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Maximizing Efficiency in Methane Binding Studies Using Graphene-like Structures

This Density Functional Theory study by Jovian Lazare explores a scaling approach to single and double methane binding with graphene-like structures. The computational findings will aid experimentalists in researching similar systems, with potential applications in chemical sensors and methane storage for energy production. The study focuses on the utilization of NWChem on supercomputers like Bluewaters and XSEDE, which effectively scales with its OpenMP and MPI functionalities in Fortran programming. Scaling calculations on a Benzene-Acetylene model provide a simple example, aiming to maximize processing elements with the least node utilization to enhance efficiency. Despite challenges like memory issues, future scaling work will target larger-scale systems for improved computational outcomes.

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Maximizing Efficiency in Methane Binding Studies Using Graphene-like Structures

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  1. Scaling Approach to Single and Double Methane Binding with Graphene–like Structures: A Density Functional Theory Study By Jovian Lazare

  2. Why study these systems? • Computational results will help experimentalists studying similar systems with applications in chemical sensors and possibly methane storage (source of energy; 90% of methane is produced during formation of coal and capturing after its release due to mining and erosion is important) NWChem will be the standard application of choice for use on Bluewaters and XSEDE resources; it scales well on supercomputers with its utilization of OpenMP and MPI with fortran programming language

  3. Scaling Calculations on Benzene-Acetylene model with C6v Symmetry as a simple example -n=-N*nodes, where –N is processes/node and –n is PE -N*-d≤32, where the less or equal value represents the integer units and –d is the threads per process ***Caught signal Terminated, sending to application n/a : Did not complete due to memory issues

  4. Future Scaling Work on Project and Other Larger Scale Systems Conclusion of approach: Get the max number of processing elements with the least amount of nodes. This should theoretically save computer time/resources

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