An introduction to Digital Signal Processors (DSP) Using the C55xx family

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Jonathan Kelley
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1 An introduction to Digital Signal Processors (DSP) Using the C55xx family

2 Group status (~2 minutes each) 5 groups stand up What processor(s) you are using Wireless? If so, what technologies/chips are you using? If not, what is your primary communication bus/scheme? What roadblocks/concerns/issues are you currently worried about We re going to jump back to switching regulators later. Bring slides for next time. I wanted to get through all of DSP/specialized processors today.

3 There are different kinds of embedded processors There are a fair number of different kinds of microprocessors used in embedded systems Microcontrollers Small, fairly simple devices. Non-volatile storage. Generally a fair bit of basic I/O (GPIO, SPI, etc.) Processor More-or-less a desktop processor with favorable power numbers. Atom, ARM A8, etc. System on a Chip Generally more CPU power than a microcontroller, but has lots of add-ons including perhaps analog I/O and specialized devices (Ethernet controller, LCD controller, FPGA) etc.

4 Digital Signal Processor (DSP) DSP chips are optimized for high performance/low power on very specific types of computation. Price: C5515 hits 100MHz Tasks: 0.22mW/MHz@(100 or 120) 0.15mW/MHz@(60 or 75) Filtering, FFT are the big ones.

5 Fixed point vs. floating point A reasonable way to break down DSPs: Floating point No floating point (Fixed point) Floating point makes things a lot easier for the programmer. Fixed point A good DSP programmer can often get better power numbers with fixed point. But can be a ton of work.

6 Basic fixed point Qn is a naming scheme used to describe fixed point numbers. n specifies the digit which is the last before the radix point. So a normal integer is Q0. Examples 0110 is 6 in binary 0110 as a Q2 is 1.5 Numbers are generally 2 s complement 1100 is as Q3 is -0.5

7 Factoids Signed x-bit Q x-1 numbers represent values from -1 to (almost) 1. This is the form typically used because two numbers in that range multiplied by each other are still in that range. Multiplying two 16-bit Q15 numbers yields?

9 And this is important

10 Lowpass filter template 10

11 FIR filter Basic idea is to take an input, x, but it into a big (and wide) shift register. Multiply each of the x values (old and new) by some constant. Sum up those product terms. Example: Say b 0 =.5, b 1 =.75, and b 2 =.25 x is 1, -1, 0, 1, -1, 0 etc. forever. What is the output? y[ n] M b k 0 k x[ n k]

12 Automatic tools--matlab The figure directly above is from Matlab. You specify the various parameters (f pass, f stop, p, A p, A s, etc.) and it will generate the b x values needed. If parameters are too difficult, this could be huge (500+ z -1 blocks) In that case, we may want to use an IIR filter. Those are feedbackbased and are a bit more touchy (prone to being unstable etc.).

13 Consider a traditional RISC CPU For reasonably large filter, b y doesn t fit in the register file. top: LD x++ LD b++ MULT a,x,b ADD accum, accum, a goto top (++ indicates auto increment) That s a lot of instructions Plus we need to shift the x values around. Also a loop Depending on how you count it, could be 8-10 instructions per Z -1 block

14 Some FIR tricks Most obvious is to use a circular buffer for the x values The problem with this is that you need more instructions to see if you ve fallen off the end of the buffer and need to wrap around And it s a branch, which is mildly annoying due to predictors etc.

A slightly different version Int16 FIR(Uint16 i) { Int32 sum; Uint16 j, index; sum=0; //The actual filter work for(j=0; j<lpl; j++) { index = ASIZE + i - j; X B 0 1 2 3 4 5 0 1 2 3 4 5 if(i>=j) else

15 A slightly different version Int16 FIR(Uint16 i) { Int32 sum; Uint16 j, index; sum=0; //The actual filter work for(j=0; j<lpl; j++) { index = ASIZE + i - j; X B if(i>=j) else index = i - j; index = ASIZE + i - j; This part is icky } sum += (Int32)in[index] * (Int32)LP[j]; } sum = sum + 0x ; // So we round rather than truncate. return (Int16) (sum >> 15); // Conversion from 32 Q30 to 16 Q15.

