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Daniel Reynolds

Publications and source records attributed to Daniel Reynolds.

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Optimized Parallelization of Boundary Integral Poisson-Boltzmann Solvers

The Poisson-Boltzmann (PB) model governs the electrostatics of solvated biomolecules, i.e., potential, field, energy, and force. These quantities can provide useful information about protein properties, functions, and dynamics. By considering the advantages of current algorithms and computer hardware, we focus on the parallelization of the treecode-accelerated boundary integral (TABI) PB solver using the Message Passing Interface (MPI) on CPUs and the direct-sum boundary integral (DSBI) PB solver using KOKKOS on GPUs. We provide optimization guidance for users when the DSBI solver on GPU or the TABI solver with MPI on CPU should be used depending on the size of the problem. Specifically, when the number of unknowns is smaller than a predetermined threshold, the GPU-accelerated DSBI solver converges rapidly thus has the potential to perform PB model-based molecular dynamics or Monte Carlo simulation. As practical appliations, our parallelized boundary integral PB solvers are used to solve electrostatics on selected proteins that play significant roles in the spread, treatment, and prevention of COVID-19 virus diseases. For each selected protein, the simulation produces the electrostatic solvation energy as a global measurement and electrostatic surface potential for local details.

q-bio.BM

Simulating Cosmological Evolution with Enzo

In this paper we describe our massively parallel version of Enzo, a multiphysics, parallel, AMR application for simulating cosmological structure formation developed at UCSD and Columbia. We describe its physics, numerical algorithms, implementation, and performance on current terascale platforms. We also discuss our future plans and some of the challenges we face as we move to the petascale.

astro-ph