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Separate handling of ml inside nrn_acc_manager #719
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olupton
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Dec 17, 2021
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December 20, 2021 09:51
olupton
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Dec 21, 2021
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Dec 23, 2021
Summary of changes: - Support OpenMP target offload when NMODL and GPU support are enabled. (#693, #704, #705, #707, #708, #716, #719) - Use sensible defaults for the --nwarp parameter, improving the performance of the Hines solver with --cell-permute=2 on GPU. (#700, #710, #718) - Use a Boost memory pool, if Boost is available, to reduce the number of independent CUDA unified memory allocations used for Random123 stream objects. This speeds up initialisation of models using Random123, and also makes it feasible to use NSight Compute on models using Random123 and for NSight Systems to profile initialisation. (#702, #703) - Use -cuda when compiling with NVHPC and OpenACC or OpenMP, as recommended on the NVIDIA forums. (#721) - Do not compile for compute capability 6.0 by default, as this is not supported by NVHPC with OpenMP target offload. - Add new GitLab CI tests so we test CoreNEURON + NMODL with both OpenACC and OpenMP. (#698, #717) - Add CUDA runtime header search path explicitly, so we don't rely on it being implicit in our NVHPC localrc. - Cleanup unused code. (#711) Co-authored-by: Pramod Kumbhar <[email protected]> Co-authored-by: Ioannis Magkanaris <[email protected]> Co-authored-by: Christos Kotsalos <[email protected]> Co-authored-by: Nicolas Cornu <[email protected]>
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Nov 2, 2022
Summary of changes: - Support OpenMP target offload when NMODL and GPU support are enabled. (BlueBrain/CoreNeuron#693, BlueBrain/CoreNeuron#704, BlueBrain/CoreNeuron#705, BlueBrain/CoreNeuron#707, BlueBrain/CoreNeuron#708, BlueBrain/CoreNeuron#716, BlueBrain/CoreNeuron#719) - Use sensible defaults for the --nwarp parameter, improving the performance of the Hines solver with --cell-permute=2 on GPU. (BlueBrain/CoreNeuron#700, BlueBrain/CoreNeuron#710, BlueBrain/CoreNeuron#718) - Use a Boost memory pool, if Boost is available, to reduce the number of independent CUDA unified memory allocations used for Random123 stream objects. This speeds up initialisation of models using Random123, and also makes it feasible to use NSight Compute on models using Random123 and for NSight Systems to profile initialisation. (BlueBrain/CoreNeuron#702, BlueBrain/CoreNeuron#703) - Use -cuda when compiling with NVHPC and OpenACC or OpenMP, as recommended on the NVIDIA forums. (BlueBrain/CoreNeuron#721) - Do not compile for compute capability 6.0 by default, as this is not supported by NVHPC with OpenMP target offload. - Add new GitLab CI tests so we test CoreNEURON + NMODL with both OpenACC and OpenMP. (BlueBrain/CoreNeuron#698, BlueBrain/CoreNeuron#717) - Add CUDA runtime header search path explicitly, so we don't rely on it being implicit in our NVHPC localrc. - Cleanup unused code. (BlueBrain/CoreNeuron#711) Co-authored-by: Pramod Kumbhar <[email protected]> Co-authored-by: Ioannis Magkanaris <[email protected]> Co-authored-by: Christos Kotsalos <[email protected]> Co-authored-by: Nicolas Cornu <[email protected]> CoreNEURON Repo SHA: BlueBrain/CoreNeuron@423ae6c
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Mechanism are not use on GPU if they are artificial, so stop sending it.
For clarity, clean handling of ml inside nrn_acc_manager by dividing into functions
CI_BRANCHES:NMODL_BRANCH=hackathon_main,NEURON_BRANCH=master,