Copyright © 2015 Pearson Education, Inc. Chapter 2: Data Manipulation.

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Copyright © 2015 Pearson Education, Inc. Chapter 2: Data Manipulation

Copyright © 2015 Pearson Education, Inc. 2.1 Computer Architecture 2.2 Machine Language 2.3 Program Execution 2.4 Arithmetic/Logic Instructions 2.5 Communicating with Other Devices 2.6 Program Data Manipulation 2.7 Other Architectures Chapter 2: Data Manipulation 2-2

Copyright © 2015 Pearson Education, Inc. Central Processing Unit (CPU) or processor –Arithmetic/Logic unit versus Control unit –Registers General purpose Special purpose Bus Motherboard Computer Architecture 2-3

Copyright © 2015 Pearson Education, Inc. Figure 2.1 CPU and main memory connected via a bus 2-4

Copyright © 2015 Pearson Education, Inc. A program can be encoded as bit patterns and stored in main memory. From there, the CPU can then extract the instructions and execute them. In turn, the program to be executed can be altered easily. Stored Program Concept 2-5

Copyright © 2015 Pearson Education, Inc. Machine instruction: An instruction (or command) encoded as a bit pattern recognizable by the CPU Machine language: The set of all instructions recognized by a machine Terminology 2-6

Copyright © 2015 Pearson Education, Inc. Reduced Instruction Set Computing (RISC) –Few, simple, efficient, and fast instructions –Examples: PowerPC from Apple/IBM/Motorola and ARM Complex Instruction Set Computing (CISC) –Many, convenient, and powerful instructions –Example: Intel Machine Language Philosophies 2-7

Copyright © 2015 Pearson Education, Inc. Data Transfer: copy data from one location to another Arithmetic/Logic: use existing bit patterns to compute a new bit patterns Control: direct the execution of the program Machine Instruction Types 2-8

Copyright © 2015 Pearson Education, Inc. Figure 2.2 Adding values stored in memory 2-9

Copyright © 2015 Pearson Education, Inc. Figure 2.3 Dividing values stored in memory 2-10

Copyright © 2015 Pearson Education, Inc. Figure 2.4 The architecture of the machine described in Appendix C 2-11

Copyright © 2015 Pearson Education, Inc. Op-code: Specifies which operation to execute Operand: Gives more detailed information about the operation –Interpretation of operand varies depending on op-code Parts of a Machine Instruction 2-12

Copyright © 2015 Pearson Education, Inc. Figure 2.5 The composition of an instruction for the machine in Appendix C 2-13

Copyright © 2015 Pearson Education, Inc. Figure 2.6 Decoding the instruction 35A7 2-14

Copyright © 2015 Pearson Education, Inc. Figure 2.7 An encoded version of the instructions in Figure

Copyright © 2015 Pearson Education, Inc. Controlled by two special-purpose registers –Program counter: address of next instruction –Instruction register: current instruction Machine Cycle –Fetch –Decode –Execute Program Execution 2-16

Copyright © 2015 Pearson Education, Inc. Figure 2.8 The machine cycle 2-17

Copyright © 2015 Pearson Education, Inc. Figure 2.9 Decoding the instruction B

Copyright © 2015 Pearson Education, Inc. Figure 2.10 The program from Figure 2.7 stored in main memory ready for execution 2-19

Copyright © 2015 Pearson Education, Inc. Figure 2.11 Performing the fetch step of the machine cycle 2-20

Copyright © 2015 Pearson Education, Inc. Figure 2.11 Performing the fetch step of the machine cycle (continued) 2-21

Copyright © 2015 Pearson Education, Inc. Logic: AND, OR, XOR –Masking Rotate and Shift: circular shift, logical shift, arithmetic shift Arithmetic: add, subtract, multiply, divide –Precise action depends on how the values are encoded (two’s complement versus floating- point). Arithmetic/Logic Operations 2-22

Copyright © 2015 Pearson Education, Inc. Figure 2.12 Rotating the bit pattern 65 (hexadecimal) one bit to the right 2-23

Copyright © 2015 Pearson Education, Inc. Controller: An intermediary apparatus that handles communication between the computer and a device –Specialized controllers for each type of device –General purpose controllers (USB and FireWire) Port: The point at which a device connects to a computer Memory-mapped I/O: CPU communicates with peripheral devices as though they were memory cells Communicating with Other Devices 2-24

Copyright © 2015 Pearson Education, Inc. Figure 2.13 Controllers attached to a machine’s bus 2-25

