CUDA-accelerated Molecular Modeling Applications
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Modern graphics processing units (GPUs) contain hundreds of arithmetic units and can be harnessed to provide tremendous acceleration for many numerically intensive scientific applications. The key to effective utilization of GPUs for scientific computing is the design and implementation of efficient data-parallel algorithms that can scale to hundreds of tightly coupled processing units. The use of several GPUs at a coarser level of parallelism can bring even more computational power to bear on highly parallelizable computational problems. NVIDIA CUDA enables GPUs programming in a variation of the C programming language. A working CUDA installation is required to run the software provided on this page.
Research Publications and Additional Information
CUDA-accelerated test versions of VMD and example data
- All of the new test versions of VMD now include CUDA support by default. These test versions of VMD are available by following the instructions on this page.