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[[Category:Software]][[Category:BiomolecularSimulation]] | [[Category:Software]][[Category:BiomolecularSimulation]] | ||
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=Introduction= | =Introduction= | ||
OpenMM<ref name="OpenMM_home">OpenMM Homepage: https://openmm.org/</ref> is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations or as a library you call from your own code. It provides a combination of extreme flexibility (through custom forces and integrators), openness, and high performance (especially on recent GPUs) that makes it unique among MD simulation packages. | OpenMM<ref name="OpenMM_home">OpenMM Homepage: https://openmm.org/</ref> is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations or as a library you call from your own code. It provides a combination of extreme flexibility (through custom forces and integrators), openness, and high performance (especially on recent GPUs) that makes it unique among MD simulation packages. | ||
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OpenMM on the CUDA platform requires only one CPU per GPU because it does not use CPUs for calculations. While OpenMM can use several GPUs in one node, the most efficient way to run simulations is to use a single GPU. As you can see from [https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Narval&gpu_model=&cpu_model=&arch=&dataset=6n4o Narval benchmarks] and [https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Cedar&gpu_model=V100-SXM2&cpu_model=&arch=&dataset=6n4o Cedar benchmarks], on nodes with NvLink (where GPUs are connected directly) OpenMM runs slightly faster on multiple GPUs. Without NvLink there is a very little speedup of simulations on P100 GPUs ([https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Cedar&gpu_model=P100-PCIE&cpu_model=&arch=&dataset=6n4o Cedar benchmarks]). | OpenMM on the CUDA platform requires only one CPU per GPU because it does not use CPUs for calculations. While OpenMM can use several GPUs in one node, the most efficient way to run simulations is to use a single GPU. As you can see from [https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Narval&gpu_model=&cpu_model=&arch=&dataset=6n4o Narval benchmarks] and [https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Cedar&gpu_model=V100-SXM2&cpu_model=&arch=&dataset=6n4o Cedar benchmarks], on nodes with NvLink (where GPUs are connected directly) OpenMM runs slightly faster on multiple GPUs. Without NvLink there is a very little speedup of simulations on P100 GPUs ([https://mdbench.ace-net.ca/mdbench/bform/?software_contains=OPENMM.cuda&software_id=&module_contains=&module_version=&site_contains=Cedar&gpu_model=P100-PCIE&cpu_model=&arch=&dataset=6n4o Cedar benchmarks]). | ||
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