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Computer Arithmetic: Number Representation and Arithmetic Operations

This lecture focuses on number representation and techniques for implementing arithmetic operations in computer architecture. It covers both integer and floating-point arithmetic. The lecture discusses decimal and binary number systems, integer representation, sign-magnitude representation, two's complement representation, and addition/subtraction operations.

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Computer Arithmetic: Number Representation and Arithmetic Operations

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  1. CS 447 – Computer Architecture Lecture 2Computer Arithmetic (1) August 29, 2007 Karem Sakallah ksakalla@qatar.cmu.edu www.qatar.cmu.edu/~msakr/15447-f07/

  2. Chapter objectives In this lecture we will focus on the representation of numbers and techniques for implementing arithmetic operations. Processors typically support two types of arithmetic: integer, or fixed point, and floating point. For both cases, the lecture first examines the representation of numbers and then discusses arithmetic operations.

  3. Arithmetic & Logic Unit • Does the calculations • Everything else in the computer is there to service this unit • Handles integers • May handle floating point (real) numbers • May be separate (maths co-processor)

  4. ALU Inputs and Outputs

  5. d3 d7 d5 d0 d4 d1 d6 d2 0 2 7 9 0 0 0 3 107 103 104 101 105 100 106 102 Review: Decimal Numbers • Integer Representation • number is sum of DIGIT * “place value” Range 0 to 10n - 1 379210 = 3  103 + 7  102 + 9  101 + 2  100 = 3000 + 700 + 90 + 2

  6. 3792 + 531 ??? 1 “carry 1” because 9+3 = 12 0 4 3 2 3 Review: Decimal Numbers • Adding two decimal numbers • add by “place value”, one digit at a time 3 7 9 2 + 0 5 3 1

  7. b5 b6 b0 b7 b3 b1 b4 b2 1 0 0 0 1 0 0 1 26 23 24 22 21 20 25 27 Binary Numbers • Humans can naturally count up to 10 values, but computers can count only up to 2 values (0 and 1) • (Unsigned) Binary Integer Representation “base” of place values is 2, not 10 011001002 = 26 + 25 + 22 = 64 + 32 + 4 = 10010 Range 0 to 2n - 1

  8. Binary Representation If a number is represented in n = 8-bits Value in Binary: Value in Decimal:27.a7 + 26.a6 + 25.a5 + 24.a4 + 23.a3 + 22.a2 + 21.a1 + 20.a0 Value in Binary: Value in Decimal:2n-1.an-1 + 2n-2.an-2 + … + 24.a4 + 23.a3 + 22.a2 + 21.a1 + 20.a0

  9. Binary Arithmetic • Add up to 3 bits at a time per place value • A and B • “carry in” • Output 2 bits at a time • sum bit for that place value • “carry out” bit(becomes carry-in of next bit) • Can be done using a function with 3 inputs, 2 outputs carry-in bits 1 1 1 0 0 A bits 1 1 1 0 B bits + 0 1 1 1 sum bits 0 1 0 1 carry-out bits 1 1 1 1 0 B A FA carry out carry in sum

  10. Integer Representation • Only have 0 & 1 to represent everything • Positive numbers stored in binary • e.g. 41=00101001 • No minus sign • No period • Sign-Magnitude • Two’s complement

  11. Sign-Magnitude • Problems: • Need to consider both sign and magnitude in arithmetic • Two representations of zero (+0 and -0) • Left most bit is sign bit • 0 means positive • 1 means negative • +18 = 00010010 • -18 = 10010010

  12. Two’s Complement • -3 = 11111101 • -2 = 11111110 • -1 = 11111111 • -0 = 00000000 • +3 = 00000011 • +2 = 00000010 • +1 = 00000001 • +0 = 00000000

  13. Two’s Complement If a number is represented in n = 8-bits Value in Binary: Value in Decimal:27.a7 + 26.a6 + 25.a5 + 24.a4 + 23.a3 + 22.a2 + 21.a1 + 20.a0 • +3 = 00000011 • +2 = 00000010 • +1 = 00000001 • +0 = 00000000 • -3 = 11111101 • -2 = 11111110 • -1 = 11111111 • -0 = 00000000

  14. Benefits • One representation of zero • Arithmetic works easily (see later) • Negating is fairly easy • 3 = 00000011 • Boolean complement gives 11111100 • Add 1 to LSB 11111101

  15. -1 0 +1 -2 1111 0000 1110 0001 -3 +2 + 1101 0010 -4 +3 1100 0011 0 100 = + 4 -5 1011 +4 1 100 = - 4 0100 1010 0101 -6 +5 - 1001 0110 +6 -7 1000 0111 +7 -8 2's complement • Only one representation for 0 • One more negative number than positive numbers

  16. Geometric Depiction of Two’s Complement Integers

  17. Negation Special Case 1 • 0 = 00000000 • Bitwise NOT 11111111 • Add 1 to LSB +1 • Result 1 00000000 • Overflow is ignored, so: • - 0 = 0 

  18. Negation Special Case 2 • -128 = 10000000 • bitwise NOT 01111111 • Add 1 to LSB +1 • Result 10000000 • So: • -(-128) = -128 X • Monitor MSB (sign bit) • It should change during negation

  19. Range of Numbers • 8 bit 2’s complement • +127 = 01111111 = 27 -1 • -128 = 10000000 = -27 • 16 bit 2’s complement • +32767 = 011111111 11111111 = 215 - 1 • -32768 = 100000000 00000000 = -215

  20. Conversion Between Lengths • Positive number pack with leading zeros • +18 = 00010010 • +18 = 00000000 00010010 • Negative numbers pack with leading ones • -18 = 10010010 • -18 = 11111111 10010010 • i.e. pack with MSB (sign bit)

  21. Addition and Subtraction • Normal binary addition • Monitor sign bit for overflow • Take two’s complement of subtrahend and add to minuend • i.e. a - b = a + (-b) • So we only need addition and complement circuits

  22. 0 0 1 1 +1 0 1 1 1 1 1 0 0 1 0 1 +1 1 0 1 1 0 0 1 0 010110101011 flip +1 Binary Subtraction • 2’s complement subtraction: add negative 5 - 3 = 2 0101 001111001101 flip +1 2 ignoreoverflow -3 in 2’s complement form 3 - 5 = -2 0011 -2 00010010 flip -5 in 2’s complement form +1 (flip+1 also gives positive of negative number)

  23. Hardware for Addition and Subtraction

  24. Multiplication • Complex • Work out partial product for each digit • Take care with place value (column) • Add partial products

  25. Multiplication Example • 1011 Multiplicand (11 dec) • x 1101 Multiplier (13 dec) • 1011 Partial products • 0000 Note: if multiplier bit is 1 copy • 1011 multiplicand (place value) • 1011 otherwise zero • 10001111 Product (143 dec) • Note: need double length result

  26. Unsigned Binary Multiplication

  27. Execution of Example

  28. Flowchart for Unsigned Binary Multiplication

  29. Multiplying Negative Numbers • This does not work! • Solution 1 • Convert to positive if required • Multiply as above • If signs were different, negate answer • Solution 2 • Booth’s algorithm

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