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Computational Chemistry
There are several ongoing projects on accelerating quantum chemistry codes using CUDA-enabled GPUs, including work on Gaussian and GAMESS. The charts below are representative results, followed by links to software and technical reports on CUDA acceleration of computational chemistry.
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| Direct self-consistent field (SCF) calculations Ufimtsev and Martinez |
Two-Electron integral evaluation Koji Yasuda |
| ISV/Application | Supported Features | Expected Speed up* | Release Status |
| GAMESS-US | Libqc with Rys Quadrature Algorithm, integral evaluation, closed shell Fock matrix construction. | In development | |
| NWChem | Triples part of Reg-CCSD(T), CCSD & EOMCCSD task schedulers | 3-8x projected | In development |
| Q-CHEM | Various features including RI-MP2. | In development | |
| TeraChem | “Full GPU-based solution”. | 44-650x | Released, v1.45 |
| VASP | Davidson iteration scheme | 3x-6.5x | Released |
* Expected Speed Up vs a quad-core x64 CPU based system. Speed-ups as per NVIDIA in house testing or application provider documentation.
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- Learn about GPU acceleration in VMD
- NAMD 2.7 Beta 2 including CUDA Acceleration
- HOOMD: Highly Optimized Object Oriented Molecular Dynamics
- OpenMM library for Accelerating Molecular Dynamics on GPUs
- GROMACS using OpenMM
- AMBER CUDA Port
- LAMMPS GPU Port
- TeraChem: First Quantum Chemistry Code Written Ground-up for CUDA GPUs
- ACE-MD
- MDGPU
- GPUGrid.net
- BigDFT : DFT (Density Functional Theory) Electronic Structure Code -- Paper PDF
- PC GAMESS on CUDA
- Todd Martinez work on Quantum Chemistry on GPUs
- Q-Chem on CUDA
- An implementation of the Smooth Particle-Mesh Ewald (PME) Method on GPU Hardware
- Two-Electron Integral Evaluation on the GPU
- Acceleration of Fragment MO (FMO) Method using CUDA
- NAMD and VMD Publications
- Molecular Dynamics on a GPU Grid
GPU Technology Conference Sessions
- Keynote: High-Throughput Science , Hanspeter Pfister, Harvard University
- GPU Accelerated Molecular Dynamics with AMBER, The Scripps Research Institute and San Diego Supercomputer Center
- GPU Accelerated Visualization and Analysis in VMD, University of Illinois at Champaign-Urbana
- Computational Biophysics and Long Range Electrostatics on GPUs, NVIDIA
- Volunteer Computing for GPUs: Petaflops for Free, UC Berkeley
- Harnessing the GPU for Surgical Training and Preoperative Planning, CSIRO
- GPU Accelerated Solvers for ODEs Describing Cardiac Membrane Equations, UC San Diego
- Reconstructing the Brain: Extracting Neural Circuitry with CUDA and MPI, Harvard University
- Unlocking Biologically-Inspired Computer Vision: a High-Throughput Approach, MIT
- A Large Scale Simulation of Lattice QCD with a GPU Cluster, National Taiwan University
- Overview of NVIDIA CUDA Support in AMBER - Lessons Learned, Capabilities Gained, Ross Walker, University of California San Diego, San Diego Supercomputing Center
- Harnessing GPU Speed to Accelerate LAMMPS Particle Simulation, Paul Crozier, Sandia National Laboratory
- Accelerating Molecular Modeling Applications with GPU Computing, John Stone, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign