2009/10/23 Olof Bjarnason <olof.bjarna...@gmail.com> > > > 2009/10/22 MRAB <pyt...@mrabarnett.plus.com> > > 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) >>> >>> [ If every core had it's own primary memory, the situation would be >>> different. It would be more like the situation in a distributed/internet >>> based system, spread over several computers. One could view each core as a >>> separate computer actually ] >>> >>> Don't forget about the on-chip cache! :-) >> > > Sorry for continuing slightly OT: > > Yes, that makes matters even more interesting. > > Caches for single-cpu-boards speed up memory access quite dramatically. Are > caches for multi-core boards shared among the cores? Or do each core have a > separate cache? I can only imagine how complicated the read/write logic must > be of these tiny electronic devices, in any case. > > Of course caches makes the memory access-operations must faster, but I'm > guessing register instructions are still orders of magnitude faster than > (cached) memory access. (or else registers would not really be needed - you > could just view the whole primary memory as an array of registers!) > > So I think my first question is still interesting: What is the point of > multiple cores, if memory is the bottleneck? > (it helps to think of algorithms such as line-drawing or ray-tracing, which > is easy to parallellize, yet I believe are still faster using a single core > instead of multiple because of the read/write-to-memory-bottleneck. It does > help to bring more workers to the mine if >
um typo "It does NOT help to .." only one is allowed access at a time, or more likely, several are allowed > yet it gets so crowded that queues/waiting is inevitable) > > -- > >> http://mail.python.org/mailman/listinfo/python-list >> > > > > -- > twitter.com/olofb > olofb.wordpress.com > olofb.wordpress.com/tag/english > > -- twitter.com/olofb olofb.wordpress.com olofb.wordpress.com/tag/english
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