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COMPUTER ORGANIZATION AND DESIGN 6th Edition The Hardware/Software Interface Chapter 1 Computer Abstractions and Technology  §1.1 Introduction The Computer Revolution...

COMPUTER ORGANIZATION AND DESIGN 6th Edition The Hardware/Software Interface Chapter 1 Computer Abstractions and Technology  §1.1 Introduction The Computer Revolution ◼ Progress in computer technology ◼ Underpinned by domain-specific accelerators ◼ Makes novel applications feasible ◼ Computers in automobiles ◼ Cell phones ◼ Human genome project ◼ World Wide Web ◼ Search Engines ◼ Computers are pervasive Chapter 1 — Computer Abstractions and Technology — 2 Classes of Computers ◼ Personal 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 Chapter 1 — Computer Abstractions and Technology — 3 Classes of Computers ◼ Supercomputers ◼ Type of server ◼ High-end scientific and engineering calculations ◼ Highest capability but represent a small fraction of the overall computer market ◼ Embedded computers ◼ Hidden as components of systems ◼ Stringent power/performance/cost constraints Chapter 1 — Computer Abstractions and Technology — 4 The PostPC Era Chapter 1 — Computer Abstractions and Technology — 5 The PostPC Era ◼ Personal Mobile Device (PMD) ◼ Battery operated ◼ Connects to the Internet ◼ Hundreds of dollars ◼ Smart phones, tablets, electronic glasses ◼ Cloud computing ◼ Warehouse Scale Computers (WSC) ◼ Software as a Service (SaaS) ◼ Portion of software run on a PMD and a portion run in the Cloud ◼ Amazon and Google Chapter 1 — Computer Abstractions and Technology — 6 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 — 7 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 — 8  §1.2 Seven Great Ideas in Computer Architecture Seven Great Ideas ◼ Use abstraction to simplify design ◼ Make the common case fast ◼ Performance via parallelism ◼ Performance via pipelining ◼ Performance via prediction ◼ Hierarchy of memories ◼ Dependability via redundancy Chapter 1 — Computer Abstractions and Technology — 9  §1.3 Below Your Program 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 Chapter 1 — Computer Abstractions and Technology — 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 Chapter 1 — Computer Abstractions and Technology — 11  §1.4 Under the Covers Components of a Computer The BIG Picture ◼ Same components for all 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 Chapter 1 — Computer Abstractions and Technology — 12 Inside the Processor (CPU) ◼ Datapath: performs operations on data ◼ Control: sequences datapath, memory,... ◼ Cache memory ◼ Small fast SRAM memory for immediate access to data Chapter 1 — Computer Abstractions and Technology — 13 Abstractions The BIG Picture ◼ 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 Chapter 1 — Computer Abstractions and Technology — 14 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 — 15 Networks ◼ Communication, resource sharing, nonlocal access ◼ Local area network (LAN): Ethernet ◼ Wide area network (WAN): the Internet ◼ Wireless network: WiFi, Bluetooth Chapter 1 — Computer Abstractions and Technology — 16  §1.5 Technologies for Building Processors and Memory Technology Trends ◼ Electronics technology continues to evolve ◼ Increased capacity and performance ◼ Reduced cost DRAM capacity Year Technology Relative performance/cost 1951 Vacuum tube 1 1965 Transistor 35 1975 Integrated circuit (IC) 900 1995 Very large scale IC (VLSI) 2,400,000 2013 Ultra large scale IC 250,000,000,000 Chapter 1 — Computer Abstractions and Technology — 17 Semiconductor Technology ◼ Silicon: semiconductor ◼ Add materials to transform properties: ◼ Conductors ◼ Insulators ◼ Switch Chapter 1 — Computer Abstractions and Technology — 18  §1.6 Performance Defining Performance ◼ Which airplane has the best performance? Chapter 1 — Computer Abstractions and Technology — 19 Response Time and Throughput ◼ Response time ◼ How long it takes to do a task ◼ Throughput ◼ 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… Chapter 1 — Computer Abstractions and Technology — 20 Relative Performance ◼ Define Performance = 1/Execution Time ◼ “X is n time faster than Y” Performanc e X Performanc e Y = Execution time Y Execution time X = n ◼ 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 Chapter 