The document discusses digital signal processing (DSP) systems and their implementation in very-large-scale integration (VLSI) design. It highlights typical DSP algorithms, advantages of both analog and digital signal processing, the performance metrics of DSP systems, and the challenges related to power consumption and system complexity. Additionally, it covers various representations of DSP algorithms and the evolution of scaling in CMOS technology.

1. 1
Introduction to
Digital Signal
Processing Systems
Shao-Yi Chien

2. DSP in VLSI Design Shao-Yi Chien 2
Outline
 Introduction
 Typical DSP algorithms
 Scaled CMOS technologies
 Representations of DSP algorithms

3. DSP in VLSI Design Shao-Yi Chien 3
Analog Signal
 Real-word signal
 Infinite accuracy on time and magnitude
t
f
f(5.17382…)=3.7416…

4. DSP in VLSI Design Shao-Yi Chien 4
Digital Signal
 Get after sampling and quantization
 Finite accuracy on time and magnitude
 Easy to process with digital processing
element
t
f
t
f
Sampling Quantization
f(5)=4

5. DSP in VLSI Design Shao-Yi Chien 5
Typical DSP Systems
Sampling
Quantization
Reconstruction
Inverse Quantization
SENSORS
Digital Inputs
Analog Inputs
DIGITAL SIGNAL
PROCESSING
A/D D/A
User Interface Display
ACTUATORS
Digital Outputs
Analog Outputs

6. DSP in VLSI Design Shao-Yi Chien 6
Advantages of Analog Signal
Processing
 Can operate in very high frequency
 Sometimes low area
 Low power

7. DSP in VLSI Design Shao-Yi Chien 7
Advantages of Digital Signal
Processing (DSP)
 More robust
 Insensitive to environment and component tolerance
 The accuracy can be controlled better
 Can cancel the noise and interference while
amplifying the signal
 Predictable, repeatable behavior
 Can be stored and recovered, transmitted and
received, processed and manipulated without error

8. DSP in VLSI Design Shao-Yi Chien 8
Features of DSP Systems
 Real-time throughput requirement
So-called hard real-time systems
 Data-driven property
 Non-terminating program

9. DSP in VLSI Design Shao-Yi Chien 9
Hard Real-Time Systems
Courtesy Warner Brothers Studios

10. DSP in VLSI Design Shao-Yi Chien 10

11. DSP in VLSI Design Shao-Yi Chien 11
Performance Metrics of DSP
Systems
 Hardware circuitry and resources (area)
 Speed of execution
 Power consumption
 Finite word length performance

12. DSP in VLSI Design Shao-Yi Chien 12
Characteristics of DSP Systems
(1/4)
 Data format
1D speech
2D image
3D video
time
time

13. DSP in VLSI Design Shao-Yi Chien 13
Characteristics of DSP Systems
(2/4)
 Algorithms

14. DSP in VLSI Design Shao-Yi Chien 14
Characteristics of DSP Systems
(3/4)
 Sample
rates

15. DSP in VLSI Design Shao-Yi Chien 15
Characteristics of DSP Systems
(4/4)
 Clock rates
 Numeric representations

16. DSP in VLSI Design Shao-Yi Chien 16
Standard Digital Signal
Processors (1/2)
 Allow rapid prototyping and time-to-market
 Sometimes, the execution speed and code
size is reasonably good
 Not always cost effective
 Often cannot meet the requirements of
throughput, power consumption, and size

17. DSP in VLSI Design Shao-Yi Chien 17
Standard Digital Signal
Processors (2/2)
 DSP Architectures
Harvard architecture
MAC
Fixed-point arithmetic
 Alternatives:
DSP-enhanced CPU
GPU

18. DSP in VLSI Design Shao-Yi Chien 18
Application-Specific ICs for DSP
(1/2)
 Better performances
Processing capacity
Power consumption
Pin-restriction problem
 Main problem: the system is very complex
to design
Long time-to-market

