9/3/2023 0 Comments Simply fortran cuda supportI would like to come back to OpenCurrent but for the moment plan 1 will be to implement CUDA as is. Will email sales.Įelson - again thanks, OpenCurrent looks ideal however i need to catchup on the maths of the solver using at the moment. Mkcolg - thanks for the heads up, Ive been looking through the PGI website (the demo videos were very useful) and i think accelerator is likely my best option - cost dependent. I will take your advice on staying with Fortran, thanks Im going to get a mid range nVidia card for the moment and if successful will upgrade when Fermi is released. Ive been reading around and am thinking:ĬGORAC - yes, double precision is a must. I am new to CUDA and would appreciate any advice. Do I need a more specialist card?ĭo you see any ‘not good plans’ in above? The program runs in double precission (required). For the purposes of CUDA would C++ be usable? Im willing to learn C, but would rather C++. When complete will make the code open source I want to develop and initially test on my ‘good last year’ gaming machine and if initial results look promising upgrade to a more intensive system. I am certain have got the options correct but suspect CPU parallelisation (at least letting the compiler decide where to parallelize) is not the answer. I have tried (automated) OpenMP implementation with the intel copmpiler on the Fortran code and have had limited success. I saw Portland Group have released CUDA Fortran which sounds like would skip the onerous step 1 however this is (£?)800 and beyond budget (unless speedup is extreme which I dont know yet). My plan is to convert the FORTRAN to C++, check all works through visual studio express then move to CUDAĪnd test different methods for speedup. Advice on below would be much appreciated. The code is a finite differnce model and I suspect very parallelizable. Through the use of the lattice Boltzmann method, a series of computational models were created to simulate air flow in woodwind instruments.Im new and planning how to convert a LARGE serial Fortran program to run on GPU. Start- ing as a two-dimensional code in Matlab running on the CPU, the model went through a series of iterations before becoming a three-dimension code in Fortran that was accelerated through the use of GPU parallel computing. The accuracy and stability of the model are shown by comparison to various published benchmark tests. Thus far, the air flow in organ pipes for a two dimensional model was simulated showing oscillating flow by the labium as expected. This thesis offers the mathematical and computational background as well as a description of the implementation of the basic LBM for simulat- ing flow in musical instruments. The method described here is meant as a first step to a code that is highly flexible and can be used to study many as- pects of acoustics in musical instruments. Future applicability of the model includes observing flow at the exit of both square and round organ pipes in addition to modeling the reed-mouthpiece system of the clarinet. The occurrence of turbulent flows is quite common in nature and several industrial applications. The accurate simulation of these complex flows is still a great challenge in science. Large Eddy Simulation (LES) is an efficient technique based on the elimination of all scales of a flow smaller than a characteristic length ∆, considering that the flow pattern in small scales is homogeneous and isotropic. Therefore, modeling of turbulence in such scales is universal and independent of the flow type.
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