Chapter 10 - Computer Arithmetic
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1 Chapter 10 - Computer Arithmetic Luis Tarrataca luis.tarrataca@gmail.com CEFET-RJ L. Tarrataca Chapter 10 - Computer Arithmetic 1 / 102
2 1 Motivation 2 Arithmetic and Logic Unit 3 Integer representation Sign-Magnitude Representation Twos Complement Representation Range Extension L. Tarrataca Chapter 10 - Computer Arithmetic 2 / 102
3 4 Integer Arithmetic Negation Addition Subtraction Hardware Block Diagram for Adder Multiplication Unsigned Integers Twos complement multiplication 5 Floating-point representation L. Tarrataca Chapter 10 - Computer Arithmetic 3 / 102
4 Motivation Motivation How can a computer perform arithmetic operations? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 4 / 102
5 Motivation How can a computer perform arithmetic operations? Any ideas? Well, it depends on the type of numbers: integer and floating point; Representation is a crucial design issue... Guess what we will be seeing next ;) L. Tarrataca Chapter 10 - Computer Arithmetic 5 / 102
6 Arithmetic and Logic Unit What is the computer component responsible for calculations? ideas? Any L. Tarrataca Chapter 10 - Computer Arithmetic 6 / 102
7 Arithmetic and Logic Unit Arithmetic and Logic Unit What is the computer component responsible for calculations? ideas? Any Arithmetic Logic Unit Component that performs arithmetic and logical operations; All other system components are there mainly to: Bring data into the ALU; Process the data; Take the results back out; L. Tarrataca Chapter 10 - Computer Arithmetic 7 / 102
8 Arithmetic and Logic Unit What is the general organization of the ALU? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 8 / 102
9 Arithmetic and Logic Unit Very generally: Figure: ALU Inputs and outputs (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 9 / 102
10 Arithmetic and Logic Unit Operands for arithmetic/logic operations are provided in registers; The results of an operation are also stored in registers; ALU may also set flags as the result of an operation, e.g.: Overflow flag is set to 1: If a result exceeds the length of the register into which it is to be stored. Zero flag is set to 1: If a result produces value zero (JMP.Z, JMP.NZ, etc...) Flags are also stored in registers within the processor. Processor provides signals that control: ALU operation; Data movement into and out of the ALU. L. Tarrataca Chapter 10 - Computer Arithmetic 10 / 102
11 Arithmetic and Logic Unit Figure: Expanded Structure of a computer (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 11 / 102
12 Integer representation Integer representation An n-bit sequence a n 1 a n 2 a 0 is an unsigned integer A: n 1 A = 2 i a i i=0 But what if we have to express negative numbers. Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 12 / 102
13 Integer representation Sign-Magnitude Representation Sign-Magnitude Representation The number sign can be represented using the leftmost bit: If bit is 0, the number is positive; If bit is 1, the number is negative; L. Tarrataca Chapter 10 - Computer Arithmetic 13 / 102
14 Integer representation Sign-Magnitude Representation The number sign can be represented using the leftmost bit: If bit is 0, the number is positive; If bit is 1, the number is negative; Can you see any problems with this method? L. Tarrataca Chapter 10 - Computer Arithmetic 14 / 102
15 Integer representation Sign-Magnitude Representation There are several problems in fact: Addition and subtraction operations require: Considering both signs and the magnitudes of each number; There are two representations of 0: We need to test for two cases representing zero; This operation is frequently used in computers... Because of these drawbacks sign-magnitude representation is rarely use... L. Tarrataca Chapter 10 - Computer Arithmetic 15 / 102
16 Integer representation Sign-Magnitude Representation So what can we use to represent integers? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 16 / 102
17 Integer representation Twos Complement Representation Twos Complement Representation Like the sign magnitude system: uses the most significant bit as a sign bit; easy to test whether an integer is positive or negative However, it differs from the use of the sign-magnitude representation: in the way that the other bits are interpreted. L. Tarrataca Chapter 10 - Computer Arithmetic 17 / 102
18 Integer representation Twos Complement Representation Key characteristics of twos complement representation and arithmetic: Figure: Characteristics of twos complement representation and arithmetic (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 18 / 102
