C1. Digital Signal Processors
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There a numerous websites for speech/audio signal processing and recognition on the internet.
Here we have a list of some of the commonly used websites, which can be linked for tutorials,
discussions, papers, example code etc.
http://www.phys.unsw.edu.au/~jw/dB.html
Introduction to the definition of Decibels for measuring energy/volume of speech/audio signals.
http://www.phys.unsw.edu.au/~jw/hearing.html
Introduction (including interactive demos) to curves of equal loudness.
http://www.phys.unsw.edu.au/music/
Homepage for "Music Acoustics".
http://www.phys.unsw.edu.au/~jw/musFAQ.html
FAQ for "Music Acoustics".
http://www.wotsit.org
File formats for various kinds, including audio and music.
http://www.speech.cs.cmu.edu/comp.speech/index.html
FAQ for the newsgroup "Comp.Speech".
http://www.bdti.com/faq/dsp_faq.htm
FAQ for the news group "Comp.DSP".
http://www.harmony-central.com/Effects/effects-explained.html
Introduction to audio effects, including many examples.
http://www.slideshare.net/fcharlot/digital-signal-processor-evolution-over-the-last-30-years
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Introduction
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Why process signals digitally?
Definition of a real-time application.
Why use Digital Signal processing processors?
What are the typical DSp algorithms?
Parameters to consider when choosing a DSP processor.
Main Architectural Features of DSPs
DSP market
Texas Instruments’ TMS320 family.
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Why use digital signal processing?
•Analog signal processing is achieved by using analogue
components such as:
✓Resistors.
✓ Capacitors.
✓ Inductors.
•The inherent tolerances associated with these components,
temperature, voltage changes, components aging and mechanical
vibrations can dramatically affect the effectiveness of the analog
circuit.
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Why use digital signal processing?
With DSP it is easy to:
• Change applications
• Correct applications
• Update applications
DSP reduces:
• Noise susceptibility
• Chips number
• Development time
• Cost
• Power consumption
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Why NOT use digital signal processing?
•High frequency signals cannot be processed digitally because of
two reasons:
✓Analog to Digital Converters, ADC cannot work fast enough
✓The application can be too complex to be performed in real-time
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Real-time processing
• DSP processors have to perform tasks in real-time, so how do
we define real-time?
• The definition of real-time depends on the application
• Example: a 100-tap FIR filter is performed in real-time if the
DSP can perform and complete the following operation
between two samples read:
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Real-time processing
•We can say that we have a real-time application if:
Waiting Time ≥ 0
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What are the typical DSP algorithms?
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•The Sum of Products (SOP) is the key element in most DSP algorithms !!!
Hardware vs. Microcode multiplication
• DSP processors are optimized to perform multiplication
and addition operations.
• Multiplication and addition are done in hardware in one
cycle.
• Example: 4-bit multiply (unsigned).
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What is special for DSP?
• DSP = A class of microprocessors optimized for DSprocessing
• DSP have advantage in speed, cost and energy efficiency
• DSPs tend to be used for 1 program, not many programs.
– Hence OSes are much simpler, there is no virtual memory or protection,..
• DSPs sometimes run hard real-time apps (computational intensive)
– You must account for anything that could happen in a time slot
– All possible interrupts or exceptions must be accounted for and their
collective time be subtracted from the time interval (Interrupt handling:
the interrupts or exceptions reduce the time for computation)
– Therefore, exceptions are BAD!
• DSPs have an infinite continuous data stream to process in
time slots from the environment
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(e.g. audio processing with 48 KHz sampling rate)
What is special for DSP?
• The “MIPS/MFLOPS” of DSPs is speed of Multiply-Accumulate (MAC)
– DSP are judged by whether they can keep the multipliers busy 100% of the
time.
• The "SPEC" of DSPs are 4 algorithms:
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Inifinite Impulse Response (IIR) filters
Finite Impulse Response (FIR) filters
FFT, and
convolvers
• In DSPs, algorithms are king!
– Binary compatibility not an issue
• Software is not (yet) king in DSPs.
– People still write in assembly language for a product to minimize the die area
for ROM in the DSP chip.
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What is special for DSP?
➢DSP architectures are molded by DSP algorithms
➢Fast Multipliers
➢Multiple Execution Units
➢Efficient Memory Access
➢Data Format
➢Efficient Zero-Overhead Looping
➢Streamlined I/O
➢Specialized Instruction Sets
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➢ Fast Multipliers:
Main operations: multiply & add
-Multiplication is one of the most common operations in signal
processing (convolution, FIR/IIR filtering, FFTransforms...)
-Need fast multipy-accumulate operations shift, multiply and add
in a loop. Each require one or more cycle.
-Need to develope special hardware for multiplication
1982- Texas Instruments(TMS32010) (in a single clock cycle)
-All modern DSP processors include at least one or more
“dedicated, single-cycle multiplier” or combined multiplyaccumulate unit (MAC).
