Randy Cygan

BES Requirements Worksheet

1.1. Project Information - The Nature of the Mineral-Water Interface: A Molecular Simulation and Spectroscopic Investigation

2. Project Summary & Scientific Objectives for the Next 5 Years

Please give a brief description of your project - highlighting its computational aspect - and outline its scientific objectives for the next 3-5 years. Please list one or two specific goals you hope to reach in 5 years.

Classical simulation using approximate energy expressions remain the computational method of choice for atomistic simulations of complex systems such as the clay-water interface. We are well equipped for these simulations at Sandia, with a dedicated computer cluster with 100 processors, and access to institutional computing clusters. We use the LAMMPS code for molecular dynamics simulations, as well as the Forcite module of Materials Studio software for efficient parameter development. However, we will continue to use quantum methods both as a tool in force field development and as a means to study reactivity at clay surfaces. We employ density functional theory (DFT) methods using the freely available VASP code and the commercially available DMol3 module of Materials Studio. Using ab initio MD, we can directly compare dynamical properties from quantum and classical MD simulations. 
 
Specific technical goals include the development of an accurate classical force field to describe the edge structure of clay minerals, and the development of large-scale models for ion adsorption onto basal and edge structures of muscovite with validation by spectroscopy.

3. Current HPC Usage and Methods

3a. Please list your current primary codes and their main mathematical methods and/or algorithms. Include quantities that characterize the size or scale of your simulations or numerical experiments; e.g., size of grid, number of particles, basis sets, etc. Also indicate how parallelism is expressed (e.g., MPI, OpenMP, MPI/OpenMP hybrid)

Classical molecular dynamics using LAMMPS and Forcite codes 
up to 250K atom systems 
up to 50M time steps 
 
Quantum Density Funcitonal Theory using VASP and DMol codes 
up to 400 atom systems 
up to 60K time steps for AIMD 
 
Quantum Hartree-Fock using Gaussian code 
up to 200 atom clusters 
 
All MPI based processing 

3b. Please list known limitations, obstacles, and/or bottlenecks that currently limit your ability to perform simulations you would like to run. Is there anything specific to NERSC?

Practical limitations include institutional queue priorities and processor/time limits 
Limit on number of atoms and ability to include critical chemistry 
Visualization software for large atom systems 
 
Nothing NERSC-specific 

3c. Please fill out the following table to the best of your ability. This table provides baseline data to help extrapolate to requirements for future years. If you are uncertain about any item, please use your best estimate to use as a starting point for discussions.

Please list any required or important software, services, or infrastructure (beyond supercomputing and standard storage infrastructure) provided by HPC centers or system vendors.

None 

4. HPC Requirements in 5 Years

4a. We are formulating the requirements for NERSC that will enable you to meet the goals you outlined in Section 2 above. Please fill out the following table to the best of your ability. If you are uncertain about any item, please use your best estimate to use as a starting point for discussions at the workshop.

4b. What changes to codes, mathematical methods and/or algorithms do you anticipate will be needed to achieve this project's scientific objectives over the next 5 years.

Vertorization using GPUs

4c. Please list any known or anticipated architectural requirements (e.g., 2 GB memory/core, interconnect latency < 3 #s).

4d. Please list any new software, services, or infrastructure support you will need over the next 5 years.

GPU-based algorithms 

4e. It is believed that the dominant HPC architecture in the next 3-5 years will incorporate processing elements composed of 10s-1,000s of individual cores, perhaps GPUs or other accelerators. It is unlikely that a programming model based solely on MPI will be effective, or even supported, on these machines. Do you have a strategy for computing in such an environment? If so, please briefly describe it.

No 

New Science With New Resources

To help us get a better understanding of the quantitative requirements we've asked for above, please tell us: What significant scientific progress could you achieve over the next 5 years with access to 50X the HPC resources you currently have access to at NERSC? What would be the benefits to your research field if you were given access to these kinds of resources?

Please explain what aspects of "expanded HPC resources" are important for your project (e.g., more CPU hours, more memory, more storage, more throughput for small jobs, ability to handle very large jobs).

Increased CPU hours with associated increase in memory 
 
Will lead to improved uncertainty quantification with larger number of realizations; important for performance assessment projects 
 
Will allow improved fidelity in capturing full chemistry associated with systems involving large molecules and complex substrates 
 
Longer simulation times allow opportunity to capture critical chemistry and better validate models with spectrosocpy and experiment