19 Integer representation Twos Complement Representation Consider an n-bit integer, A, in twos complement: If A is positive, then the sign bit, a n 1, is zero; Remaining bits represent number magnitude: n 2 A = 2 i a i, for A 0 i=0 Zero is identified as positive (zero sign bit) and a magnitude of all 0s; Range of positive integers that may be represented is: from 0 (all of the magnitude bits are 0)... through 2 n 1 1 (all of the magnitude bits are 1). L. Tarrataca Chapter 10 - Computer Arithmetic 19 / 102
20 Integer representation Twos Complement Representation A negative number A has the sign bit, a n 1, set to one: Remaining n 1 bits can take on any one of 2 n 1 values Therefore, range is from 1 to 2 n 1 ; L. Tarrataca Chapter 10 - Computer Arithmetic 20 / 102
21 Integer representation Twos Complement Representation Ideally: the negative numbers should facilitate arithmetic operations: similar to unsigned integer arithmetic; In unsigned integer representation: Weight of the most significant bit is +2 n 1 ; It turns out that with a sign bit desired arithmetic properties are achieved if: Weight of the most significant bit is 2 n 1 ; L. Tarrataca Chapter 10 - Computer Arithmetic 21 / 102
22 Integer representation Twos Complement Representation This is the convention used in twos complement representation: n 1 A = 2 n 1 a n i a i for A < 0 For a n 1 = 0, then 2 n 1 a n 1 = 0, i.e.: Equation defines nonnegative integer; For a n 1 = 1, then the term 2 n 1 is subtracted from the summation, i.e.: yielding a negative integer i=0 L. Tarrataca Chapter 10 - Computer Arithmetic 22 / 102
23 Integer representation Twos Complement Representation Figure: Alternative representations for 4 bit integers (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 23 / 102
24 Integer representation Twos Complement Representation Twos complement is a weird representation from the human perspective: However: Facilitates addition and subtraction operations; For this reason: it is almost universally used as the processor representation for integers. L. Tarrataca Chapter 10 - Computer Arithmetic 24 / 102
25 Integer representation Twos Complement Representation Example A useful illustration of twos complement: Figure: An eight-position twos complement value box (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 25 / 102
26 Integer representation Twos Complement Representation Example A useful illustration of twos complement: Figure: Convert binary to decimal (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 26 / 102
27 Integer representation Twos Complement Representation Example A useful illustration of twos complement: Figure: Convert decimal -120 to binary (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 27 / 102
28 Integer representation Range Extension Range Extension Sometimes it is desirable to take an n-bit integer and store it in m-bits: where m > n Easy in sign-magnitude notation: move the sign bit to the new leftmost position and fill in with zeros. L. Tarrataca Chapter 10 - Computer Arithmetic 28 / 102
29 Integer representation Range Extension Range Extension Sometimes it is desirable to take an n-bit integer and store it in m-bits: where m > n Same procedure will not work for twos complement: What can we do to solve this problem? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 29 / 102
30 Integer representation Range Extension Rule for twos complement integers is: Move sign bit to leftmost position and fill in with copies of the sign bit, i.e.: For positive numbers: Fill in with zeros For negative numbers: Fill in with ones Example: L. Tarrataca Chapter 10 - Computer Arithmetic 30 / 102
31 Integer Arithmetic Negation Negation How can we negate a number in twos complement? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 31 / 102
32 Integer Arithmetic Negation How can we negate a number in twos complement? Any ideas? To negate an integer in twos complement notation: 1 Complement each bit (including sign bit); 2 Add 1; 3 Example: L. Tarrataca Chapter 10 - Computer Arithmetic 32 / 102
33 Integer Arithmetic Negation Two special cases to consider in negation (1/2): Consider A = 0. In that case, for an 8-bit representation: Carry bit out of the most significant bit is ignored; The result is that the negation of 0 is 0; L. Tarrataca Chapter 10 - Computer Arithmetic 33 / 102
34 Integer Arithmetic Negation Two special cases to consider in negation (2/2): Negation of the bit pattern of 1 followed by n 1zeros: Produces the same number Why? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 34 / 102