Copyright © 2015 Pearson Education, Inc. Figure 2.14 A conceptual representation of memory-mapped I/O 2-26

Copyright © 2015 Pearson Education, Inc. Direct memory access (DMA): Main memory access by a controller over the bus Von Neumann Bottleneck: Insufficient bus speed impedes performance Handshaking: The process of coordinating the transfer of data between components Communicating with Other Devices (continued) 2-27

Copyright © 2015 Pearson Education, Inc. Parallel Communication: Several communication paths transfer bits simultaneously. Serial Communication: Bits are transferred one after the other over a single communication path. Communicating with Other Devices (continued) 2-28

Copyright © 2015 Pearson Education, Inc. Measurement units –Bps: Bits per second –Kbps: Kilo-bps (1,000 bps) –Mbps: Mega-bps (1,000,000 bps) –Gbps: Giga-bps (1,000,000,000 bps) Bandwidth: Maximum available rate Data Communication Rates 2-29

Copyright © 2015 Pearson Education, Inc. Programing languages shields users from details of the machine: –A single Python statement might map to one, tens, or hundreds of machine instructions –Programmer does not need to know if the processor is RISC or CISC –Assigning variables surely involves LOAD, STORE, and MOVE op-codes Programming Data Manipulation 2-30

Copyright © 2015 Pearson Education, Inc. print(bin(0b & 0b )) # Prints '0b ' print(bin(0b | 0b )) # Prints '0b ' print(bin(0b ^ 0b )) # Prints '0b ' Bitwise Problems as Python Code 2-31

Copyright © 2015 Pearson Education, Inc. If statement: if (water_temp > 140): print('Bath water too hot!') While statement: while (n < 10): print(n) n = n + 1 Control Structures 2-32

Copyright © 2015 Pearson Education, Inc. Function: A name for a series of operations that should be performed on the given parameter or parameters Function call: Appearance of a function in an expression or statement Functions 2-33 x = 1034 y = 1056 z = 2078 biggest = max(x, y, z) print(biggest)# Prints '2078'

Copyright © 2015 Pearson Education, Inc. Argument Value: A value plugged into a parameter Fruitful functions return a value void functions, or procedures, do not return a value Functions (continued) 2-34 sideA = 3.0 sideB = 4.0 # Calculate third side via Pythagorean Theorem hypotenuse = math.sqrt(sideA**2 + sideB**2) print(hypotenuse)

Copyright © 2015 Pearson Education, Inc. # Calculates the hypotenuse of a right triangle import math # Inputting the side lengths, first try sideA = int(input('Length of side A? ')) sideB = int(input('Length of side B? ')) # Calculate third side via Pythagorean Theorem hypotenuse = math.sqrt(sideA**2 + sideB**2) print(hypotenuse) Input / Output 2-35

Copyright © 2015 Pearson Education, Inc. # Marathon training assistant. import math # This function converts a number of minutes and # seconds into just seconds. def total_seconds(min, sec): return min * 60 + sec # This function calculates a speed in miles per hour given # a time (in seconds) to run a single mile. def speed(time): return 3600 / time Marathon Training Assistant 2-36

Copyright © 2015 Pearson Education, Inc. # Prompt user for pace and mileage. pace_minutes = int(input('Minutes per mile? ')) pace_seconds = int(input('Seconds per mile? ')) miles = int(input('Total miles? ')) # Calculate and print speed. mph = speed(total_seconds(pace_minutes, pace_seconds)) print('Your speed is ' + str(mph) + ' mph') # Calculate elapsed time for planned workout. total = miles * total_seconds(pace_minutes, pace_seconds) elapsed_minutes = total // 60 elapsed_seconds = total % 60 print('Your elapsed time is ' + str(elapsed_minutes) + ' mins ' + str(elapsed_seconds) + ' secs') Marathon Training Assistant (continued) 2-37

Copyright © 2015 Pearson Education, Inc. Figure 2.15 Example Marathon Training Data 2-38 Time Per Mile Total Elapsed Time MinutesSecondsMilesSpeed (mph)MinutesSeconds

Copyright © 2015 Pearson Education, Inc. Technologies to increase throughput: –Pipelining: Overlap steps of the machine cycle –Parallel Processing: Use multiple processors simultaneously SISD: No parallel processing MIMD: Different programs, different data SIMD: Same program, different data Other Architectures 0-39

Copyright © 2015 Pearson Education, Inc. EndofChapter