CDS&E: Massively Parallel Quantum Dynamics: Computing many accurate quantum states for real molecular applications

Texas Tech University, Lubbock TX

Investigators

Abstract

Lionel "Bill" Poirier of Texas Tech University is supported by a CDS&E (Computational and Data-Enabled Science and Engineering) award from the Chemical Theory, Models, and Computational Methods program in the Chemistry Division, and the Office of Advanced Cyberinfrastructure. He and his research group are developing methods to scale exact quantum dynamical molecular simulations across the next generation of massively parallel supercomputers. Molecular simulations promise to enable computers to replace expensive and time-consuming laboratory experiments. Thus, these simulations used routinely in many areas (energy, drug design, nanomaterials, etc). However, most simulations treat the atomic nuclei that make up the molecules as classical particles and ignore quantum dynamical effects of nuclear motion. Quantum effects can be important, and excluding them may lead to unreliable results. Including them, on the other hand, presents daunting numerical hurdles and difficult mathematics. To meet this challenge, Poirier and coworkers are developing the world's first massively parallel exact quantum dynamics code, SwitchIT, which is also designed to be easy to use (even for "non-experts") and easy to access (anyone may download the package for free). SwitchIT may thus dramatically improve the accuracy, reliability and true predictive power of molecular simulations, in the many areas where these are employed. Poirier and coworkers plan to release the SwitchIT as open source and build a user community around the language by ensuring that interested researchers can contribute to the SwitchIT codebase. This permits a wider growth of the project. This aspect is of special interest to the software cluster in the Office of Advanced Cyberinfrastructure, which has provided co-funding for this award. Recent developments in supercomputing technology promise great leaps forward in scientific computation, with the potential to significantly advance a broad range of scientific fields. Increasingly, cutting edge science has come to rely on large-scale interdisciplinary collaboration, shared infrastructure, and massively parallel high performance computers (HPC). At the same time, within the chemical dynamics field, there has been a shift towards larger and more diverse systems, including nanomaterials and biological molecules. Finally, the need to incorporate quantum dynamical (QD) effects in numerical simulations in order to obtain accurate results is becoming increasingly recognized, even for large systems (e.g., electron transport in photosynthesis). The convergence of these trends is inevitable. Yet, due to steep learning curves and/or lack of access, relatively few chemists currently benefit from either HPC or exact QD. Poirier's research seeks to leverage the power of HPC, to enable exact QD calculations for larger and more challenging molecular applications than heretofore realized. Such calculations constitute a pioneering advance over previous exact QD efforts, with massive parallelization a vital CDS&E feature of the approach taken. The implementation also fuses together two linear algebra innovations that: (1) enable efficient parallelization of sparse iterative linear solvers and eigensolvers across 1000 - 10000 cores; (2) use wavelets to reduce the basis size to a manageable level, even for exact QD systems with as many as 12 atoms. "Expert" QD practitioners can tap into SwitchIT at a low level to introduce HPC capability into their own QD codes, whereas SwitchIT provides non-experts with an easy-to-use front end and extensive documentation. In addition, Poirier and group members regularly provide guidance and training, as well as access to the Texas Tech Chemistry Computation Cluster. Poirier's group members themselves receive intensive interdisciplinary training in computational science and next-generation HPC highly relevant skills, e.g., for American competitiveness. In short, this NSF award extends the complexity of systems that can be studied with exact QD, while simultaneously cyber-enabling a much broader cross section of the community to perform such calculations.