35 Integer Arithmetic Negation Two special cases to consider in negation (2/2): Negation of the bit pattern of 1 followed by n 1zeros: Produces the same number Why? Any ideas? Twos complement range: [ 2 n 1, 2 n 1 1] L. Tarrataca Chapter 10 - Computer Arithmetic 35 / 102
36 Integer Arithmetic Addition Addition How can we add a number in twos complement? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 36 / 102
37 Integer Arithmetic Addition Addition Addition proceeds as if the two numbers were unsigned integers: L. Tarrataca Chapter 10 - Computer Arithmetic 37 / 102
38 Integer Arithmetic Addition Addition Addition proceeds as if the two numbers were unsigned integers: Carry bit beyond (indicated by shading) is ignored; L. Tarrataca Chapter 10 - Computer Arithmetic 38 / 102
39 Integer Arithmetic Addition Addition Addition proceeds as if the two numbers were unsigned integers: L. Tarrataca Chapter 10 - Computer Arithmetic 39 / 102
40 Integer Arithmetic Addition Addition Addition proceeds as if the two numbers were unsigned integers: Carry bit beyond (indicated by shading) is ignored; L. Tarrataca Chapter 10 - Computer Arithmetic 40 / 102
41 Integer Arithmetic Addition Addition But what happens with this case? L. Tarrataca Chapter 10 - Computer Arithmetic 41 / 102
42 Integer Arithmetic Addition Addition But what happens with this case? Two numbers of the same sign produce a different sign... L. Tarrataca Chapter 10 - Computer Arithmetic 42 / 102
43 Integer Arithmetic Addition Addition But what happens with this case? L. Tarrataca Chapter 10 - Computer Arithmetic 43 / 102
44 Integer Arithmetic Addition Addition But what happens with this case? Two numbers of the same sign produce a different sign... L. Tarrataca Chapter 10 - Computer Arithmetic 44 / 102
45 Integer Arithmetic Addition Addition Why do you think this happens? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 45 / 102
46 Integer Arithmetic Addition Addition Why do you think this happens? Any ideas? Overflow: The result is larger that what can be stored with the word; Solution: Increase word size? When overflow occurs: ALU must signal this fact so that no attempt is made to use the result. L. Tarrataca Chapter 10 - Computer Arithmetic 46 / 102
47 Integer Arithmetic Subtraction Subtraction How can we subtract a number in twos complement? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 47 / 102
48 Integer Arithmetic Subtraction Subtraction To subtract the subtrahend from the minuend: Take the twos complement of the subtrahend and add it to the minuend. I.e.: subtraction is achieved using addition; L. Tarrataca Chapter 10 - Computer Arithmetic 48 / 102
49 Integer Arithmetic Subtraction Subtraction is achieved using addition; Carry bit beyond (indicated by shading) is ignored; L. Tarrataca Chapter 10 - Computer Arithmetic 49 / 102
50 Integer Arithmetic Subtraction Subtraction is achieved using addition; Carry bit beyond (indicated by shading) is ignored; L. Tarrataca Chapter 10 - Computer Arithmetic 50 / 102
51 Integer Arithmetic Subtraction Subtraction is achieved using addition; L. Tarrataca Chapter 10 - Computer Arithmetic 51 / 102
52 Integer Arithmetic Subtraction Subtraction is achieved using addition; Overflow: two numbers of the same sign produce a different sign; L. Tarrataca Chapter 10 - Computer Arithmetic 52 / 102
53 Integer Arithmetic Subtraction Subtraction is achieved using addition; Carry bit beyond (indicated by shading) is ignored; Overflow: two numbers of the same sign produce a different sign; L. Tarrataca Chapter 10 - Computer Arithmetic 53 / 102
54 Integer Arithmetic Hardware Block Diagram for Adder Hardware Block Diagram for Adder How can we map these concepts into hardware? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 54 / 102
55 Integer Arithmetic Hardware Block Diagram for Adder Hardware Block Diagram for Adder Figure: Block diagram of hardware for addition and subtraction (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 55 / 102
56 Integer Arithmetic Hardware Block Diagram for Adder From the previous figure: Central element is a binary adder: Presented with two inputs; Produces a sum and an overflow indication; Adder treats the two numbers as unsigned integers For the addition operation: The two numbers are presented in two registers; Result may be stored in one of these registers or in a third; For the subtraction operation: Subtrahend (B register) is passed through a twos complementer; Overflow indication is stored in a 1-bit overflow flag. L. Tarrataca Chapter 10 - Computer Arithmetic 56 / 102
