Floating-Point Processing

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Computer Organization &

Computer Organization &

Assembly Languages Assembly Languages

Pu-Jen Cheng

Floating-Point Processing

Adapted from the slides prepared by Kip Irvine for the book, Assembly Language for Intel-Based Computers, 5th Ed.

And prepared by Behrooz Parhami for the book, Computer Architecture, 2005

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Outline

„

Floating-Point Binary Representation

„

Floating-Point Unit

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Decimal Fractions vs Binary Floating-Point

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Floating-Point Binary Representation

„

IEEE Floating-Point Binary Reals

„

The Exponent

„

Normalized Binary Floating-Point Numbers Creating the IEEE Representation

„

Creating the IEEE Representation

„

Converting Decimal Fractions to Binary Reals

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IEEE Floating-Point Binary Reals

„

Types

¾ Single Precision

„ 32 bits: 1 bit for the sign, 8 bits for the exponent, and 23 bits for the fractional part of the significand.

¾ Double Precision

¾ Double Precision

„ 64 bits: 1 bit for the sign, 11 bits for the exponent, and 52 bits for the fractional part of the significand.

¾ Double Extended Precision

„ 80 bits: 1 bit for the sign, 16 bits for the exponent, and 63 bits for the fractional part of the significand.

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Single-Precision Format (short real)

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Sign

¾ 1 = negative, 0 = positive

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Significand

¾ decimal digits to the left & right of decimal point

i h d i i l i

exponent fraction

1 8 23

sign

¾ weighted positional notation

¾ Example:

123.154 = (1 x 102) + (2 x 101) + (3 x 100) + (1 x 10–1) + (5 x 10–2) + (4 x 10–3)

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Exponent

¾ unsigned integer

¾ integer bias (127 for single precision)

approximate normalized range: 2-126 to 2127

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„ Biased Exponent = Actual Exponent + 127

Single-Precision Format (cont.)

„ Normalized: a single 1 appears to the left of the binary point

„ Unnormalized: exponent is zero

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Examples (Single Precision)

„

Order: sign bit, exponent bits, and fractional part

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ANSI/IEEE Standard Floating-Point Format

Short (32-bit) format

8 bits, bias = 127,

126 to 127

23 bits for fractional part (plus hidden 1 in integer part)

Short exponent range is –127 to 128 but the two extreme values

are reserved for special operands (similarly for the long format)

Long (64-bit) format

Sign Exponent Significand 11 bits,

bias = 1023,

1022 to 1023 52 bits for fractional part (plus hidden 1 in integer part)

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Real-Number Encodings

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Normalized finite numbers

¾ all the nonzero finite values that can be encoded in a normalized real number between zero and infinity

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Positive and Negative Infinity

N N ( t b )

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NaN (not a number)

¾ bit pattern that is not a valid FP value

¾ Two types: quiet, signaling

Specific encodings (single precision)

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Distribution of Floating-point Numbers on the Real Line

Negative numbers

FLP FLP ±0 +∞

–∞

Positive numbers min

max – – min + + max +

Denormals allow graceful underflow

±0, ±∞, NaN

1.f × 2e Denormals:

0.f × 2emin

Denser Denser

Sparser Sparser

Overflow region

Overflow region Underflow

regions Underflow

example

Overflow example Midway

example

Typical example

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Converting Single-Precision to Decimal

1. If the MSB is 1, the number is negative; otherwise, it is positive.

2. The next 8 bits represent the exponent. Subtract binary 01111111

(decimal 127), producing the unbiased exponent. Convert the unbiased exponent to decimal.

3. The next 23 bits represent the significand. Notate a “1.”, followed by the significand bits. Trailing zeros can be ignored. Create a floating- the significand bits. Trailing zeros can be ignored. Create a floating

point binary number, using the significand, the sign determined in step 1, and the exponent calculated in step 2.

4. Unnormalize the binary number produced in step 3. (Shift the binary point the number of places equal to the value of the exponent. Shift right if the exponent is positive, or left if the exponent is negative.)

5. From left to right, use weighted positional notation to form the decimal sum of the powers of 2 represented by the floating-point binary

number.

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Example

Convert 0 10000010 1011000000000000000000 to Decimal 1. The number is positive.

2. The unbiased exponent is binary 00000011, or decimal 3.

3 Combining the sign exponent and significand the binary 3. Combining the sign, exponent, and significand, the binary

number is +1.01011 X 23.

