Molecular modeling on GPUs

Molecular modeling on GPU is the technique of using a <a href="/facts/Graphics_processing_unit/PTK1RQVp">graphics processing unit</a> (GPU) for <a href="/facts/Molecular_dynamics/yR3DNt6U">molecular simulations</a>.
In 2007, <a href="/facts/Nvidia/8QfCgqbu">Nvidia</a> introduced video cards that could be used not only to show graphics but also for scientific calculations. These cards include many arithmetic units (as of 2016<a href="https://en.wikipedia.org/w/index.php?title=Molecular_modeling_on_GPUs&action=edit">[update]</a>, up to 3,584 in Tesla P100) working in parallel. Long before this event, the computational power of video cards was purely used to accelerate graphics calculations. The new features of these cards made it possible to develop parallel programs in a high-level <a href="/facts/Application_programming_interface/GMlN4vUr">application programming interface</a> (API) named <a href="/facts/CUDA/fvPpolot">CUDA</a>. This technology substantially simplified programming by enabling programs to be written in <a href="/facts/C_(programming_language)/Ky2No763">C</a>/<a href="/facts/C%2B%2B/Et0F2qn9">C++</a>. More recently, <a href="/facts/OpenCL/ns8y6np7">OpenCL</a> allows <a href="/facts/Cross-platform/16zqdvNR">cross-platform</a> GPU acceleration.
<a href="/facts/Quantum_chemistry/H9AXV0lx">Quantum chemistry</a> calculations and <a href="/facts/Molecular_mechanics/6wPpARWP">molecular mechanics</a> simulations (<a href="/facts/Molecular_modeling/bc80hbtm">molecular modeling</a> in terms of <a href="/facts/Classical_mechanics/ykG8upsN">classical mechanics</a>) are among beneficial applications of this technology. The video cards can accelerate the calculations tens of times, so a PC with such a card has the power similar to that of a cluster of workstations based on common processors.

Molecular modeling on GPUs open-in-new

Molecular modeling on GPUs