Abacus (China) –...
THE STATE OF COMPUTING                 Computer Development Milestones• First Generation (1945 – 54)     o Technology & Ar...
THE STATE OF COMPUTING                 Computer Development Milestones• Second Generation (1955 – 64)     o Technology & A...
THE STATE OF COMPUTING                 Computer Development Milestones• Third Generation (1965 – 74)     o Technology & Ar...
THE STATE OF COMPUTING                 Computer Development Milestones• Fourth Generation (1975 – 90)     o Technology & A...
THE STATE OF COMPUTING                 Computer Development Milestones• Fifth Generation (1991 onwards)     o Technology &...
THE STATE OF COMPUTING                        Elements of Modern Computers•     Computing Problems•     Algorithms and Dat...
THE STATE OF COMPUTING                Evolution of Computer Architecture• The study of computer architecture involves both...
THE STATE OF COMPUTING               Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Pr...
THE STATE OF COMPUTING                Evolution of Computer Architecture• Fig 1.3 Sumit Mittu, Assistant Professor, CSE/IT...
THE STATE OF COMPUTING               Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Pr...
THE STATE OF COMPUTING               Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Pr...
THE STATE OF COMPUTING                     System Attributes to Performance•     Machine Capability and Program Behaviour•...
THE STATE OF COMPUTING                     System Attributes to Performance•     Cycle Time (processor)                   ...
THE STATE OF COMPUTING                     System Attributes to Performance• MIPS Rate                 𝐼𝑐               𝑓 ...
THE STATE OF COMPUTING                  System Attributes to Performance• A benchmark program contains 450000 arithmetic  ...
THE STATE OF COMPUTING                   System Attributes to Performance                                                 ...
Multiprocessors and Multicomputers• Shared Memory Multiprocessors     o   The UMA Model     o   The NUMA Model     o   The...
Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   23
Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   24
Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   25
Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   26
Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   27
Multivector and SIMD Computers• Vector Processors     o Vector Processor Variants         • Vector Supercomputers         ...
Multivector and SIMD ComputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   29
Multivector and SIMD Computers• SIMD Supercomputers     o SIMD Machine Model            • S = < N, C, I, M, R >         • ...
Multivector and SIMD ComputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   31
PRAM and VLSI Models• Parallel Random Access Machines     o Time and Space Complexities         • Time complexity         ...
PRAM and VLSI ModelsSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   33
PRAM and VLSI Models• Parallel Random Access Machines     o PRAM Models     o PRAM Variants         • EREW-PRAM Model     ...
PRAM and VLSI Models• VLSI Complexity  Model     o The 𝑨𝑻 𝟐 Model         • Memory Bound           on Chip Area         • ...
Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   36
Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   37
Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University   38
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Aca2 01 new

  1. 1. Sumit Mittu Assistant Professor, CSE/ITLovely Professional University sumit.12735@lpu.co.in www.tinyurl.com/askSumit
  2. 2. What is this course all about and Why study this course?Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 2
  3. 3. CSE539: Advanced Computer Architecture Chapter 1 Parallel Computer ModelsBook: “Advanced Computer Architecture – Parallelism, Scalability, Programmability”, Hwang & Jotwani Sumit Mittu Assistant Professor, CSE/IT Lovely Professional University sumit.12735@lpu.co.in
  4. 4. In this chapter…• THE STATE OF COMPUTING• MULTIPROCESSORS AND MULTICOMPUTERS• MULTIVECTOR AND SIMD COMPUTERS• PRAM AND VLSI MODELS• ARCHITECTURAL DEVELOPMENT TRACKS Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 4
  5. 5. THE STATE OF COMPUTING Computer Development Milestones• How it all started… o 500 BC: Abacus (China) – The earliest mechanical computer/calculating device. • Operated to perform decimal arithmetic with carry propagation digit by digit o 1642: Mechanical Adder/Subtractor (Blaise Pascal) o 1827: Difference Engine (Charles Babbage) o 1941: First binary mechanical computer (Konrad Zuse; Germany) o 1944: Harvard Mark I (IBM) • The very first electromechanical decimal computer as proposed by Howard Aiken• Computer Generations o 1st 2nd 3rd 4th 5th o Division into generations marked primarily by changes in hardware and software technologies Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 5