4. The unnormalized binary number is +1010.11.

5. The decimal value is +10 3/4, or +10.75.

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Outline

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Floating-Point Binary Representation

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Floating-Point Unit

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Floating Point Unit

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FPU Register Stack

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Rounding

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Floating-Point Exceptions

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Floating-Point Instruction Set Arithmetic Instructions

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Arithmetic Instructions

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Comparing Floating-Point Values

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Reading and Writing Floating-Point Values

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Exception Synchronization

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Mixed-Mode Arithmetic

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Masking and Unmasking Exceptions

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FPU Register Stack

„ 8 individually addressable 80-bit data registers

„ Register stack: R0~R7

„ Three-bit field named TOP in the FPU status word identifies the register number that is currently the top of stack.

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Special-Purpose Registers

• Opcode register: stores opcode of last noncontrol instruction executed

• Control register: controls precision and rounding method for calculations

• Status register: top-of-stack pointer,

diti d ti i

condition codes, exception warnings

• Tag register: indicates content type of each register in the register stack

• Last instruction pointer register: pointer to last non-control executed instruction

• Last data (operand) pointer register:

points to data operand used by last executed instruction

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Rounding

„

FPU attempts to round an infinitely accurate result from a floating-point calculation

¾ may be impossible because of storage limitations

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Example

St 1 0111 i 3 f ti l bit

¾ Store +1.0111 in 3 fractional bits

¾ rounding up by adding .0001 produces 1.100

¾ rounding down by subtracting .0001 produces 1.011

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Round to nearest even

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Round down toward –

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Round up toward

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Round toward zero

∞ ∞

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Round-to-Nearest (Even)

rtnei(x)

4 3 2 1

rtni(x)

4 3 2 1

–4 –3 –2 –1

x

–4 –3 –2 –1 1 2 3 4

–4 –3 –2 –1

x

–4 –3 –2 –1 1 2 3 4

(a) Round to nearest even integer (b) Round to nearest integer

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Directed Rounding

rutni(x)

4 3 2 1

ritni(x)

4 3 2 1

(a) Round inward to nearest integer (b) Round upward to nearest integer

–4 –3 –2 –1

x

–4 –3 –2 –1 1 2 3 4

–4 –3 –2 –1

x

–4 –3 –2 –1 1 2 3 4

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Floating-Point Exceptions

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Six types of exception conditions

¾ Invalid operation

¾ Divide by zero

¾ Denormalized operand

Numeric overflow (or underflow)

¾ Numeric overflow (or underflow)

¾ Inexact precision

„

Each has a corresponding mask bit

¾ if set when an exception occurs, the exception is handled automatically by FPU

¾ if clear when an exception occurs, a software exception handler is invoked

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FPU Instruction Set

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Instruction mnemonics begin with letter F

„

Second letter identifies data type of memory operand

¾ B = bcd I i t

¾ I = integer

¾ no letter: floating point

„

Examples

¾ FBLD load binary coded decimal

¾ FISTP store integer and pop stack

¾ FMUL multiply floating-point operands

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FPU Instruction Set

„

Operands

¾ zero, one, or two

¾ no immediate operands

¾ no general-purpose registers (EAX, EBX, ...)

integers must be loaded from memory onto the stack

¾ integers must be loaded from memory onto the stack and converted to floating-point before being used in calculations

¾ if an instruction has two operands, one must be a FPU register

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FP Instruction Set

„

Data Types

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Load Floating-Point Value

„ FLD

¾ Copies floating point operand from memory into the top of the FPU stack, ST(0)

„ Example

„ Example

„ Loading constants: FLD1 (1), FLDZ (0), FLDL2T (log210), FLDPI, FLDLG2 (log102), FLDLN2 (loge2)

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Store Floating-Point Value

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FST

¾ Copies floating point operand from the top of the FPU stack into memory

FSTP

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FSTP

¾ pops the stack after copying

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Arithmetic Instructions

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Same operand types as FLD and FST

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Floating-Point Add

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FADD

¾ Adds source to destination

¾ No-operand version pops the FPU stack after adding (ST(1) = ST(0)+ST(1); pop ST(0))

„

Examples:

fadd=faddp st(1), st(0)

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Floating-Point Subtract

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FSUB

¾ subtracts source from destination.

¾ No-operand version pops the FPU stack after subtractingg

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Example:

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Floating-Point Multiply

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FMUL

¾ Multiplies source by

destination, stores product in destination

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FDIV

¾ Divides destination by source, then pops the stack

The no-operand versions of FMUL and FDIV pop the stack after multiplying or dividing.

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Comparing FP Values

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FCOM instruction

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Operands:

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Condition codes set by FPU

¾ Codes similar to CPU flags

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Branching after FCOM

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Required steps:

1. Use the FNSTSW instruction to move the FPU status word into AX.

2. Use the SAHF instruction to copy AH into the EFLAGS register.

register.

