CUDA-accelerated ion placement for STMV virus structure

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

CUDA 1.1

CUDA-accelerated test versions of VMD, NAMD, cionize, and example data

CUDA 1.0 Intel C/C++ 9.0 CPU builds (for comparison, do not use for production runs) GNU GCC CPU builds (for comparison)

Related software

  • VMD -- Molecular visualization and analysis
  • NAMD -- Molecular dynamics simulation
  • NVIDIA -- Makers of the Tesla, Quadro, and GeForce devices used by GPU-accelerated apps listed above

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