16 How fast could one do it? Well, I suppose we could try one instruction. MAC y, x++, z++ That s got lots of problems. No register use for the arrays so very heavy memory use 2 data elements from memory/cache 3 register file changes (pointers, accumulator) Plus we need to do a MAC and mults are already slow hurts clock period. Plus we need to worry about wrapping around in the circular buffer. Oh yeah, we need to know when to stop.

17 Data I need a lot of ports to memory Instruction fetch 2 data elements I need a lot of ports to the register file Or at least banked registers

18 C55xx Data buses (cont.) Twelve independent buses: Three data read buses Two data write buses Five data address buses One program read bus One program address bus So yeah, we can move data Registers appear to go on the same buses. Registers are memory mapped

19 OK, so data seems doable Well sort of, still worried about updating pointers. 2 data reads, 1 data write, need to update 2 pointers, running out of buses.

20 MAC? Most CPUs don t have a Multiply and accumulate instruction Too slow. Hurts clock period So unless we use the MAC a LOT it hurts. But for a DSP this is our bread and butter. So we ll take the 10% clock period hit or whatever so we don t have to use two separate instructions.

21 Wrapping around? Seems possible. Imagine a fairly smart memory. You can tell it the start address, end-of-buffer address and start-of-buffer address. It knows enough to be able to generate the next address, even with wrap around. This also takes care of our pointer problem

22 Circular Buffer Start Address Registers (BSA01, BSA23, BSA45, BSA67, BSAC) The CPU includes five 16-bit circular buffer start address registers Each buffer start address register is associated with a particular pointer A buffer start address is added to the pointer only when the pointer is configured for circular addressing in status register ST2_55.

23 Circular Buffer Size Registers (BK03, BK47, BKC) Three 16-bit circular buffer size registers specify the number of words (up to 65535) in a circular buffer. Each buffer size register is associated with particular pointers In the TMS320C54x-compatible mode (C54CM = 1), BK03 is used for all the auxiliary registers, and BK47 is not used.

24 By the way If we know the start and end of the buffer We know the length of the loop. Pretty much down to one instruction once we get going. The TI optimized FIR filter takes 25 cycles to set things up and then takes 1 cycle per MAC.

25 FFTs Another common thing we want to do is an FFT Tells you about the frequency parts of a signal Breaks down the signal into sin bins Useful in a lot of applications

26 Discrete Fourier Transform (DFT) The DFT is commonly written as: One might also use

27 The Fast Fourier Transform (FFT) Algorithm There are many fast algorithms (FFTs) that can be used to compute the Discrete Fourier Transform (DFT). Since the DFT is defined as: How many MACs do we need? Real or complex? Any algorithm which reduces this can be said to be fast

30 WN = e-j2π/n

31 FFT support FFTs typically take an array in normal order and return the output in bit reversed order. Or the other way around (as on prev. page) Hardware often able to swap the order of the address bits makes it (much) faster to deal with the bitreversed data.

32 And a bit more Other support? Verterbi is an algorithm commonly used for error correct/communication. Provide special instructions for it Mainly data movement, pointer, and compare instructions. Overflow is a constant worry in filters TI s accumulators provide 4 guard bits for detection. That s unheard of in a mainstream processor. Saves instructions for checking for overflow.

33 Why do I care again? To be clear the point of this slide set is For certain special purpose tasks, there are processors dedicated to doing those tasks Those processors can be both more powerful and lowerpower than a generic CPU at doing that task. The trick is that they are designed to do tasks that are common in that field. Here we see they have optimized a common DSP task (FIR filter stage) from about 8-10 assembly instructions down to 1! Other such devices? GPUs For graphics Move large amounts of data with simple operations SIMD Network processors 1 Pattern matching - the ability to find specific patterns of bits or bytes within packets in a packet stream. Key lookup - the ability to quickly undertake a database lookup using a key (typically an address in a packet) to find a result, typically routing information. Data bitfield manipulation - the ability to change certain data fields contained in the packet as it is being processed. Etc. 1 See for more details. List taken from there.

TMS320C3X Floating Point DSP

TMS320C3X Floating Point DSP Microcontrollers & Microprocessors Undergraduate Course Isfahan University of Technology Oct 2010 By : Mohammad 1 DSP DSP : Digital Signal Processor Why A DSP? Example Voice