  6. 6. THE STATE OF COMPUTING Computer Development Milestones• First Generation (1945 – 54) o Technology & Architecture: • Vacuum Tubes • Relay Memories • CPU driven by PC and accumulator • Fixed Point Arithmetic o Software and Applications: • Machine/Assembly Languages • Single user • No subroutine linkage • Programmed I/O using CPU o Representative Systems: ENIAC, Princeton IAS, IBM 701 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 6
  7. 7. THE STATE OF COMPUTING Computer Development Milestones• Second Generation (1955 – 64) o Technology & Architecture: • Discrete Transistors • Core Memories • Floating Point Arithmetic • I/O Processors • Multiplexed memory access o Software and Applications: • High level languages used with compilers • Subroutine libraries • Processing Monitor o Representative Systems: IBM 7090, CDC 1604, Univac LARC Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 7
  8. 8. THE STATE OF COMPUTING Computer Development Milestones• Third Generation (1965 – 74) o Technology & Architecture: • IC Chips (SSI/MSI) • Microprogramming • Pipelining • Cache • Look-ahead processors o Software and Applications: • Multiprogramming and Timesharing OS • Multiuser applications o Representative Systems: IBM 360/370, CDC 6600, T1-ASC, PDP-8 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 8
  9. 9. THE STATE OF COMPUTING Computer Development Milestones• Fourth Generation (1975 – 90) o Technology & Architecture: • LSI/VLSI • Semiconductor memories • Multiprocessors • Multi-computers • Vector supercomputers o Software and Applications: • Multiprocessor OS • Languages, Compilers and environment for parallel processing o Representative Systems: VAX 9000, Cray X-MP, IBM 3090 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 9
  10. 10. THE STATE OF COMPUTING Computer Development Milestones• Fifth Generation (1991 onwards) o Technology & Architecture: • Advanced VLSI processors • Scalable Architectures • Superscalar processors o Software and Applications: • Systems on a chip • Massively parallel processing • Grand challenge applications • Heterogeneous processing o Representative Systems: S-81, IBM ES/9000, Intel Paragon, nCUBE 6480, MPP, VPP500 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 10
  11. 11. THE STATE OF COMPUTING Elements of Modern Computers• Computing Problems• Algorithms and Data Structures• Hardware Resources• Operating System• System Software Support• Compiler Support Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 11
  12. 12. THE STATE OF COMPUTING Evolution of Computer Architecture• The study of computer architecture involves both the following: o Hardware organization o Programming/software requirements• The evolution of computer architecture is believed to have started with von Neumann architecture o Built as a sequential machine o Executing scalar data• Major leaps in this context came as… o Look-ahead, parallelism and pipelining o Flynn’s classification o Parallel/Vector Computers o Development Layers Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 12
  13. 13. THE STATE OF COMPUTING Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 13
  14. 14. THE STATE OF COMPUTING Evolution of Computer Architecture• Fig 1.3 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 14
  15. 15. THE STATE OF COMPUTING Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 15
  16. 16. THE STATE OF COMPUTING Evolution of Computer ArchitectureSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 16
  17. 17. THE STATE OF COMPUTING System Attributes to Performance• Machine Capability and Program Behaviour• Peak Performance• Turnaround time• Cycle Time, Clock Rate and Cycles Per Instruction (CPI)• Performance Factors o Instruction Count, Average CPI, Cycle Time, Memory Cycle Time and No. of memory cycles• System Attributes o Instruction Set Architecture, Compiler Technology, Processor Implementation and control, Cache and Memory Hierarchy• MIPS Rate, FLOPS and Throughput Rate• Programming Environments – Implicit and Explicit Parallelism Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 17
  18. 18. THE STATE OF COMPUTING System Attributes to Performance• Cycle Time (processor) 𝜏• Clock Rate 𝑓 = 1/𝜏• Average no. of cycles per instruction 𝐶𝑃𝐼• No. of instructions in program 𝐼𝑐• CPU Time 𝑇 = 𝐼 𝑐 × 𝐶𝑃𝐼 × 𝜏• Memory Cycle Time 𝑘𝜏• No. of Processor Cycles needed 𝑝• No. of Memory Cycles needed 𝑚• Effective CPU Time 𝑇 = 𝐼𝑐 × (𝑝 + 𝑚 × 𝑘) × 𝜏 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 18
  19. 19. THE STATE OF COMPUTING System Attributes to Performance• MIPS Rate 𝐼𝑐 𝑓 𝑓×𝐼 𝑐• 𝜏= = = 𝑇×106 𝐶𝑃𝐼×106 𝐶×106• Throughput Rate 𝑀𝐼𝑃𝑆×106 𝑓• 𝑊𝑝 = = 𝐼𝑐 𝐶𝑃𝐼×𝐼 𝑐 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 19
