ti_traning_for_c6000
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Hardware 1011 x 1110 10011010 Microcode 1011 x 1110 0000 1011. 1011.. 1011... 10011010
Chapter 1, Slide 12
Cycle Cycle Cycle Cycle
1 2 3 4
Cycle 5
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why NOT go digital?
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.
Processing Time n
We can say that we have a real-time application if:
Waiting Time ≥ 0
Chapter 1, Slide 8
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Chapter 1, Slide 6
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Real-time processing
DSP processors have to perform tasks in real-time, so how do we define realtime? 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:
X (k ) =
Discrete Cosine Transform
F (u ) =
∑ c(u). f ( x). cos 2 N u(2 x + 1)
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
π
Chapter 1, Slide 11
Chapter 1, Slide 4
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
With DSP it is easy to:
Change applications. Correct applications. Update applications.
Parameters to consider when choosing a DSP processor
Parameter I/O bandwidth: Serial Ports (number/speed) DMA channels Multiprocessor support Supply voltage Power management On-chip timers (number/width) Cost Package External memory interface controller JTAG TMS320C6211 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes TMS320C6711 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes
Additionally DSP reduces:
Noise susceptibility. Chip count. Development time. Cost. Power consumption.
Chapter 1, Slide 5 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Parameters to consider when choosing a DSP processor
Parameter Arithmetic format Extended floating point Extended Arithmetic Performance (peak) Number of hardware multipliers Number of registers Internal L1 program memory cache Internal L1 data memory cache Internal L2 cache TMS320C6211 (@150MHz) 32-bit N/A 40-bit 1200MIPS 2 (16 x 16-bit) with 32-bit result 32 32K 32K 512K TMS320C6711 (@150MHz) 32-bit 64-bit 40-bit 1200MFLOPS 2 (32 x 32-bit) with 32 or 64-bit result 32 32K 32K 512K
FIR filter with linear phase. Adaptive filters.
Chapter 1, Slide 3
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Analogue signal processing is achieved by using analogue components such as:
Chapter 1 Introduction
Learning Objectives
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. Programmable vs ASIC DSP. Texas Instruments’ TMS320 family.
C6711 Datasheet: \Links\TMS320C6711.pdf C6211 Datasheet: \Links\TMS320C6211.pdf
Chapter 1, Slide 13 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Hardware vs. Microcode multiplication
DSP processors are optimised to perform multiplication and addition operations. Multiplication and addition are done in hardware and in one cycle. Example: 4-bit multiply (unsigned).
Resistors. Capacitors. Inductors.
The inherent tolerances associated with these components, temperature, voltage changes and mechanical vibrations can dramatically affect the effectiveness of the analogue circuitry.
Chapter 1, Slide 9
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why do we need DSP processors?
Use a DSP processor when the following are required:
Large memory. Advanced operating systems.
Chapter 1, Slide 10 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
What are the typical DSP algorithms?
Chapter 1, Slide 2 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Digital signal processing techniques are now so powerful that sometimes it is extremely difficult, if not impossible, for analogue signal processing to achieve similar performance. Examples:
y ( n) =
∑a
N k =0
k
x ( n k )+
∑b
k =1
N
k
y (n k )
Convolution
y ( n) =
∑ x ( k ) h( n k ) ∑ x(n) exp[ j(2π / N )nk ]
n =0
N 1 x =0
N 1
Discrete Fourier Transform
y (n ) = ∑ a(k )x(n k )
k =0
Chapter 1, Slide 7 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
99
Real-time processing
Waiting Time n+1 Sample Time
Cost saving. Smaller size. Low power consumption. Processing of many “high” frequency signals in real-time.
Use a GPP processor when the following are required:
Why do we need DSP processors?
Why not use a General Purpose Processor (GPP) such as a Pentium instead of a DSP processor?
What is the power consumption of a Pentium and a DSP processor? What is the cost of a Pentium and a DSP processor?
The Sum of Products (SOP) is the key element in most DSP algorithms:
Algorithm Finite Impulse Response Filter Equation
y (0
M
k
x(n k )
Infinite Impulse Response Filter
Chapter 1, Slide 12
Cycle Cycle Cycle Cycle
1 2 3 4
Cycle 5
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why NOT go digital?
