This appendix presents the displays from the IPP benchmarks.
conv -- IPP Convolution
-1: Perform convolution on float vector.
Default Parameters:
-loop_start 5000 // Suggest number of loops for calibration.
-start 4 // Starting problem size is 2^4 or 16.
-param 16 // Size of coefficient kernel.
ipp/fft -- IPP Fft (fast fourier transform) benchmark Single precision -1 -- inter-op: interleaved, out-of-place CC fwd fft -2 -- inter-ip: interleaved, in-place CC fwd fft (vrsn >= 5) -11 -- split-op: interleaved, out-of-place CC fwd fft -12 -- split-ip: interleaved, out-of-place CC fwd fft (vrsn >= 5)
mcopy -- float matrix copy using IPP
-1: rows -> rows select algorithm
-2: rows -> cols select algorithm
-3: cols -> rows select algorithm
-4: cols -> cols select algorithm
-11: rows -> rows copy algorithm
-12: rows -> cols copy algorithm
-13: cols -> rows copy algorithm
-14: cols -> cols copy algorithm
-22: rows -> cols transpose algorithm
-23: cols -> rows transpose algorithm
Default parameters:
-stop 12 // Largest problem size is 2^12 or 4096
vmul -- IPP vector multiply
-1: float VSIPL++ allocation
-2: complex<float> VSIPL++ allocation
-12: complex<float> IPP allocation (ippsMul_32fc) (in place)
-22: complex<float> IPP allocation (ippsMul_32fc_I) (in place)
-101: float IPP allocation (ippsMul_32f)
-102: complex<float> IPP allocation (ippsMul_32fc)