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➢ Multiple Execution Units
• Need to perform high computational tasks:
- In real time
- e.g. Filtering signals in 10-100KHz sampling rate in real time
• Several independent execution units required
- Should operate in parallel
- e.g. Arithmetic Logic Unit (ALU) and a shifter in parallel to
MAC units
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➢ Efficient Memory Access
Executing a MAC in a single cycle means:
→ Fetching the MAC instruction in a single cycle
→ Fetching a data sample in a single cycle
→ Fetching a filter coefficient in a single cycle
So, good performance requires high memory bandwidth!
Commonly used approach:
- Use two or more separate memory banks:
-Each have its own bus
-Each could be read or written during every cycle
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➢ Efficient Memory Access
More optimized DSP processors
General purpose processors
SISD (von Neumann)
Bus
OR
HARVARD
Early DSP processors
HARVARD modified
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➢ High memory bandwidth requirement
❑ Support via dedicated hardware for calculating memory
addresses:
→ Address Generation Units
❑ In DSP algorithms memory access is very predictable
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E.g: FIR filter: coefficients accessed sequentially
❑ Use:
1. Register indirect addressing with post increment
➢ Increment address pointer where repetitive computations are
performed on a series of data.
2. Circular Addressing
➢ Allows processor to access data sequentially and then automatically
wrap around to the beginning address
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➢ Data Format
✓ DSP algorithms generally use floating point formats
✓ Fixed point processors:
➢ Cheaper and less power consuming
✓ Floating point formats require more complex hardware
✓ Use shortest data word width that will provide adequate accuracy
➢ Consider the cost & energy consumption
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➢ Data Format:
• Most fixed point DSP processors use 16 bit data words.
– Sufficient for many applications
• Some use 20, 24 or 32 bit data word for better accuracy
• Most DSP processors include one or more accumulator regs
• Accumulator Registers:
– wider than other registers
– Provide extra guard bits to avoid overflow
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➢ Efficient Zero Overhead Looping
• DSP algorithms have many loops:
– Use efficient looping
• Special loop: Zero Overhead Looping
– No loop counter
– No branching back to the top of the loop
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➢ Streamlined I/O:
• Specialized serial or parallel I/O interfaces
• Streamlined I/O handling mechanisms
• E.g.:
- Low overhead interrupts
- Direct memory access, DMA.
– Synchronous serial ports
– Parallel ports
– Timers
– On-chip A/D, D/A
– converters
– Host ports
– Bit I/O ports
– On-chip DMA controller
– Clock generators
– On-chip peripherals often designed for
– “background” operation, even when core is powered down.
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➢ Specialized Instruction Sets
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Two goals in instruction sets:
1. Make maximum use of hardware, increase efficiency
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Programmer can specify parallel operations in single inst.s
2. Minimize memory space required to store DSP programs.
(Memory is a cost!)
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Keep inst.s short.
→ Use mode bits rather than encoding
→ Restrict operations to specific registers
→ Restrict operation combinations in the inst.
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This makes DSP instructions complicated!!
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➢ Specialized Instruction Sets:
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DSPs aren’t usually programmed in HLL: C,C++..etc
Program optimization is essential
– Programmer should optimize code in assembly level
More easier inst. set, more desirable it is for programmer.
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Applications Development
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Choosing a DSP Processor
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right DSP depends on the application; a good choice for
one application might be a poor choice for another.
• Some useful criteria for choosing a DSP are:
- arithmetic format
- data width
- speed
- memory organization
- ease of development
- multiprocessor support
- power consumption
- cost
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Main Architectural Features of DSPs
- Data path configured for DSP
• Fixed-point arithmetic
• MAC- Multiply-accumulate
- Multiple memory banks and buses
• Harvard Architecture
• Multiple data memories blocks
- Specialized addressing modes
• Bit-reversed addressing
• Circular buffers
- Specialized instruction set and execution control
• Zero-overhead loops
• Support for MAC
- Specialized peripherals for DSP
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Compound Annual Growth Rate = CAGR
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Different Needs? Multiple Families!
’C6000
(’C62x, ’C67x)
’C5000
‘C3x ‘C4x ‘C8x
(’C54x)
‘C5x
’C2000
(’C20x,’C24x)
‘C1x ‘C2x
• Comm Infrastructure
Best MIPS per:
Watt / Dollar/ Size
• Wireless Telephones
Lowest Cost
Control Systems
•Storage
Maximum Performance
Multi-Channel / Function
• xDSL
• Imaging, Video
• Modems / Telephony
• VoIP
•Motor Control
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• Architectures for developing DSp applications
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ASIC (Application Specific IC)
FPGA (Field Programmable Gate Array )
ASSP (Application-specific standard products )
GPP (General purpose processors)
DSP
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DSP Application – Mobile Phone
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