# Quiz for Chapter 3 Arithmetic for Computers 3.10

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1 Date: Quiz for Chapter 3 Arithmetic for Computers 3.10 Not all questions are of equal difficulty. Please review the entire quiz first and then budget your time carefully. Name: Course: Solutions in RED 1. [9 points] This problem covers 4-bit binary multiplication. Fill in the table for the Product, Multplier and Multiplicand for each step. You need to provide the DESCRIPTION of the step being performed (shift left, shift right, add, no add). The value of M (Multiplicand) is 1011, Q (Multiplier) is initially Product Multiplicand Multiplier Description Step Initial Values Step => No add Step Shift left M Step Shit right Q Step => Add M to Product Step Shift left M Step Shift right Q Step => No add Step Shift left M Step Shift right Q Step => Add M to Product Step Shift left M Step Shift right Q Step => No add Step Shift left M Step Shift Right Q Step [6 points] This problem covers floating-point IEEE format. (a) List four floating-point operations that cause NaN to be created? Four operations that cause Nan to be created are as follows: (1) Divide 0 by 0 (2) Multiply 0 by infinity (3) Any floating point operation involving Nan (4) Adding infinity to negative infinity (b) Assuming single precision IEEE 754 format, what decimal number is represent by this word: (Hint: remember to use the biased form of the exponent.) The decimal number

2 = (+1)* (2^( ))*(1.001) 2 = (+1)*(0.25)*(0.125) = [12 points] The floating-point format to be used in this problem is an 8-bit IEEE 754 normalized format with 1 sign bit, 4 exponent bits, and 3 mantissa bits. It is identical to the 32-bit and 64-bit formats in terms of the meaning of fields and special encodings. The exponent field employs an excess- 7coding. The bit fields in a number are (sign, exponent, mantissa). Assume that we use unbiased rounding to the nearest even specified in the IEEE floating point standard. (a) Encode the following numbers the 8-bit IEEE format: (1) binary This number = * 2-3 = (+1) * (1.1011) 2 * 2 (4-7) = in the 8-bit IEEE 754 (after applying unbiased rounding to the nearest even) (2) 16.0 decimal This number = (1000.0) 2 = (1.000) 2 * 2 (10-7) = in the 8-bit IEEE 754 (b) Perform the computation binary binary showing the correct state of the guard, round and sticky bits. There are three mantissa bits (The sticky bit is set to 1) (The least two significant bits are the guard and round bits) After rounding with sticky bit, the answer then is (1.101) 2 (c) Decode the following 8-bit IEEE number into their decimal value: The decimal value is (+1)*(2) (10-7) *1.625 = 13.0 (d) Decide which number in the following pairs are greater in value (the numbers are in 8-bit IEEE 754 format): (1) and The first number = 2 (8-7) *(1.1)2 = 3.0 The second number = 2 (8-7) *(1.111)2 = 3.75 The second number is greater in value (2) and Page 2 of 8

3 The first number = -2 (12-7) *(1.1)2 = The second number = -2 (8-7) *(1.101)2 = The first number is greater in value. (e) In the 32-bit IEEE format, what is the encoding for negative zero? The representation of negative zero in 32-bit IEEE format is (f) In the 32-bit IEEE format, what is the encoding for positive infinity? The representation for positive infinity in 32-bit IEEE format is [9 points] The floating-point format to be used in this problem is a normalized format with 1 sign bit, 3 exponent bits, and 4 mantissa bits. The exponent field employs an excess-4 coding. The bit fields in a number are (sign, exponent, mantissa). Assume that we use unbiased rounding to the nearest even specified in the IEEE floating point standard. (a) Encode the following numbers in the above format: (1) 1.0 binary The encoding for the above number is (2) binary The encoding for the above number is (b) In one sentence for each, state the purpose of guard, rounding, and sticky bits for floating point arithmetic. The guard bit is an extra bit that is added at the least significant bit position during an arithmetic operation to prevent loss of significance The round bit is the second bit that is used during a floating point arithmetic operation on the rightmost bit position to prevent loss of precision during intermediate additions. The sticky bit keeps record of any 1 s that have been shifted on to the right beyond the guard and round bits (c) Perform rounding on the following fractional binary numbers, use the bit positions in italics to determine rounding (use the rightmost 3 bits): (1) Round to positive infinity: binary The result is Page 3 of 8

