> Olof Bjarnason wrote: > [snip] >> A short question after having read through most of this thread, on the >> same subject (time-optimizing CPython): >> >> http://mail.python.org/pipermail/python-list/2007-September/098964.html >> >> We are experiencing multi-core processor kernels more and more these >> days. But they are all still connected to the main memory, right? >> >> To me that means, even though some algorithm can be split up into >> several threads that run on different cores of the processor, that any >> algorithm will be memory-speed limited. And memory access is a quite >> common operation for most algorithms. >> >> Then one could ask oneself: what is the point of multiple cores, if >> memory bandwidth is the bottleneck? Specifically, what makes one >> expect any speed gain from parallelizing a sequential algorithm into >> four threads, say, when the memory shuffling is the same speed in both >> scenarios? (Assuming memory access is much slower than ADDs, JMPs and >> such instructions - a quite safe assumption I presume)
Modern (multi-core) processors have several levels of caches that interact with the other cores in different ways. You should read up on NUMA. http://en.wikipedia.org/wiki/Non-Uniform_Memory_Access Stefan -- http://mail.python.org/mailman/listinfo/python-list