  20. 20. THE STATE OF COMPUTING System Attributes to Performance• A benchmark program contains 450000 arithmetic instructions, 320000 data transfer instructions and 230000 control transfer instructions. Each arithmetic instruction takes 1 clock cycle to execute whereas each data transfer and control transfer instruction takes 2 clock cycles to execute. On a 400 MHz processors, determine: o Effective no. of cycles per instruction (CPI) o Instruction execution rate (MIPS rate) o Execution time for this program Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 20
  21. 21. THE STATE OF COMPUTING System Attributes to Performance Performance Factors Instruction Average Cycles per Instruction (CPI) Processor Cycle Count (Ic) Time (𝜏) Processor Memory Memory Access Cycles per References per Latency (k)System Instruction Instruction (m)Attributes (CPI and p)Instruction-setArchitectureCompilerTechnologyProcessorImplementationand ControlCache andMemoryHierarchy Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 21
  22. 22. Multiprocessors and Multicomputers• Shared Memory Multiprocessors o The UMA Model o The NUMA Model o The COMA Model o The CC-NUMA Model• Distributed-Memory Multicomputers o The NORMA Machines o Message Passing multicomputers• Taxonomy of MIMD Computers• Representative Systems o Multiprocessors: BBN TC-200, MPP, S-81, IBM ES/9000 Model 900/VF, o Multicomputers: Intel Paragon XP/S, nCUBE/2 6480, SuperNode 1000, CM5, KSR-1 Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 22
  23. 23. Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 23
  24. 24. Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 24
  25. 25. Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 25
  26. 26. Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 26
  27. 27. Multiprocessors and MulticomputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 27
  28. 28. Multivector and SIMD Computers• Vector Processors o Vector Processor Variants • Vector Supercomputers • Attached Processors o Vector Processor Models/Architectures • Register-to-register architecture • Memory-to-memory architecture o Representative Systems: • Cray-I • Cray Y-MP (2,4, or 8 processors with 16Gflops peak performance) • Convex C1, C2, C3 series (C3800 family with 8 processors, 4 GB main memory, 2 Gflops peak performance) • DEC VAX 9000 (pipeline chaining support) Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 28
  29. 29. Multivector and SIMD ComputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 29
  30. 30. Multivector and SIMD Computers• SIMD Supercomputers o SIMD Machine Model • S = < N, C, I, M, R > • N: No. of PEs in the machine • C: Set of instructions (scalar/program flow) directly executed by control unit • I: Set of instructions broadcast by CU to all PEs for parallel execution • M: Set of masking schemes • R: Set of data routing functions o Representative Systems: • MasPar MP-1 (1024 to 16384 PEs) • CM-2 (65536 PEs) • DAP600 Family (up to 4096 PEs) • Illiac-IV (64 PEs) Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 30
  31. 31. Multivector and SIMD ComputersSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 31
  32. 32. PRAM and VLSI Models• Parallel Random Access Machines o Time and Space Complexities • Time complexity • Space complexity • Serial and Parallel complexity • Deterministic and Non-deterministic algorithm o PRAM • Developed by Fortune and Wyllie (1978) • Objective: o Modelling idealized parallel computers with zero synchronization or memory access overhead • An n-processor PRAM has a globally addressable Memory Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 32
  33. 33. PRAM and VLSI ModelsSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 33
  34. 34. PRAM and VLSI Models• Parallel Random Access Machines o PRAM Models o PRAM Variants • EREW-PRAM Model • CREW-PRAM Model • ERCW-PRAM Model • CRCW-PRAM Model o Discrepancy with Physical Models • Most popular variants: EREW and CRCW • SIMD machine with shared architecture is closest architecture modelled by PRAM • PRAM Allows different instructions to be executed on different processors simultaneously. Thus, PRAM really operates in synchronized MIMD mode with shared memory Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 34
  35. 35. PRAM and VLSI Models• VLSI Complexity Model o The 𝑨𝑻 𝟐 Model • Memory Bound on Chip Area • I/O Bound on Volume 𝑨𝑻 • Bisection Communication Bound (Cross- section area) 𝑨 𝑻 • Square of this area used as lower bound Sumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 35
  36. 36. Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 36
  37. 37. Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 37
  38. 38. Architectural Development TracksSumit Mittu, Assistant Professor, CSE/IT, Lovely Professional University 38
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