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Computer Organization & Design

Computer Organization & Design. The importance of computer organization. Why should a computer scientist study computer organization? You probably won’t be designing hardware, but … … you might work on embedded systems … you could be designing compilers

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Computer Organization & Design

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  1. Computer Organization & Design

  2. The importance of computer organization • Why should a computer scientist study computer organization? • You probably won’t be designing hardware, but … • … you might work on embedded systems • … you could be designing compilers • … you want your software to perform well • In all of these cases, you need to understand the hardware!

  3. What is a computer? • From The Dictionarys: • “One who computes” • We could argue that people are computers • “A device that computes, especially a programmable electronic machine that performs high-speed mathematical or logical operations that assembles, stores, correlates, or otherwise processes information.” • Anything from a simple abacus to the microprocessor-based computers of today

  4. The Computer Revolution • Progress in computer technology • Underpinned by Moore’s Law • Makes novel applications feasible • Computers in automobiles • Cell phones • Human genome project • World Wide Web • Search Engines • Computers are pervasive

  5. Classes of Computers • Desktop computers • General purpose, variety of software • Subject to cost/performance tradeoff • Server computers • Network based • High capacity, performance, reliability • Range from small servers to building sized • Embedded computers • Hidden as components of systems • Stringent power/performance/cost constraints

  6. CIS 273: Lecture 1

  7. What You Will Learn • How programs are translated into the machine language • And how the hardware executes them • The hardware/software interface • What determines program performance • And how it can be improved • How hardware designers improve performance • What is parallel processing Chapter 1 — Computer Abstractions and Technology — 8

  8. Understanding Performance • Algorithm • Determines number of operations executed • Programming language, compiler, architecture • Determine number of machine instructions executed per operation • Processor and memory system • Determine how fast instructions are executed • I/O system (including OS) • Determines how fast I/O operations are executed Chapter 1 — Computer Abstractions and Technology — 9

  9. Below Your Program • Application software • Written in high-level language • System software • Compiler: translates HLL code to machine code • Operating System: service code • Handling input/output • Managing memory and storage • Scheduling tasks & sharing resources • Hardware • Processor, memory, I/O controllers §1.2 Below Your Program Chapter 1 — Computer Abstractions and Technology — 10

  10. Levels of Program Code • High-level language • Level of abstraction closer to problem domain • Provides for productivity and portability • Assembly language • Textual representation of instructions • Hardware representation • Binary digits (bits) • Encoded instructions and data • using English words • according to their intended use • less time to develop programs • programs to be independent of the computer

  11. Components of a Computer • Same components forall kinds of computer • Desktop, server,embedded • Input/output includes • User-interface devices • Display, keyboard, mouse • Storage devices • Hard disk, CD/DVD, flash • Network adapters • For communicating with other computers The BIG Picture

  12. Components of a computer CIS 273: Lecture 1

  13. Anatomy of a Mouse • Optical mouse • LED illuminates desktop • Small low-res camera • Basic image processor • Looks for x, y movement • Buttons & wheel • Supersedes roller-ball mechanical mouse Chapter 1 — Computer Abstractions and Technology — 14

  14. Through the Looking Glass • LCD screen: picture elements (pixels) • Mirrors content of frame buffer memory Chapter 1 — Computer Abstractions and Technology — 15

  15. Inside the AMD Barcelona microprocessor • Cache memory (SRAM vs DRAM)

  16. Abstractions • Abstraction helps us deal with complexity • Hide lower-level detail • Instruction set architecture (ISA) • The hardware/software interface • Application binary interface • The ISA plus system software interface • Implementation • The details underlying and interface The BIG Picture

  17. A Safe Place for Data • Volatile main memory • Loses instructions and data when power off • Non-volatile secondary memory • Magnetic disk • Flash memory • Optical disk (CDROM, DVD) Chapter 1 — Computer Abstractions and Technology — 18

  18. Networks • Network • Communication • Resource sharing • Nonlocal access • Local area network (LAN): Ethernet • Within a building • Wide area network (WAN: the Internet • Wireless network: WiFi, Bluetooth Chapter 1 — Computer Abstractions and Technology — 19

  19. Technologies for Building Processors and Memory

  20. Technology Trends • Electronics technology continues to evolve • Increased capacity and performance • Reduced cost DRAM capacity Chapter 1 — Computer Abstractions and Technology — 21

  21. Defining Performance • What is Performance • Which airplane has the best performance?

  22. Response Time and Throughput • Response time (execution time) • How long it takes to do a task • Throughput (bandwidth) • Total work done per unit time • e.g., tasks/transactions/… per hour • How are response time and throughput affected by • Replacing the processor with a faster version? • Adding more processors? • We’ll focus on response time for now…

  23. Defining Performance

  24. Relative Performance • Example: time taken to run a program • 10s on A, 15s on B • Execution TimeB / Execution TimeA • = 15s / 10s = 1.5 • So A is 1.5 times faster than B