19. DSP in VLSI Design Shao-Yi Chien 19
Application-Specific ICs for DSP
(2/2)
 Large design space
 Hard to find optimal solution
 Systemspecification
algorithmhardware
architecturelogic
implementationVLSI
implementation
 ASIC  Accelerator design in
an SoC

20. DSP in VLSI Design Shao-Yi Chien 20
Typical DSP Algorithms
 Convolution
 Correlation
 Digital filters
 Adaptive filters
 Motion estimation
 Discrete cosine transform (DCT)
 Vector quantization (VQ)
 Viterbi algorithm and dynamic programming
 Decimator and expander
 Wavelets and filter banks

21. DSP in VLSI Design Shao-Yi Chien 21
Convolution (1/2)
 Can be used to describe the behavior of a
linear time-invariant systems
x(n): input signal
y(n): output signal
h(n): unit-sample response

22. DSP in VLSI Design Shao-Yi Chien 22
Convolution (2/2)
 Finite impulse response (FIR) system
 Infinite impulse response (IIR) system

23. DSP in VLSI Design Shao-Yi Chien 23
Digital Filters
 LTI, causal filter
 M-tap finite impulse response filter

24. DSP in VLSI Design Shao-Yi Chien 24

25. DSP in VLSI Design Shao-Yi Chien 25
Moore’s Law

26. DSP in VLSI Design Shao-Yi Chien 26
Scaled CMOS technology
(Moore’s Law) (1/3)

27. DSP in VLSI Design Shao-Yi Chien 27
Scaled CMOS technology
(Moore’s Law) (2/3)
180
160
140
120
100
80
Maximum power for high
performance with heat sink (W)
0.9
1.2
1.5
1.8
2.5
3.3
Power supply voltage (V) for
desktop
7-8
6-7
6
5-6
5
4-5
Maximum number of wiring levels
(logic), on chip
1,100
1,000
800
600
450
300
Chip frequency (MHz) for a
high-performance on-chip clock
430M
210M
50M
26M
14M
5M
ASIC (gate per chip)
800M
350M
150M
64M
28M
12M
Microprocessor transistor per chip
( 2.3 times per generation)
64G
16G
4G
1G
256M
64M
Memory in bits/chip
(DRAM/FLASH)
0.07
0.10
0.13
0.18
0.25
0.35
Minimum feature of size (um)
2010
2007
2004
2001
1998
1995
Year of first DRAM shipment
Source: SIA (Semiconductor Industry Association) road map
ITRS: International Technology Roadmap for Semiconductors
http://www.itrs.net/

28. DSP in VLSI Design
Scaled CMOS technology
(Moore’s Law) (3/3)
Shao-Yi Chien 28

29. DSP in VLSI Design Shao-Yi Chien 29
DSP and VLSI
 Modern DSP
 Well suite to VLSI implementation
 Feasible or economically viable only if implemented
using VLSI technologies
 VLSI
 Large investmentneed large volume of products
 Communication
 Consumer applications
 Necessary performance requirement (especially real-
time requirement)
 DSP systems are hard real-time systems

30. DSP in VLSI Design Shao-Yi Chien 30
Example: the Chip for PS2
’98
239 mm2
@0.25um
’98
279 mm2
@0.25um
’99
110 mm2
@0.18um
’01
75 mm2
@0.14um
’99
108 mm2
@0.18um
’02
77 mm2
@0.16um
Emotion Engine
Graphics Synthesizer
’04
87 mm2
@90nm
-----------------------------------
Slide No.20
Ken Kutaragi
ISSCC2006 Plenary Talk
Feb 6, 2006 SF, CA
----------------------------------------
Ref: K. Kutaragi, The Future of Computing for "Real-Time Entertainment," ISSCC2006

