Hi, I set up a Jenkins job to run a couple of (simple) benchmarks comparing Cython's current performance under CPython and PyPy. Note that these are C-API intensive benchmarks by design.
https://sage.math.washington.edu:8091/hudson/job/cython-devel-cybenchmarks-pypy/lastSuccessfulBuild/artifact/bench_chart.html Basically, PyPy's cpyext is currently about 100-200x slower than CPython's native C-API for these kinds of benchmarks. That's because it hasn't been optimised in any way, correctness and completeness are still the main goals in its development (and they're not there yet). The one major performance issue in cpyext is currently the creation and deallocation of the PyObject representation for each object, which obviously has a huge impact on everything. I profiled the nbody benchmark and it showed that almost 80% of the runtime is currently spent in creating and discarding PyObject instances. Here's the call graph: http://cython.org/callgrind-pypy-nbody.png The up side of this is that there is likely a lot of low hanging fruit in cpyext (plus some more tweaks in Cython), given that no optimisation at all has been done so far. It shouldn't be too hard to drop the factor substantially. I also think we should add a couple of more C-ish benchmarks to see how much overhead there really is for less C-API intensive code. Stefan _______________________________________________ cython-devel mailing list cython-devel@python.org http://mail.python.org/mailman/listinfo/cython-devel
