Numbers and number systems. Radix number systems 4 Some number of positions and some number of...

Numbers and number systems

Radix number systems

Some number of positions and some number of symbols

The number of positions varies by context The number of symbols is a property of the

number system – Decimal -- 10 symbols– Binary -- 2 symbols– Octal -- 8 symbols– Hexadecimal -- 16 symbols

Start with whole numbers

Each position has a value Each symbol has a value Multiply the value of the symbol by the value

of the position, then add– In decimal, 3874 means

• 3 times 1,000• plus 8 time 100• plus 7 times 10 • plus 4 times 1

Decimal, binary, octal, hex

In decimal there are 10 symbols (0..9) and the value of each position is a power of 10.– 100 = 1 = value of the units position– 101 = 10 = value of next position to the left– etc.

In binary, there are 2 symbols, 0 and 1, and the value of each position is a power of 2.

In octal, 8 symbols, and powers of 8 In hexadecimal, 16 symbols, and powers of 16

Converting

Binary to/from octal and hex is very easy– mark off groups

Decimal is harder, but not very much.– Example

• 3176 to binary, octal, hex

• 71348 to decimal, binary, hex

• 5A3216 to decimal, binary, octal

Include fractions

Same principles Use negative powers of the base to the right

of the radix point. (Only call it a decimal point in the decimal number system.)– 426.12810 to binary, octal, hex

– 11011.10112 to decimal, octal, hex

– 426.548 to decimal, binary, hex

– AB1.216 to decimal, binary, octal

Negatives

Same as positive, but need a way to recognize that the value is negative.

What does negative mean?– Distance from 0, opposite direction of positive– For every positive, there is a corresponding

negative. When those are added, the result is exactly 0.

Ways to represent negatives Sign magnitude

– - or ( ) or red ink or whatever 1’s complement

– reverse the bits to get the negative– (subtract from all 1’s to get the complement)

2’s complement– subtract from a power of two 10000000 …. 000 (number

of places depends on the size of the storage available.)– It so happens that reversing the bits and adding 1

accomplishes this subtraction. excess something

– Add something to the value before storing

2’s complement

For n bits, each value is expressed relative to its distance from 2n. – Technically, that means subtract each value

from 2n . Conveniently, that can be accomplished by switching each bit and then adding 1 to the result.

For n = 4: subtract from 24 = 10000, show only four bits.0000 0 0100 4 1000 -8 1100 -40001 1 0101 5 1001 -7 1101 -30010 2 0110 6 1010 -6 1110 -20011 3 0111 7 1011 -5 1111 -1

Note, 0 comes first, then the positive values, then the negatives.

Does this work?

Check it out. Example: 3 + 4:

– 0011 + 0100 = 0111 = 7 Example: -3 + -4:

– 1101 + 1100 = 1)1001. 1001 = -7• note that the extra 1 that flows out of the

computation is not an overflow. Example: +3 + -4:

– 0011 = 1100 = 1111 = -1Examples don’t prove correctness, of course; they are only illustrations

Excess something

The point of excess something representation for values is that numbers stay in the order you expect

– the greatest negative is the smallest value

– 0 is in the middle

– the greatest positive is the largest value. We will see excess 127 used in representing exponents.

– The value 43 would be represented as 43+127 = 170

– The value -43 would be represented as -43 + 127 = 84

– The smaller values (the negatives) start with 0 in binary; the larger values (the positives) start with binary 1. This is the opposite of 2’s complement, where the negatives start with 1 and the positives start with 0.

Binary arithmetic - addition

0 + 0 = 0 0 + 1 = 1

Overflow: If there is not enough room to hold the result correctly. – An extra bit that drops out is not necessarily an overflow.

– If the two numbers are of opposite signs, no overflow can occur. (Why not?)

– If the numbers are of the same sign, overflow occurs if the carry into the sign bit position is different from the carry out of the sign bit position.

(Add two small negative nos.)