57 Integer Arithmetic Multiplication Multiplication Multiplication is a complex operation: Compared with addition and subtraction; Again lets consider multiplying: Two unsigned numbers; Two signed (twos complement) numbers; L. Tarrataca Chapter 10 - Computer Arithmetic 57 / 102
58 Integer Arithmetic Multiplication Unsigned Integers How can we perform multiplication? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 58 / 102
59 Integer Arithmetic Multiplication How can we perform multiplication? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 59 / 102
60 Integer Arithmetic Multiplication Several important observations: 1 Multiplication involves the generation of partial products: One for each digit in the multiplier; These partial products are then summed to produce the final product. 2 The partial products are easily defined. When the multiplier bit is 0,the partial product is 0; When the multiplier is 1, the partial product is the multiplicand; 3 Total product is produced by summing the partial products: each successive partial product is shifted one position to the left relative 4 Multiplication of two n-bit binary integers produces up to 2n bits; L. Tarrataca Chapter 10 - Computer Arithmetic 60 / 102
61 Integer Arithmetic Multiplication How can we translate these concepts into hardware? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 61 / 102
62 Integer Arithmetic Multiplication How can we translate these concepts into hardware? Any ideas? We can perform a running addition on the partial products: Rather than waiting until the end; Eliminates the need for storage of all the partial products; Fewer registers are needed We can save some time on the generation of partial products: For each 1 on the multiplier, an add and a shift operation are required For each 0, only a shift is required. L. Tarrataca Chapter 10 - Computer Arithmetic 62 / 102
63 Integer Arithmetic Multiplication Possible implementation employing these measures: L. Tarrataca Chapter 10 - Computer Arithmetic 63 / 102
64 Integer Arithmetic Multiplication 1 Multiplier and multiplicand are loaded into two registers (Q and M); 2 A third register, the A register, is also needed and is initially set to 0; 3 There is also a 1-bit C register, initialized to 0: which holds a potential carry bit resulting from addition. L. Tarrataca Chapter 10 - Computer Arithmetic 64 / 102
65 Integer Arithmetic Multiplication Example L. Tarrataca Chapter 10 - Computer Arithmetic 65 / 102
66 Integer Arithmetic Multiplication 4 Control logic then reads the bits of the multiplier one at a time: If Q 0 is 1, then: the multiplicand is added to the A register... and the result is stored in the A register... with the C bit used for overflow. Then all of the bits of the C, A, and Q registers are shifted to the right one bit: So that the C bit goes into A n 1, A 0 goes into Q n 1 and Q 0 is lost. If Q 0 is 10, then: Then no addition is performed, just the shift; Process is repeated for each bit of the original multiplier; Resulting 2n-bit product is contained in the A and Q registers L. Tarrataca Chapter 10 - Computer Arithmetic 66 / 102
67 Integer Arithmetic Multiplication Or in flowchart form: Figure: Flowchart for unsigned binary multiplication (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 67 / 102
68 Integer Arithmetic Multiplication Twos complement multiplication How can we perform multiplication using twos complement? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 68 / 102
69 Integer Arithmetic Multiplication Product of two N-bit numbers requires maximum of 2N: Double the precision of the two operands using two s complement; For example, take 6 5 = 30 Figure: (Source: wikipedia) Discarding the bits beyond the eighth bit will produce the correct result; L. Tarrataca Chapter 10 - Computer Arithmetic 69 / 102
70 Integer Arithmetic Multiplication Can you see any problems with this approach? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 70 / 102
71 Integer Arithmetic Multiplication Very inefficient: Precision is doubled ahead of time; This means that all additions must be double-precision; Therefore twice as many partial products are needed... L. Tarrataca Chapter 10 - Computer Arithmetic 71 / 102
72 Integer Arithmetic Multiplication Can we do better than this? L. Tarrataca Chapter 10 - Computer Arithmetic 72 / 102
73 Integer Arithmetic Multiplication Can we do better than this? Yes we can through Booth s algorithm =) L. Tarrataca Chapter 10 - Computer Arithmetic 73 / 102
