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ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Applications of Distributed Arithmetic to Digital Signal Processing:
A Tutorial Review
VLSI Signal Processing台灣大學電機系吳安宇
Ref: Stanley A. White, “Applications of Distributed Arithmetic to Digital Signal Processing: A Tutorial
Review,” IEEE ASSP Magazine, July, 1989
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Outline
Distributed Arithmetic (DA) Introduction
Technical overview of DA
Increasing the speed of DA multiplication
Application of DA to a biquadratic digital filter
Conclusions
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Distributed Arithmetic (DA, 1974) Introduction
The most-often encountered form of computation in DSP:
Sum of product
Dot-product
Inner-product
Executed most efficiently by DA
By careful design one may reduce gate count in a signal processing arithmetic unit by a number seldom smaller then 50% and often as large as 80%
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technical overview of DA
Advantage of DA: efficiency of mechanization
A frequently argued:
Slowness because of its inherent bit-serial nature (not true)
Some modifications to increase the speed by employing techniques:
Plus more arithmetic operations
Expense of exponentially increased memory
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -continued I
The sum of product:
where xk is a 2’s-complement binary number scaled such that | xk |<1 Ak is fixed coefficients
xk : {bk0, bk1, bk2……, bk(N-1) } , word length=N
where bk0 is the sign bit
Express each xk as:
(2) 代入 (1) =>
K
kkk xAy
1(1)
1
10 2
N
n
nknkk bbx (2)
K
k
N
n
nknkk bbAy
1
1
10 2 (3)
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -continued II
Critical step
where K=No. of taps (inputs), N: Wordlength of Data
K
k
N
n
nknkk bbAy
1
1
10 2 (3)
1
1 10
1
)(2N
n
K
kkk
nK
kknk bAbAy (4)
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -continued III
Consider the equation (4)
has only 2K possible values
has only 2K possible values
We can store it in a lookup-table(ROM): size=2*2K
1
1 10
1
)(2N
n
K
kkk
nK
kknk bAbAy
K
kknkbA
1
K
kkk bA
10 )(
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -continued IV
ExampleLet no. of taps K=4
and the fixed coefficients are A1=0.72, A2=-0.3, A3=0.95, A4=0.11
We need 22K = 32-word ROM (k=4)
1
1 10
1
)(2N
n
K
kkk
nK
kknk bAbAy
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
ExampleUnfolding
nnnnk
knk bAbAbAbAbA 44332211
4
1
)()()()(
)(
0,440,330,220,11
4
10
bAbAbAbA
bAk
kk
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Example -continued I
Hardware architecture
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Example -continued II
Shorten the table
eq. (4)
nnnnk
knk bAbAbAbAbA 44332211
4
1
4
10
4
10 )()(
kkk
kkk bAbA
1
1 10
1
)(2N
n
K
kkk
nK
kknk bAbAy (5)
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Hardware architecture
Only 16 words of ROM are required,now.
Example -continued II
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -advanced
Input
1
1
)1(0 22
N
n
Nnknkk bbx
1
10 2
N
n
nknkk bbx
2‘s-complement
1
1
)1(00 22
2
1 N
n
Nnknknkkk bbbbx (7)
(6)},......,{)]([2
1)1(10 nkkkkkk bbbxxx
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -advanced I
1
1
)1(00 22
2
1 N
n
Nnknknkkk bbbbx
1
0
)1(222
1 N
n
Nnknk cx
K
kkk xAy
1代入
1
0
)1(
1
)1(1
0
022222
1 N
n
Nnn
K
k
Nnkn
N
nk QbQcAy
Where and
K
kkn
kn c
AbQ
1 2)(
}1,1{0,
0,
)(
knknkn
knknkn cwhere
n
n
bb
bbc
K
k
kAQ
1 2)0(
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Technique overview -advanced II
Hardware architecture
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Increase the speed of DA multiplication
The way I:Plus more arithmetic operations
1
0
)1( 022N
n
Nnn QbQy Initial
condition
1
0
)1(1
)2(2
11
00 22....222
N
n
NN
NN
nn bQbQbQbQbQ
Even part Odd part
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
InitialCondition1/2*Q(0)
1
0
)1( 022N
n
Nnn QbQy
Odd part(sign}
Even part
Increase the speed of DA multiplicationHardware architecture of way I -at the expense of linearly increased memory & arithmetic operation
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Increase the speed of DA multiplicationThe way II: - at the expense of exponentially increased memory
ROM : 2*7 words => 1*128 words
Hardware architecture
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Transfer function of a typical biquadratic digital filter:
The time-domain description:
22
11
22
110
1)(
)(
zBzB
zAzAA
zX
zY
Tnnnnn yyxxxBBAAAzY ]][[)( 212121210
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Hardware architecture
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
The vector matrix equation
The relationships between two equations
1
1
1
210
222
111
n
n
n
n
n
n
v
u
x
dda
bca
cba
y
v
u
2121
211
2111212221212102
21022111
00
)()()(
)(
ccbbB
bbB
dbdcadbdcaccbbaA
bbadadaA
aA
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Normal form biquadratic filter
b1
z-1
c1
a1
d1
z-1
d2
a0
c2
z-1
b2
a2
xn yn
vn
un
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
DA realization
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Increase speed
1*3 BAAT DA structure 4*3 BAAT DA structure
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Increase speed II2048 word/ROM
require 4 ROM
4 operations
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
Application of DA to a biquadratic digital filter
Increase speed III32 word/ROM
require 8 ROM
8 operations
ACCESS IC LAB Graduate Institute of Electronics Engineering, NTU
ConclusionsDA is a very efficient means to mechanize computations that are dominated by inner products
If performance/cost ratio is critical, DA should be seriously considered as a contender
When a many computing methods are compared, DA should be considered. It is not always (but often) best, and never poorly.