Fast Fourier Transforms on Motorola's Digital Signal Processors

More documents

Recommendations

Info

5.2.2 Fully Optimized Complex FFT for the DSP96002 APPENDIX A presents a fully optimized program for 1024-point complex input FFT for the DSP96002. Like the fully optimized program for the DSP56001/2, this program takes advantage of trivial twiddle factors in all of the passes as follows: • Naturally, the first and second passes are combined into a radix-4 pass with each radix-4 butterfly requiring 8 instruction cycles. This is equal to 2 instruction cycles per radix-2 butterfly. • All trivial butterflies in the middle passes are calculated by a separate routine. • Each pass is written in a separate section to reduce the DO loop overhead. To reduce the program length, the special radix-4 and normal radix-2 butterflies are programmed in subroutines. Only two-nested DO loops are used for each pass. • The last two passes are also combined into a radix-4 pass. After the combination, the number of instruction cycles per radix-2 butterfly is decreased from 5 to 4.25 instruction cycles. Because radix-4 butterflies are used in the last two passes, an extra set of 256 complex twiddle factors must be present in the external memory. These twiddle factors are generated off-line by MATHLAB software. 5-12 MOTOROLA
The fully optimized 1024-point complex FFT uses 18891 instruction cycles; while the optimized 1024point complex FFT program (seen on the Motorola DSP bulletin board; Dr. BuB) uses 20958 instruction cycles. Optimization saves 20,958-18,891=2,067 instruction cycles which equals about 10% cycle time of the optimized code. Also note that the fully optimized code only works with fixed data length. ■ MOTOROLA 5-13
Page 1 and 2:
Motorola’s High-Performance DSP T
Page 3 and 4:
SECTION 1 Definition and History SE
Page 5 and 6:
SECTION 5 Optimizing Performance of
Page 7 and 8:
APPENDIX B Real-Valued Input FFT Ta
Page 9 and 10:
Figure 4-3 Figure 4-4 Figure 4-5 Fi
Page 11 and 12:
Table 8-1 Table 8-2 Table 8-3 Table
Page 13 and 14:
When interpreted as an infinite sum
Page 15 and 16:
2. Pattern-Based ⎯ Many problems
Page 17 and 18:
In summary, the basic nature of the
Page 19 and 20:
ecause: j2πfnT+j2πn e T - ⎛ ---
Page 21 and 22:
2.2 Windowing and Windowing Effects
Page 23 and 24:
xf () x(nT) 1 0.9 0.8 0.7 0.6 0.5 0
Page 25 and 26:
Note that many textbooks simply def
Page 27 and 28:
“Since there are two independent
Page 29 and 30: appropriately called the decimation
Page 31 and 32: x(0) x(4) Figure 3-4 Decimation-in-
Page 33 and 34: Binary Index 000 x(0) 001 010 011 1
Page 35 and 36: 3.4 The Decimation-in- Frequency Ra
Page 37 and 38: DSP56001/2 and DSP96002 hardware fe
Page 39 and 40: 4. Bit-reversed addressing mode 5.
Page 41 and 42: 4.3 Complexity of a Radix-2 DIT FFT
Page 43 and 44: The data paths are 24 bits wide, th
Page 45 and 46: The kernel shown in Figure 4-4 exec
Page 47 and 48: ;Alters Program Control Registers ;
Page 49 and 50: PORT A CLK 4 ADDRESS 32 Control 19
Page 51 and 52: ;r0 ➨ A ;r1 ➨ B ;r4 ➨ C ;r5
Page 53 and 54: 5 5 7 ADDRESS Sigma Delta Codec PI/
Page 55 and 56: limits its results to those bits. T
Page 57 and 58: flow in the FFT calculation is to s
Page 59 and 60: of the sine table, 256 points. Howe
Page 61 and 62: normal_order=output_pointer; bitrev
Page 63 and 64: A′ A CW c BW b DW c W b = + + ( +
Page 65 and 66: ;r0->A,r4->B, r1->C, r6->D; ;r1->A
Page 67 and 68: Ar′ = Ar + Br + ( Dr + Cr) Ai′
Page 69 and 70: “Optimization saves . . . 2067 in
Page 71 and 72: plexity to practical complexity ref
Page 73 and 74: 5.1.2 Optimization for Fast
Page 75 and 76: 3. pass. This change results in lon
Page 77 and 78: 5.2 Example of Optimization 5.2.1 F
Page 79: Pass 0 1 2 3 4 5 6 7 8 A B C D W=(1
Page 83 and 84: 6.1 Real-Valued Input FFT Algorithm
Page 85 and 86: The twiddle factors appear to be in
Page 87 and 88: X=A+jB Y=C+jD X’=A+C+j(D+B) - Y
Page 89 and 90: takes four points in and four point
Page 91 and 92: Z( k) = DFT[ z( n) ] = DFT[ x( n) +
Page 93 and 94: F( k) a real sequence with N points
Page 95 and 96: Eight multiplications, five additio
Page 97 and 98: further: 1. Since the input data is
Page 99 and 100: 6.4 The Goertzel Algorithm Previous
Page 101 and 102: The power of magnitude of the DFT c
Page 103 and 104: SSI or HI The double buffering is i
Page 105 and 106: “To implement Eqn. 7-1, a two dim
Page 107 and 108: F( k) where: N - 1 2c( k) ---------
Page 109 and 110: 7.2.2 Two Dimensional DCT A one dim
Page 111 and 112: facturer may offer a higher perform
Page 113 and 114: 8.2.1.1 Complex FFT on Floating-Poi
Page 115 and 116: 8.2.2 FFT on Fixed-Point DSPs As me
Page 117 and 118: “Motorola's family of digital sig
Page 119 and 120: APPENDIX A Fully Optimized Complex
Page 121 and 122: ;**********************************
Page 123 and 124: ;**********************************
Page 125 and 126: movem 2,m5 movem 2,m7 move #data,r0
Page 127 and 128: ; ------------ NORMAL RADIX-2 BUTTE
Page 129 and 130: nop nop jmp * end ; ; Sine-Cosine T
Page 131 and 132:
; Input signal for FFT rfft56.asm a
Page 133 and 134:
move #POINTS/2-1,m0 ;modulo address
Page 135 and 136:
; r0->A,r1->B,r4->A’,r5->B’,r6-
Page 137 and 138:
_inner_pass do n3,_end_grp ;do grou
Page 139 and 140:
APPENDIX B Real-Valued Input FFT B.
Page 141 and 142:
count set 0 dup points/2 dc @cos(@c
Page 143 and 144:
B.2 Real FFT for DSP56001/2 ; ; Thi
Page 145 and 146:
dup points/4 dc @cos(@cvf(count)*fr
Page 147 and 148:
macr y1,y0,a y:(r4),y0 ;a=Wi*H2r-Wr
show all

Fast Fourier Transforms on Motorola's Digital Signal Processors

Create successful ePaper yourself

Delete template?

Save as template?