This collaborative project between the San Diego Supercomputer Center at the University of California San Diego, the Quantum Theory Project at the University of Florida and industrial partners NVIDIA, Intel and Amazon is focused on developing innovative, comprehensive open source software element libraries for accelerating condensed phase Molecular Dynamics (MD) simulations of biomolecules using next generation accelerator hardware including Intel's MIC system and Graphics Processing Units (GPU). It will extend support to include all major MD techniques and develop open source accelerated analysis libraries. A priority is enhanced sampling techniques including Thermodynamic Integration, constant pH algorithms, Multi-Dimensional Hamiltonian Replica Exchange and Metadynamics. These elements will then be combined, in collaboration with Amazon to support MD as-a-service through easily accessible web front ends to cloud services, including Amazon's EC2 GPU hardware. Transitioning large scale MD workflows from requiring access to large supercomputer hardware to being accessible to all on desktop and cloud resources provides the critical software infrastructure to support transformative research in the fields of chemistry, life science, materials science, environmental and renewable energy.
The software elements created through this project have an extremely broad impact. The integration of comprehensive support for next generation hardware acceleration into the AMBER software alone benefits a very large user base. With over 10,000 downloads of the latest AMBER Tools package from unique IPs and >800 sites using the AMBER MD engines testify to the scope of the community of researchers this work impacts. The development of simple web based front ends for use of elastically scalable cloud resources makes simulations routine for all researchers. Meanwhile education and outreach efforts train the next generation of scientists not just in how to use the MD acceleration libraries and advanced MD simulation techniques developed here but also gets them thinking about how their approach can be transformed given that performance that was previously restricted to large scale supercomputers is now available on individual desktops.
