On Fri, 2012-01-06 at 16:09 +0100, Paulo Pinto wrote: > From what I see in HPC conferences papers and webcasts, I think it might be > already too late for D > in those scenarios.
Indeed, for core HPC that is true: if you aren't using Fortran, C, C++, and Python you are not in the game. The point is that HPC is really about using computers that cost a significant proportion of the USA national debt. My thinking is that with Intel especially, looking to use the Moore's Law transistor count mountain to put heterogeneous many core systems on chip, i.e. arrays of CPUs connected to GPGPUs on chip, the programming languages used by the majority of programmers not just those playing with multi-billion dollar kit, will have to be able to deal with heterogeneous models of computation. The current model of separate compilation and loading of CPU code and GPGPU kernel is a hack to get things working in a world where tool chains are still about building 1970s single threaded code. This represents an opportunity for non C and C++ languages. Python is beginning to take a stab at trying to deal with all this. D would be another good candidate. Java cannot be in this game without some serious updating of the JVM semantics -- an issue we debated a bit on this list a short time ago so non need to rehearse all the points. It just strikes me as an opportunity to get D front and centre by having it provide a better development experience for these heterogeneous systems that are coming. Sadly Santa failed to bring me a GPGPU card for Christmas so as to do experiments using C++, Python, OpenCL (and probably CUDA, though OpenCL is the industry standard now). I will though be buying one for myself in the next couple of weeks. > "Russel Winder" wrote in message > news:[email protected]... > On Fri, 2012-01-06 at 16:35 +0200, Manu wrote: > [...] > > Currently GPGPU is dominated by C and C++ using CUDA (for NVIDIA > addicts) or OpenCL (for Apple addicts and others). It would be good if > D could just take over this market by being able to manage GPU kernels > easily. The risk is that PyCUDA and PyOpenCL beat D to market > leadership. > -- Russel. ============================================================================= Dr Russel Winder t: +44 20 7585 2200 voip: sip:[email protected] 41 Buckmaster Road m: +44 7770 465 077 xmpp: [email protected] London SW11 1EN, UK w: www.russel.org.uk skype: russel_winder
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