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.
Processing Time n
We can say that we have a real-time application if:
Waiting Time ≥ 0
Chapter 1, Slide 8
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Chapter 1, Slide 6
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Real-time processing
DSP processors have to perform tasks in real-time, so how do we define realtime? 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:
X (k ) =
Discrete Cosine Transform
F (u ) =
∑ c(u). f ( x). cos 2 N u(2 x + 1)
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
π
Chapter 1, Slide 11
Chapter 1, Slide 4
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
With DSP it is easy to:
Change applications. Correct applications. Update applications.
Parameters to consider when choosing a DSP processor
Parameter I/O bandwidth: Serial Ports (number/speed) DMA channels Multiprocessor support Supply voltage Power management On-chip timers (number/width) Cost Package External memory interface controller JTAG TMS320C6211 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes TMS320C6711 (@150MHz) 2 x 75Mbps 16 Not inherent 3.3V I/O, 1.8V Core Yes 2 x 32-bit US$ 21.54 256 Pin BGA Yes Yes
Additionally DSP reduces:
Noise susceptibility. Chip count. Development time. Cost. Power consumption.
Chapter 1, Slide 5 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Parameters to consider when choosing a DSP processor
Parameter Arithmetic format Extended floating point Extended Arithmetic Performance (peak) Number of hardware multipliers Number of registers Internal L1 program memory cache Internal L1 data memory cache Internal L2 cache TMS320C6211 (@150MHz) 32-bit N/A 40-bit 1200MIPS 2 (16 x 16-bit) with 32-bit result 32 32K 32K 512K TMS320C6711 (@150MHz) 32-bit 64-bit 40-bit 1200MFLOPS 2 (32 x 32-bit) with 32 or 64-bit result 32 32K 32K 512K
FIR filter with linear phase. Adaptive filters.
Chapter 1, Slide 3
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Analogue signal processing is achieved by using analogue components such as:
Chapter 1 Introduction
Learning Objectives
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. Programmable vs ASIC DSP. Texas Instruments’ TMS320 family.
C6711 Datasheet: \Links\TMS320C6711.pdf C6211 Datasheet: \Links\TMS320C6211.pdf
Chapter 1, Slide 13 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Hardware vs. Microcode multiplication
DSP processors are optimised to perform multiplication and addition operations. Multiplication and addition are done in hardware and in one cycle. Example: 4-bit multiply (unsigned).
Resistors. Capacitors. Inductors.
The inherent tolerances associated with these components, temperature, voltage changes and mechanical vibrations can dramatically affect the effectiveness of the analogue circuitry.
Chapter 1, Slide 9
Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why do we need DSP processors?
Use a DSP processor when the following are required:
Large memory. Advanced operating systems.
Chapter 1, Slide 10 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
What are the typical DSP algorithms?
Chapter 1, Slide 2 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
Why go digital?
Digital signal processing techniques are now so powerful that sometimes it is extremely difficult, if not impossible, for analogue signal processing to achieve similar performance. Examples:
y ( n) =
∑a
N k =0
k
x ( n k )+
∑b
k =1
N
k
y (n k )
Convolution
y ( n) =
∑ x ( k ) h( n k ) ∑ x(n) exp[ j(2π / N )nk ]
n =0
N 1 x =0
N 1
Discrete Fourier Transform
y (n ) = ∑ a(k )x(n k )
k =0
Chapter 1, Slide 7 Dr. Naim Dahnoun, Bristol University, (c) Texas Instruments 2004
99
Real-time processing
Waiting Time n+1 Sample Time
Cost saving. Smaller size. Low power consumption. Processing of many “high” frequency signals in real-time.
Use a GPP processor when the following are required:
Why do we need DSP processors?
Why not use a General Purpose Processor (GPP) such as a Pentium instead of a DSP processor?
What is the power consumption of a Pentium and a DSP processor? What is the cost of a Pentium and a DSP processor?
The Sum of Products (SOP) is the key element in most DSP algorithms:
Algorithm Finite Impulse Response Filter Equation
y (0
M
k
x(n k )
Infinite Impulse Response Filter