CDSP+k2

AST's CDSP-k2 Benchmarks for some Common DSP Algorithms

The following table presents a performance estimation for some common DSP algorithms.
The estimation is based on an architecture that features one single-cycle MAC unit, a Butterfly unit, and supports the post-increment and bit-reverse indexing facilities.

Operation	Description	Conditions	Parameters	Cycle-Count
FIR	Finite Impulse Response Filter with Constant or Variable Coefficients	Arbitrary number of Coefficients and Samples	N=number of coefficients M=number of samples	M*(N+p)+q
IIR	Direct Form II IIR Filter, Constant or Variable Coefficients	Cascaded biquad sections, Samples multiple of 8	N=number of samples M=number of cells	M(10N+p)+q
LMS FIR Coefficients Update	Update the FIR coefficients using the Least Mean Square Algorithm	Even number of coefficients	N=Number of coefficients	2*N+p
Autocorrelation	Autocorrelation	Arbitrary input and output vector size	N=number of input samples M=number of output samples	M*(N+p)+q
Energy	Square each element in a vector and sum all the squared values	Arbitrary vector size	N=vectors size	N+p
FFT	Radix 2 Fast Fourier Transform	Number of samples is a power of 2	N=number of samples	Log2(N)(4N/2+p)+q
Dot Product	Dot product of two equal-size vectors	Arbitrary vector size	N=vector size	N+p
Weighted Vector Sum	Add two vectors elements having one of them multiplied by a constant	Even number of elements in the vectors	N=vectors size	2*N+p
Max/Min	Find the minimum/maximum value in a vector and retain its position	Arbitrary vector size	N=vectors size	N+p
Search/Skip	Search until/while a value is found in a vector and retain the (last) position where it was found	Arbitrary vector size	N=vectors size	N+p
Move	Move a vector from one position to another in memory	Arbitrary vector size	N=vectors size	N+p

Note 1: "p" and "q" count for the overhead loop-initialization instructions. Performance seriously degrades when "N" is relatively small (<32) as compared with "p".