5 01 (1) 10 (-2) 11 (-1) 01 (1) 11 (-1) 00 (0) 10 (-2) 10 (-2) 00 (0) 10 (-2) 11 (-1) 01 (1) In the above table, the range of numbers representable through 2 bits are -2 to [4 points] Using 32-bit IEEE 754 single precision floating point with one(1) sign bit, eight (8) exponent bits and twenty three (23) mantissa bits, show the representation of -11/16 ( ). The representation of is: [3 points] What is the smallest positive (not including +0) representable number in 32-bit IEEE 754 single precision floating point? Show the bit encoding and the value in base 10 (fraction or decimal OK). The smallest positive representable number 32-bit IEEE 754 single precision floating point value is Its decimal value is = (+1) * (2 (0-127) )*( ) = e [12 points] Perform the following operations by converting the operands to 2 s complement binary numbers and then doing the addition or subtraction shown. Please show all work in binary, operating on 16-bit numbers. (a) (3) (12) The decimal value of the result is 15 (b) (13) (-2) The decimal value of the result is 11 (we ignored the carry here) (c) (5) (-6) The decimal value of the result is -1 Page 5 of 8

6 (d) 7 (-7) (-7) (7) The decimal value of the result is 0 (we ignored the carry here) 9. [9 points] Consider 2 s complement 4-bit signed integer addition and subtraction. (a) Since the operands can be negative or positive and the operator can be subtraction or addition, there are 8 possible combinations of inputs. For example, a positive number could be added to a negative number, or a negative number could be subtracted from a negative number, etc. For each of them, describe how the overflow can be computed from the sign of the input operands and the carry out and sign of the output. Fill in the table below: Sign (Input 1) Sign (Input 2) Operation Sign (Output) Overflow (Y/N) N Y N N N N N Y N N N N Y N N N (b) Define the WiMPY precision IEEE 754 floating point format to be: where each X represents one bit. Convert each of the following WiMPY floating point numbers to decimal: (a) (+1)*(2 (0-7) )*(1.0) = (b) (-1)*(2 (5-7) )*(1.1010) = (c) Page 6 of 8

7 (+1)*(2 (7-7) )(1.0000) = [8 points] This problem covers 4-bit binary unsigned division (similar to Fig in the text). Fill in the table for the Quotient, Divisor and Dividend for each step. You need to provide the DESCRIPTION of the step being performed (shift left, shift right, sub). The value of Divisor is 4 (0100, with additional 0000 bits shown for right shift), Dividend is 6 (initially loaded into the Remainder). Quotient Divisor Remainder Description Step Initial Values Step Rem = Rem Div Step Rem < 0 => +Div, sll Q, Q0 = 0 Step Shift Div to right Step Rem = Rem Div Step Rem < 0 => +Div, sll Q, Q0 = 0 Step Shift Div to right Step Rem = Rem Div Step Rem < 0 => +Div, sll Q, Q0 = 0 Step Shift Div to right Step Rem = Rem Div Step Rem < 0 => +Div, sll Q, Q0 = 0 Step Shift Div to right Step Rem = Rem Div Step Rem > 0 => sll Q, Q0 = 1 Step Shift Div Right Step [8 points] Why is the 2 s complement representation used most often? Give an example of overflow when: (a) 2 positive numbers are added Assuming a 8-bit 2 s complement representation, an overflow occurs when +127 is added to itself: Here an overflow occurred due to carry into the sign bit (b) 2 negative numbers are added Assuming a 8-bit 2 s complement representation, an overflow occurs when -127 is added to itself: Here an overflow occurred due to carry out of the sign bit and the sign of the result is different from the signs of either operands. (c) A-B where B is a negative number If A = +127 and B = -127, an overflow occurs similar to case (a) Page 7 of 8

8 The two s complement system is used because it does not need to examine the sign of each operand before performing any arithmetic operation. Unlike the signed magnitude representation it does not have two different representations for zero 12. [14 points] We re going to look at some ways in which binary arithmetic can be unexpectedly useful. For this problem, all numbers will be 8-bit, signed, and in 2 s complement. (a) For x = 8, compute x & ( x). (& here refers to bitwise-and, and refers to arithmetic negation.) x = x = x & (-x) = (b) For x = 36, compute x & ( x). x = x = x & (-x) = (c) Explain what the operation x & ( x) does. It gets the least significant bit position of x which is set to 1 and raises it to power 2. (d) In some architectures (such as the PowerPC), there is an instruction adde rx=ry,rz, which performs the following: rx = ry + rz + CA where CA is the carry flag. There is also a negation instruction, neg rx=ry which performs: rx = 0 ry Both adde and neg set the carry flag. gcc (the GNU C Compiler) will often use these instructions in the following sequence in order to implement a feature of the C language: neg r1=r0 adde r2=r1,r0 Explain, simply, what the relationship between r0 and r2 is (Hint: r2 has exactly two possible values), and what C operation it corresponds to. Be sure to show your reasoning. The only two possible values for r2 are 0 and 1. If r0 = 0, then r2 = 1. If r0 is not 0, then r2 = 0. These two instructions can be used to test the branch condition: if (x == 0)... Page 8 of 8

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