PS my test was on double precision, failed to notice that too. -----Original Message----- From: numpy-discussion-admin@lists.sourceforge.net [mailto:numpy-discussion-admin@lists.sourceforge.net]On Behalf Of Joe Van Andel Sent: Tuesday, June 12, 2001 5:20 PM To: numpy-discussion Subject: [Numpy-discussion] performance comparison of C++ vs Numeric (MA) operations. I was curious about the relative performance of C++ vs Numeric Python, for operations on arrays of roughly 400,000 array elements. I built a simple array single precision multiplication function in C++, that performs an element by element multiply, checking whether each element is "valid" or "missing data". Then, for comparision, I wrote a similar multiplication routine, using the Masked Array (MA) package of Numeric Python. I compiled Numeric Python (20.1.0b2) with '-O3', by modifying setup.py to contain lines like OPTIMIZE=['-O3'] ext_modules = . . Extension('multiarray', ['Src/multiarraymodule.c'], extra_compile_args=OPTIMIZE ), --------------------------------------- On an 800 Mhz dual processor Dell Linux box, using gcc 2.95.3, Software Performance ------------------------------------------------ Numeric Python 5.0e6 multiplies/second Numeric Python -03 6.1e6 multiplies/second C++ 10.3e6 multiplies/second C++ -O3 10.3e6 multiplies/second (I tried using "plain" Numeric arrays, rather than Masked arrays, and it didn't seem to make much difference.) Has anyone else benchmarked the relative performance of C/C++ vs Numeric Python? Does anyone know of other optimizations to Numeric Python that could be implemented? I know a more realistic benchmark would include I/O, which might tend to reduce the apparent difference in performance. I've attached the benchmark modules, in case someone would like to examine them. -- Joe VanAndel National Center for Atmospheric Research http://www.atd.ucar.edu/~vanandel/ Internet: vanandel@ucar.edu