Hi list, I have observed slowdown if Numpy and Python are installed manually (i.e. not from packaging system). The slowdown can be significant when problem size is large. I wish someone in this mailing list can give me some hints on this issue. I also post performance results and my source code here. My platform is a 12-core dual-socket SMP machine running Ubuntu (Linux kernel 3.2.0). On this platform, I have two sets of installations. One is pre-installed Python 2.7.3 and Numpy 1.6.1 installed with 'apt-get'. The other is Python 2.7.3 and Numpy 1.6.1 both compiled freshly from official tarball release by myself. In order to compare performance, I wrote a piece of code that simply performs matrix-matrix multiplication using one of Numpy's functions. The source code is listed as follows: *if __name__ == "__main__": import numpy, random, time import sys size = int(sys.argv[1]) # For simplicity, we only test square matrix matrix_a = numpy.matrix(numpy.random.randn(size,size)) matrix_b = numpy.matrix(numpy.random.randn(size,size)) start_time = time.time() result = numpy.dot(matrix_a, matrix_b) print '%0.3f ms' % ((time.time() - start_time)*1000.0)* I ran this code with both pre-installed Python and compiled Python. Here is performance numbers I got: Problem size Pre-installed Python Compiled Python/Numpy Slowdown 256x256 14.165 ms 44.538 ms ~3X 512x512 109.330 ms 347.143 ms ~3X 1024x1024 867.936 ms 8975.016 ms ~10X 2048x2048 7755.084 ms 84713.997 ms ~10X Here are commands I used to compile Python and Numpy: a) ~/python2.7.3$ ./configure --prefix=MY_LOCAL_DIR b) ~/python2.7.3$ make c) ~/python2.7.3$ make install e) ~/numpy-1.6.1$ MY_LOCAL_DIR/bin/python setup.py build f) ~/numpy-1.6.1$ MY_LOCAL_DIR/bin/python setup.py install Any ideas? Thanks in advance. Bin Huang