(Result is smaller than one of them)

1 + 0 = 1 1 + 1 = 0 and carry 1

Sign changed as a result of the computation, not because of the signs of the numbers used.

Binary arithmetic - multiplication

0 * 0 = 0 0 * 1 = 0

No carry. No big tables to memorize Multiplying negatives: complement, multiply

the positives, set the sign appropriately. Size of the product is sum of the sizes of the

multiplier and multiplicand.

1 * 0 = 0 1 * 1 = 1

Fractions A part of a whole. Approximation of the real number line, with limitations

imposed by the number of places used. Consider a decimal number expressed with not more

than 5 decimal places. – How would you represent 0.0000138? Because of the

limitation on the representation (only 5 places), we cannot accurately represent this number. Instead, we would use an

approximation: 0.00001 This is an example of a roundoff error

– If we needed to represent the remaining 0.0000038 of the number, we are out of luck. This is called underflow

Overflow and Underflow

Ref. Tannenbaum. Computer Organization

How to represent fractional values in binary We have only two symbols. We must represent

– numbers: 0 and 1– sign– radix point

How do we do that?– There have been a number of perfectly good

solutions. Now that it is common to exchange data between systems, we must have one common method.

Floating point notation By example (using 8 bit word size):

– 2.5 = 10.1 in binary– One way to represent the point is to put it in the same place all the

time and then not represent it explicitly at all. To do that, we must have a standard representation for a value that puts the point in the same place every time.

– 10.1 = 1.01 * 21

– Use 1 bit for sign, 2 bits for exponent, rest for value– sign = 0 (positive); exponent = 01; significand = 101

• point assumed as in 1.01

– Result= 00110100

Refinement Use 32 or 64 bits, not 8, to make more

reasonable range of values Note that the leading 1 (as in 1.01 *21) is always

there, so we don’t need to waste one of our precious bits on it. Just assume it is always there.

Use excess something notation for handling negative exponents.

These ideas came from existing schemes developed for the PDP-11 and CDC 6600 computers.

IEEE Standard 754

One way to meet the need, agreed to and accepted by most computer manufacturers.Bits 1 8 23

Sign Exponent

Fraction

Bits 1 11 52

Sign Exponent

Fraction

Single Precision

Double Precision

Steps to IEEE format

Convert 35.75, for example– Convert the number to binary

• 100011.11

– Normalize• 1.0001111 x 25

– Fit into the required format • 5 + 127 = 132; hide the leading 1.

• 01000010000011110000000000000000

– Use Hexadecimal to make it easier to read• 420F0000

Single and double precision

Double precision uses more space, allows greater magnitude and greater precision.

Other than that, it behaves just like single precision.

We will use only single precision in examples, but any could easily be expanded to double precision.

IEEE 754 details

Ref. Tannenbaum. Computer Organization

What’s normal? Normalized means represented in the normal, or

standard, notation. Some numbers do not fit into that scheme and have a separate definition.

Consider the smallest normalized value:– 1.000--000 x 2-126

– How would we represent half of that number?1.000--000 x 2-127 But we cannot fit 127 into the

exponent field0.100 --000 x 2-126

would do it.But we are stuck with that implied 1 before the implied point

So, there are a lot of potentially useful values that don’t fit into the scheme. The solution: special rules when the exponent has value 0 (which represents -126).

Denormalization

This is denormalization: abandoning the “normal” scheme to exploit possibilities that would otherwise not be available.

No implied 1 before the implied pointPower of two multiplier is -127

Sign

0 Any non-zero value

Representing Zero

How do you represent exactly 0 if there is an implied 1 in the number somewhere?

A special case of denormalized numbers, when everything is zero, the value of the number is exactly 0.0

Infinity

A special representation is reserved for infinity, because it is a useful entity to have available.

Sign

11111111 00000… …000000000

NaN (Not a Number)

One more special case reserved for undefined results:

11111111 Any non-zero bit pattern

Sign