  25. Measuring Performance • Wall clock time, response time or elapsed time • CPU execution time Also called CPU time. • The actual time the CPU spends computing for a specific task. • 1. user CPU time The • CPU time spent in a program itself. • 2. system CPU time • The CPU time spent in the operating system performing tasks on behalf of the program. System performance CPU Performance

  26. CPU Clocking • Operation of digital hardware governed by a constant-rate clock Clock period Clock (cycles) Data transferand computation Update state • 1. Clock period: duration of a clock cycle • e.g., 250ps = 0.25ns = 250×10–12s • 2. Clock frequency (rate): cycles per second • e.g., 4.0GHz = 4000MHz = 4.0×109Hz

  27. CPU Performance and Its Factors • Performance improved by • Reducing number of clock cycles • Increasing clock rate • Hardware designer must often trade off clock rate against cycle count

  28. CPU Time Example • Computer A: 2GHz clock, 10s CPU time • Designing Computer B • Aim for 6s CPU time • Can do faster clock, but causes 1.2 × clock cycles • How fast must Computer B clock be?

  29. CPU Performance and Its Factors Example: Improving Performance

  30. Instruction Performance CPI • Instruction Count for a program • Determined by program, ISA and compiler • Average cycles per instruction (CPI) • Determined by CPU hardware • If different instructions have different CPI • Average CPI affected by instruction mix

  31. CPI Example • Computer A: Cycle Time = 250ps, CPI = 2.0 • Computer B: Cycle Time = 500ps, CPI = 1.2 • Same ISA • Which is faster, and by how much?

  32. Instruction Performance Example: Using the Performance Equation

  33. The Classic CPU Performance Equation

  34. CPI in More Detail • If different instruction classes take different numbers of cycles • Weighted average CPI Relative frequency

  35. CPI Example • Alternative compiled code sequences using instructions in classes A, B, C • Sequence 1: IC = 5 • Clock Cycles= 2×1 + 1×2 + 2×3= 10 • Avg. CPI = 10/5 = 2.0 • Sequence 2: IC = 6 • Clock Cycles= 4×1 + 1×2 + 1×3= 9 • Avg. CPI = 9/6 = 1.5 Chapter 1 — Computer Abstractions and Technology — 36

  36. Performance Summary • How can we determine the value of these factors? • Performance depends on • Algorithm: affects IC, possibly CPI • Programming language: affects IC, CPI • Compiler: affects IC, CPI • Instruction set architecture: affects IC, CPI, Tc The BIG Picture Chapter 1 — Computer Abstractions and Technology — 37

  37. Power wall ×30 5V → 1V ×1000 How could clock rates grow by a factor of 1000 while power grew by only a factor of 30?

  38. Relative Power • Suppose a new CPU has • 85% of capacitive load of old CPU • 15% voltage and 15% frequency reduction • The power wall • We can’t reduce voltage further • We can’t remove more heat • How else can we improve performance?

  39. leakage • leakage is typically responsible for 40% of the power consumption in 2008 • increasing the number of transistors increases power dissipation, even if the transistors are always off.

  40. The sea change! Constrained by power, instruction-level parallelism, memory latency

  41. Multicore In the past, programmers could rely on innovations in hardware, architecture, and compilers to double performance of their programs every 18 months without having to change a line of code.

  42. Multiprocessors • Multicore microprocessors • More than one processor per chip • Requires explicitly parallel programming • Compare with instruction level parallelism • Hardware executes multiple instructions at once • Hidden from the programmer • Hard to do • Programming for performance • Load balancing • Optimizing communication and synchronization Chapter 1 — Computer Abstractions and Technology — 43

  43. Real Stuff: Manufacturing andBenchmarking the AMD Opteron X4 • manufacture of a chip : silicon (semiconductor) • Excellent conductors of electricity • Excellent insulators from electricity • Areas that can conduct or insulate under special conditions • A VLSI circuit • `

  44. The manufacturing process for IC

  45. AMD Opteron X2 Wafer • X2: 300mm wafer, 117 chips, 90nm technology • X4: 45nm technology Chapter 1 — Computer Abstractions and Technology — 46

  46. The cost of an integrated

  47. SPEC CPU Benchmark • Programs used to measure performance • Supposedly typical of actual workload • Standard Performance Evaluation Corp (SPEC) • Develops benchmarks for CPU, I/O, Web, … • SPEC CPU2006 • Elapsed time to execute a selection of programs • Negligible I/O, so focuses on CPU performance • Normalize relative to reference machine • Summarize as geometric mean of performance ratios • CINT2006 (integer 12) and CFP2006 (floating-point 17) Chapter 1 — Computer Abstractions and Technology — 48

  48. CINT2006 for Opteron X4 2356 High cache miss rates Chapter 1 — Computer Abstractions and Technology — 49

  49. SPEC Power Benchmark • Power consumption of server at different workload levels • Performance: ssj_ops/sec • Power: Watts (Joules/sec) Chapter 1 — Computer Abstractions and Technology — 50

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