3. Use JA, JB, etc to do the branching.

Fortunately, the FCOMI instruction does steps 1 and 2 for you.

fcomi ST(0), ST(1) jnb Label1

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Comparing for Equality

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Calculate the absolute value of the difference between two floating-point values

.data

epsilon REAL8 1.0E-12 ; difference value val2 REAL8 0.0 ; value to compare

val3 REAL8 1.001E-13 ; considered equal to val2 val3 REAL8 1.001E 13 ; considered equal to val2 .code

; if( val2 == val3 ), display "Values are equal".

fld epsilon fld val2 fsub val3 fabs

fcomi ST(0),ST(1) ja skip

mWrite <"Values are equal",0dh,0ah>

skip:

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Exception Synchronization

„ Main CPU and FPU can execute instructions concurrently

¾ if an unmasked exception occurs, the current FPU instruction is interrupted and the FPU signals an exception

¾ But the main CPU does not check for pending FPU exceptions. It might use a memory value that the interrupted FPU instruction was supposed to set. pp

¾ Example:

.data

intVal DWORD 25 .code

fild intVal ; load integer into ST(0) inc intVal ; increment the integer

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Exception Synchronization

„ (continued)

„ For safety, insert a fwait instruction, which tells the CPU to wait for the FPU's exception handler to finish:

.data

intVal DWORD 25 code

.code

fild intVal ; load integer into ST(0)

fwait ; wait for pending exceptions inc intVal ; increment the integer

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FPU Code Example

expression: valD = –valA + (valB * valC).

.data

valA REAL8 1.5 valB REAL8 2.5 valC REAL8 3.0

valD REAL8 ? ; will be +6.0

.code

fld valA ; ST(0) = valA

fchs ; change sign of ST(0)

fld valB ; load valB into ST(0) fmul valC ; ST(0) *= valC

fadd ; ST(0) += ST(1)

fstp valD ; store ST(0) to valD

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Mixed-Mode Arithmetic

„ Combining integers and reals.

¾ Integer arithmetic instructions such as ADD and MUL cannot handle reals

¾ FPU has instructions that promote integers to reals and load the values onto the floating point stack.

„ Example:

data .data

N SDWORD 20 X REAL8 3.5 Z REAL8 ? Y SDWORD ? .code

fild N ; load integer into ST(0)

fadd X ; add mem to ST(0)

fist Y ; store ST(0) to mem int Y = N + X fstp Z ; store ST(0) to mem real8 Z = N + X

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Changing the Rounding Mode

„ The RC field (bits 11 and 10) of the FPU Control Word determines how the FPU will round results:

¾ 00 = Round to nearest, or to even if equidistant (initialized state) 01 = Round down (toward -infinity)

10 = Round up (toward +infinity) 11 = Truncate (toward 0) ( )

.data

N SDWORD 20 X REAL8 3.5 Z REAL8 ?

ctrlWord WORD ? .code

fstcw ctrlWord ; store control word or ctrlWord, 110000000000b ; set RC = truncate fldcw ctrlWord, ctrlWord ; load control word fild N ; load integer into ST(0)

fadd X ; add mem to ST(0)

fist Y ; store ST(0) to mem int Y = 23

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Masking and Unmasking Exceptions

„ Exceptions are masked by default

¾ Divide by zero just generates infinity, without halting the program

.data

ctrlWord WORD ? val1 DWORD 1 val2 REAL8 0.0 .code

fild val1 ; load int into ST(0)

fdiv val2 ; ST(0) = positive infinity fstcw ctrlWord ; get the control word and ctrlWord,1111111111111011b ; unmask divide by zero fldcw ctrlWord ; load it back into FPU fild val1 ; load int into ST(0)

fdiv val2 ; MS Windows will show exception

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Floating-Point Addition

Numbers to be added:

x = 2 1.00101101 y = 2 1.11101101

5 ×

×

Operand with smaller exponent

1

(±2e1s1) (±2e2s2)

+ (±2e1(s2 / 2e1–e2)) = ±2e1(s1 ± s2 / 2e1–e2)

Operands after alignment shift:

x = 2 1.00101101

y = 2 0.000111101101 y 2 1.11101101×

5

×

× Extra bits to be

rounded off

to be preshifted

Result of addition:

s = 2 1.010010111101

s = 2 1.01001100 × Rounded sum

×

5

5 5

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Hardware for Floating-Point

Addition

A lig n

s ig nific a nd s P o s s ib le s w a p

& c o m p le m e n t U np a c k

C on tr ol

Inp u t 1

S ig n ifican ds E xp o n e n ts

S ig ns

S u b Mu x

Inp u t 2

Ad d′S u b

N o rm a lize

& ro u nd A d d s ig nific a nd s

C on tr ol

& s ign logic

P a c k

O u tp ut

S ig n ifican d E xp o n e n t

S ig n

±

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Figure

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