1 — Computer Abstractions and Technology — 21 Measuring Execution Time ◼ Elapsed time ◼ Total response time, including all aspects ◼ Processing, I/O, OS overhead, idle time ◼ Determines system performance ◼ CPU time ◼ Time spent processing a given job ◼ Discounts I/O time, other jobs’ shares ◼ Comprises user CPU time and system CPU time ◼ Different programs are affected differently by CPU and system performance Chapter 1 — Computer Abstractions and Technology — 22 CPU Clocking ◼ Operation of digital hardware governed by a constant-rate clock Clock period Clock (cycles) Data transfer and computation Update state ◼ Clock period: duration of a clock cycle ◼ e.g., 250ps = 0.25ns = 250×10–12s ◼ Clock frequency (rate): cycles per second ◼ e.g., 4.0GHz = 4000MHz = 4.0×109Hz Chapter 1 — Computer Abstractions and Technology — 23 CPU Time CPU Time = CPU Clock Cycles  Clock Cycle Time CPU Clock Cycles = Clock Rate ◼ Performance improved by ◼ Reducing number of clock cycles ◼ Increasing clock rate ◼ Hardware designer must often trade off clock rate against cycle count Chapter 1 — Computer Abstractions and Technology — 24 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? Clock Cycles B 1.2  Clock Cycles A Clock Rate B = = CPU Time B 6s Clock Cycles A = CPU Time A  Clock Rate A = 10s  2GHz = 20  109 1.2  20  109 24  109 Clock Rate B = = = 4GHz 6s 6s Chapter 1 — Computer Abstractions and Technology — 25 Instruction Count and CPI Clock Cycles = Instructio n Count  Cycles per Instructio n CPU Time = Instructio n Count  CPI  Clock Cycle Time Instructio n Count  CPI = Clock Rate ◼ Instruction Count for a program ◼ Determined by program, ISA and compiler ◼ Average cycles per instruction ◼ Determined by CPU hardware ◼ If different instructions have different CPI ◼ Average CPI affected by instruction mix Chapter 1 — Computer Abstractions and Technology — 26 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? CPU Time = Instructio n Count  CPI  Cycle Time A A A = I  2.0  250ps = I  500ps A is faster… CPU Time = Instructio n Count  CPI  Cycle Time B B B = I  1.2  500ps = I  600ps CPU Time B = I  600ps = 1.2 …by this much CPU Time I  500ps A Chapter 1 — Computer Abstractions and Technology — 27  CPI in More Detail ◼ If different instruction classes take different numbers of cycles n Clock Cycles =  (CPIi  Instructio n Count i ) i=1 ◼ Weighted average CPI Clock Cycles n  Instructio n Count i  CPI = =   CPIi   Instructio n Count i=1  Instructio n Count  Relative frequency Chapter 1 — Computer Abstractions and Technology — 28 CPI Example ◼ Alternative compiled code sequences using instructions in classes A, B, C Class A B C CPI for class 1 2 3 IC in sequence 1 2 1 2 IC in sequence 2 4 1 1 ◼ Sequence 1: IC = 5 ◼ Sequence 2: IC = 6 ◼ Clock Cycles ◼ Clock Cycles = 2×1 + 1×2 + 2×3 = 4×1 + 1×2 + 1×3 = 10 =9 ◼ Avg. CPI = 10/5 = 2.0 ◼ Avg. CPI = 9/6 = 1.5 Chapter 1 — Computer Abstractions and Technology — 29 Performance Summary The BIG Picture Instructio ns Clock cycles Seconds CPU Time =   Program Instructio n Clock cycle ◼ Performance depends on ◼ Algorithm: affects IC, possibly CPI ◼ Programming language: affects IC, CPI ◼ Compiler: affects IC, CPI ◼ Instruction set architecture: affects IC, CPI, Tc Chapter 1 — Computer Abstractions and Technology — 30  §1.7 The Power Wall Power Trends ◼ In CMOS IC technology Power = Capacitive load  Voltage 2  Frequency ×30 5V → 1V ×1000 Chapter 1 — Computer Abstractions and Technology — 31 Reducing Power ◼ Suppose a new CPU has ◼ 85% of capacitive load of old CPU ◼ 15% voltage and 15% frequency reduction Pnew Cold  0.85  (Vold  0.85) 2  Fold  0.85 = 2 = 0.85 4 = 0.52 Pold Cold  Vold  Fold ◼ The power wall ◼ We can’t reduce voltage further ◼ We can’t remove more heat ◼ How else can we improve performance? Chapter 1 — Computer Abstractions and Technology — 32 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 — 33  §1.12 Concluding Remarks Concluding Remarks ◼ Cost/performance is improving ◼ Due to underlying technology development ◼ Hierarchical layers of abstraction ◼ In both hardware and software ◼ Instruction set architecture ◼ The hardware/software interface ◼ Execution time: the best performance measure ◼ Power is a limiting factor ◼ Use parallelism to improve performance Chapter 1 — Computer Abstractions and Technology — 34