74 Integer Arithmetic Multiplication Booth s Algorithm Figure: (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 74 / 102
75 Integer Arithmetic Multiplication 1 Multiplier and multiplicand are placed in the Q and M registers; 2 Q 1 is a 1-bit register placed logically to the right of Q 0 ; 3 Results of the multiplication will appear in the A and Q registers; 4 A and Q 1 are initialized to 0. L. Tarrataca Chapter 10 - Computer Arithmetic 75 / 102
76 Integer Arithmetic Multiplication 5 Control logic scans the bits of the multiplier one at a time: as each bit is examined, the bit to its right is also examined; If the two bits are the same (1-1 or 0-0): all of the bits of the A, Q, and Q 1 registers are shifted to the right 1 bit. If the two bits differ: then the multiplicand is added/subtracted from the A register depending on whether the two bits are 0-1 or 1-0. Following the addition or subtraction, the right shift occurs. All shifts performed preserve the sign: Arithmetic Right Shift L. Tarrataca Chapter 10 - Computer Arithmetic 76 / 102
77 Integer Arithmetic Multiplication In flowchart form: Figure: (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 77 / 102
78 Integer Arithmetic Multiplication Seems complicated? That is because it is; Focus on performance not on human easiness to understand... Can be proved mathematically that works: Beyond the scope of this class... Same concepts could be used to divise a division method: Beyond the scope of this class... L. Tarrataca Chapter 10 - Computer Arithmetic 78 / 102
79 Integer Arithmetic Multiplication Now that we have a basic understanding about: integer representation; integer arithmetic operations; How can we represent floating-point numbers? L. Tarrataca Chapter 10 - Computer Arithmetic 79 / 102
80 Floating-point representation Floating-point representation We can represent decimal numbers in several ways, e.g.: 976, 000, 000, 000, 000 = = I.e. the decimal point floats to a convenient location: We use the exponent of 10 to keep track of the decimal point; This way we can represent large and small numbers with only a few digits; L. Tarrataca Chapter 10 - Computer Arithmetic 80 / 102
81 Floating-point representation Same approach can be taken with binary numbers, i.e.: ±S B ±E This number can be stored in a binary word with three fields: Sign: plus or minus Significand: S Exponent: E Base: B (binary) L. Tarrataca Chapter 10 - Computer Arithmetic 81 / 102
82 Floating-point representation In general: Figure: Typical 32-Bit floating-point format (Source: [Stallings, 2015]) Leftmost bit stores the sign of the number (0 = positive, 1 = negative) Exponent value is stored in the next k = 8 bits: A fixed value (bias) is subtracted from the field to get the true value. Bias equals 2 k 1 1 Range of possible values [ (2 k 1 1), 2 k ] Final portion of the word (23 bits in this case) is the significand. L. Tarrataca Chapter 10 - Computer Arithmetic 82 / 102
83 Floating-point representation Figure: Typical 32-Bit floating-point format (Source: [Stallings, 2015]) Examples: = = = = L. Tarrataca Chapter 10 - Computer Arithmetic 83 / 102
84 Floating-point representation Figure: Typical 32-Bit floating-point format (Source: [Stallings, 2015]) Examples: = = = = Biased exponent: L. Tarrataca Chapter 10 - Computer Arithmetic 84 / 102
85 Floating-point Arithmetic Floating-point Arithmetic Now that we know how to represent floating-point numbers: How can we perform floating-point arithmetic? Any ideas? L. Tarrataca Chapter 10 - Computer Arithmetic 85 / 102
86 Floating-point Arithmetic Some observations: Addition and subtraction operations: Necessary to ensure that both operands have the same exponent value. May require shifting the radix point on one of the operands to achieve alignment Multiplication and division are more straightforward. L. Tarrataca Chapter 10 - Computer Arithmetic 86 / 102
87 Floating-point Arithmetic Figure: Floating point numbers and arithmetic operations (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 87 / 102
88 Floating-point Arithmetic Example X = = 30 Y = = 200 X + Y = ( ) 10 3 = = 230 X Y = ( ) 10 3 = = 170 X Y = ( ) = = 6000 X Y = ( ) = = 0.15 L. Tarrataca Chapter 10 - Computer Arithmetic 88 / 102
89 Floating-point Arithmetic A floating-point operation may produce one of these conditions (1/2): Exponent overflow: A positive exponent exceeds the maximum possible exponent value. Exponent underflow: Less than the minimum possible exponent value: E.g.: -200 is less than This means that the number is too small to be represented (reported as 0). L. Tarrataca Chapter 10 - Computer Arithmetic 89 / 102