31. DSP in VLSI Design Shao-Yi Chien 31
Problems: Interconnection

32. DSP in VLSI Design Shao-Yi Chien 32
Problems: Increasing Static Power
 VDD decreases
 Save dynamic power
 Protect thin gate oxides and short channels
 No point in high value because of velocity sat.
 Vt must decrease to
maintain device performance
 But this causes exponential
increase in OFF leakage
 Major future challenge
Static
Dynamic
[Moore03]

33. DSP in VLSI Design Shao-Yi Chien 33

34. DSP in VLSI Design Shao-Yi Chien 34
Problems: Power Density
 Intel VP Patrick Gelsinger (ISSCC 2001)
 If scaling continues at present pace, by 2005, high
speed processors would have power density of
nuclear reactor, by 2010, a rocket nozzle, and by
2015, surface of sun.
 “Business as usual will not work in the future.”
 Intel stock dropped 8%
on the next day
 But attention to power is
increasing
[Gelsinger01]

35. DSP in VLSI Design Shao-Yi Chien 35
1950 1960 1970 1980 1990 2000 2010 2020
Module
Heat
Flux
(W/cm
2
)
Year of Announcement
Ultra-low Vdd
3-D integration ?
bipolar
CMOS
Problems: Scaling and the Power
Crisis
After: R. Schmidt et al., IBM J. R&D, (2002).
Delay 3-4X 
Power 15X 
Density 50X 

36. DSP in VLSI Design
FinFET
Shao-Yi Chien 36

37. DSP in VLSI Design
FinFET
Shao-Yi Chien 37

38. DSP in VLSI Design
FinFET
Shao-Yi Chien 38

39. DSP in VLSI Design Shao-Yi Chien 39
Science and Technology Strategy / Roadmap
2000 2005 2010 2015 2020 2025 2030
Plan B: Subsytem Integration
R D
Plan C: Post Si CMOS Options
R R&D
Plan Q:
R D
Quantum Computing
Plan A: Extending Si CMOS
R D
Ref: Tze-Chiang Chen, "Where Si-CMOS is Going: Trendy Hype vs. Real Technology," ISSCC2006.

40. DSP in VLSI Design Shao-Yi Chien 40
More Moore & More than Moore !!!

41. DSP in VLSI Design
2.5D Interposer
Shao-Yi Chien 41

42. DSP in VLSI Design
3D-IC Technology
Shao-Yi Chien 42

43. DSP in VLSI Design
Heterogeneous System Integration
Shao-Yi Chien 43
[TSMC 2015]

44. DSP in VLSI Design
InFO (Integrated Fan Out)
Shao-Yi Chien 44
[TSMC 2015]

45. DSP in VLSI Design
CoWoS (Chip-On-Wafer-On-Substrate)
Shao-Yi Chien 45
[TSMC 2015]

46. DSP in VLSI Design
Example of CoWoS
Shao-Yi Chien 46
[TSMC 2015]

47. DSP in VLSI Design Shao-Yi Chien 47
DSP Architecture Design?
 Given DSP algorithms, find the “best”
solution in the design space under certain
constraints
 Or, modified or develop the algorithm to be
“hardware oriented” or “hardware friendly,”
and then develop the hardware
architecture

48. DSP in VLSI Design Shao-Yi Chien 48
Abstraction Layers
 System (ex: MP3 player)
 Algorithm (ex: FIR filter)
 Hardware architecture (ex: array architecture,…)
 Arithmetic units (ex: multiplier, adder, …)
 Logic gates (ex: AND, OR, …)
 Transistors (ex: NMOS, PMOS)
 Layout

49. DSP in VLSI Design Shao-Yi Chien 49
The Higher the Abstraction,
The Larger Design Space
System Level
Algorithm Level
Hardware Architecture Level
Arithmetic Level
Gates Level
Transistors Level
Physical Level
Design Space

50. DSP in VLSI Design Shao-Yi Chien 50
The Higher the Abstraction,
The More Important
System Level
Algorithm Level
Hardware Architecture Level
Arithmetic Level
Gates Level
Transistors Level
Physical Level
Performance Space

