multicore

I have a laptop running Ubuntu on Intel(R) Core(TM) i5-2410M CPU @ 2.30GHz . According to Intel website for the above processor (located here ), this processor has two cores and can run 4 threads at a time in parallel (because although it has 2 physical cores it has 4 logical cores). When I start matlabpool it starts with local configuration and says it has connected to 2 labs. I suppose this means that it can run 2 threads in parallel. Does it not know that the CPU can actually run 4 threads in parallel? In my experience, the local configuration of matlabpool uses, by default, the number of

I'm working on a bare-bones system in which I need to determine sometime after boot how many cores and threads are enabled, so that I can send them SIPI events. I also want each thread to know which thread it is. For instance, in a single-core configuration with HT enabled, we have (for instance, Intel Atom): thread 0 --> core 0 thread 0 thread 1 --> core 0 thread 1 While in a dual-core configuration with no HT we have (for instance, Core 2 Duo): thread 0 --> core 0 thread 0 thread 1 --> core 1 thread 0 What's the best way to determine this? Edit: I found how each thread can find which thread

This is undeniable: multicore computers are here to stay. So is this: efficient multicore programming is pretty difficult. It's not just a case of understanding pthreads. This is arguable: the 'developer on the street' need concern him/herself with these developments. To what extent are you concerned about having to expand your skillset for multicore? Is the software you are writing a candidate for parallelisation, and if so are you doing anything to educate yourself (if you didn't already know the techniques)? Or do you believe that the operating system will take care of most of it, the

The attached simple Java code should load all available cpu core when starting it with the right parameters. So for instance, you start it with java VMTest 8 int 0 and it will start 8 threads that do nothing else than looping and adding 2 to an integer. Something that runs in registers and not even allocates new memory. The problem we are facing now is, that we do not get a 24 core machine loaded (AMD 2 sockets with 12 cores each), when running this simple program (with 24 threads of course). Similar things happen with 2 programs each 12 threads or smaller machines. So our suspicion is that

What's the state of the art with regards to getting numpy to use mutliple cores (on Intel hardware) for things like inner and outer vector products, vector-matrix multiplications etc? I am happy to rebuild numpy if necessary, but at this point I am looking at ways to speed things up without changing my code. For reference, my show_config() is as follows, and I've never observed numpy to use more than one core: atlas_threads_info: libraries = ['lapack', 'ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/usr/local/atlas-3.9.16/lib'] language = f77 include_dirs = ['/usr/local/atlas-3.9.16/include