90 Floating-point Arithmetic A floating-point operation may produce one of these conditions (2/2): Significand underflow: In the process of aligning significands, digits may flow off the right end of the significand. Significand overflow: The addition of two significands of the same sign may result in a carry out of the most significant bit L. Tarrataca Chapter 10 - Computer Arithmetic 90 / 102
91 Floating-point Arithmetic Addition and Subtraction Addition and Subtraction In floating-point arithmetic: Addition/subtraction more complex than multiplication/division; This is because of the need for alignment; There are four basic phases of the algorithm for addition and subtraction: 1 Check for zeros. 2 Align the significands. 3 Add or subtract the significands. 4 Normalize the result. Lets have a look at each one of these... L. Tarrataca Chapter 10 - Computer Arithmetic 91 / 102
92 Floating-point Arithmetic Addition and Subtraction Phase 1: Zero check: Addition and subtraction are identical except for a sign change: Begin by changing the sign of the subtrahend if it is a subtract operation. If either operand is 0, the other is reported as the result. L. Tarrataca Chapter 10 - Computer Arithmetic 92 / 102
93 Floating-point Arithmetic Addition and Subtraction Phase 2: Significand alignment (1/2): Manipulate numbers so that the two exponents are equal, e.g.: ( )+( ) Digits must first be set into equivalent positions, i.e.: 4 of the second number must be aligned with the 3 of the first; The two exponents need to be equal Thus: ( )+( ) = ( )+( ) = L. Tarrataca Chapter 10 - Computer Arithmetic 93 / 102
94 Floating-point Arithmetic Addition and Subtraction Phase 2: Significand alignment (2/2): Alignment may be achieved by: shifting either the smaller number to the right (increasing its exponent) shifting the larger number to the left Either operation may result in the loss of digits Smaller number is usually shifted: since any digits lost are of small significance. In general terms: Repeatedly shift the significand right 1 digit and increment the exponent until the two exponents are equal. L. Tarrataca Chapter 10 - Computer Arithmetic 94 / 102
95 Floating-point Arithmetic Addition and Subtraction Phase 3: Addition Significands are added together, taking into account their signs; Because the signs may differ, the result may be 0; There is also the possibility of significand overflow by 1 digit, if so: significand of the result is shifted right and the exponent is incremented; Exponent overflow could occur as a result; this would be reported and the operation halted. L. Tarrataca Chapter 10 - Computer Arithmetic 95 / 102
96 Floating-point Arithmetic Addition and Subtraction Phase 4: Normalization Consists of shifting significand digits left until the most significant digit is nonzero; Each shift causes: a decrement of the exponent and......thus could cause an exponent underflow. L. Tarrataca Chapter 10 - Computer Arithmetic 96 / 102
97 Floating-point Arithmetic Addition and Subtraction In flowchart form: Figure: Floating Point Addition And Subtraction (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 97 / 102
98 Floating-point Arithmetic Floating-Point Multiplication Floating-Point Multiplication 1 If either operand is 0, 0 is reported as the result; 2 Then add the exponents; 3 Then multiply the significands, taking into account their signs: Similarly to twos complement multiplication. 4 After the product is calculated, the result is then normalized. L. Tarrataca Chapter 10 - Computer Arithmetic 98 / 102
99 Floating-point Arithmetic Floating-Point Multiplication In flowchart form: Figure: Floating Point Multiplication (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 99 / 102
100 Floating-point Arithmetic Floating-Point Division Floating-Point Division 1 Test for 0: If the divisor is 0, an error report is issued; A dividend of 0 results in 0. 2 Then divisor exponent is subtracted from the dividend exponent; 3 Next: divide the significands; 4 After the division is calculated, the result is then normalized; L. Tarrataca Chapter 10 - Computer Arithmetic 100 / 102
101 Floating-point Arithmetic Floating-Point Division In flowchart form: Figure: Floating Point Division (Source: [Stallings, 2015]) L. Tarrataca Chapter 10 - Computer Arithmetic 101 / 102
102 References References I Stallings, W. (2015). Computer Organization and Architecture. Pearson Education. L. Tarrataca Chapter 10 - Computer Arithmetic 102 / 102
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