51. DSP in VLSI Design Shao-Yi Chien 51
Representations of DSP
Algorithms
 DSP algorithms: nonterminating program
 Iteration period
 Sampling rate
 Latency
 Throughput
 Clock frequency
 Critical path

52. DSP in VLSI Design Shao-Yi Chien 52
Graphical Representations of
DSP Algorithms
 Can bridge the gap between algorithmic
descriptions and structural implementations
 Block diagram
 Signal-flow graph (SFG)
 Data-flow graph (DFG)
 Dependence graph (DG)

53. DSP in VLSI Design Shao-Yi Chien 53
Block Diagram (1/5)
 The most frequently used representation
 Can be constructed with different levels of
abstraction
 Can be directly mapped to circuits
implementation

54. DSP in VLSI Design Shao-Yi Chien 54
Block Diagram (2/5)

55. DSP in VLSI Design Shao-Yi Chien 55
Block Diagram (3/5)
 Data broadcast FIR filter

56. DSP in VLSI Design Shao-Yi Chien 56
Block Diagram (4/5)
(4ns)
(1ns)
Critical path: 4+1+1=6ns
Max clock frequency = 1s/6ns=167MHz

57. DSP in VLSI Design Shao-Yi Chien 57
Block Diagram (5/5)
Critical path: 4+1=5ns
Max clock frequency = 1s/5ns=200MHz

58. DSP in VLSI Design Shao-Yi Chien 58
Signal Flow Graph (SFG) (1/4)
 Nodes k
Computation or task
 Directed edges (j, k)
Linear transformation
Source node
Sink node

59. DSP in VLSI Design Shao-Yi Chien 59
Signal Flow Graph (SFG) (2/4)

60. DSP in VLSI Design Shao-Yi Chien 60
Signal Flow Graph (SFG) (3/4)
 Transpose
property

61. DSP in VLSI Design Shao-Yi Chien 61
Signal Flow Graph (SFG) (4/4)
 Used in digital filter structure and analysis
of finite word-length effects
 Only applicable to linear networks
 Cannot be used to describe multi-rate
DSP systems

62. DSP in VLSI Design Shao-Yi Chien 62
Data-Flow Graph (DFG) (1/4)
 Nodes
Computations
 Directed edges
Data paths (communication)
Has a nonnegative number of delays

63. DSP in VLSI Design Shao-Yi Chien 63
Data-Flow Graph (DFG) (2/4)
y(n)=x(n)+ay(n-1)
A: +
B: X
Execution time
Synchronous DFG
Rate

64. DSP in VLSI Design Shao-Yi Chien 64
Data-Flow Graph (DFG) (3/4)
 Data-driven property of DSP
Any node can fire whenever all the input data
are available
Intra-iteration precedence constraint
Inter-iteration precedence constraint
 Can be used to describe both linear
single-rate and nonlinear multi-rate DSP
systems

65. DSP in VLSI Design Shao-Yi Chien 65
Data-Flow Graph (DFG) (4/4)
 Use single rate DFG (SRDFG) to represent multi-rate
DFG (MRDFG)
3fA=5fB
2fB=3fC

66. DSP in VLSI Design Shao-Yi Chien 66
Dependence Graph (1/2)
 A directed graph that shows the
dependence of the computation
 Node: computation
 No node in a DG is ever reused on a
single computation basis
Single-assignment representation
 Used for systolic-array design

67. DSP in VLSI Design Shao-Yi Chien 67
Dependence Graph (2/2)

68. DSP in VLSI Design Shao-Yi Chien 68
DFG v.s. DG
 DFG
 Nodes only cover
computation in one
iteration, and will be
reused iteratively
 Contain delay
elements
 DG
 Contains computation
for all iterations, and is
used only once
 No delay elements
contained