arXiv subjects

Aaron Scheinberg

Publications and source records attributed to Aaron Scheinberg.

3 recordsLinked to original sources

arXiv2026

A toroidally spectral field solver in the X-point Gyrokinetic Code for accurate simulation of reduced magneto-hydrodynamic modes

A new field solver has been implemented in the global electromagnetic total-$f$ gyrokinetic particle-in-cell code XGC to extend the code's capability to large-scale reduced MHD-type instabilities in tokamak plasma. While XGC's regular field solver is accurate at typical microturbulence scales of the order of the ion Larmor radius in tokamaks with arbitrary aspect ratio, a more accurate field solver is required for large-scale (i.e., low toroidal mode number) MHD-type modes such as internal kink, tearing and peeling modes. The higher accuracy of the new field solver is achieved by dropping the (large aspect ratio) assumption that the poloidal magnetic field is much smaller than the toroidal magnetic field, while its numerical complexity is controlled by using a spectral discretization in the toroidal direction. To cover the entire spectrum from large-scale MHD-type modes to small-scale microturbulence, the regular and the new field solver can be run alongside each other. This work details the derivation of the new field solver, analyzes the differences between the XGC's regular and new field solvers, and verifies the new field solver against analytic predictions and the gyrokinetic code ORB5 and the MHD code NIMROD.

physics.plasm-ph↗

arXiv2021

Enabling particle applications for exascale computing platforms

The Exascale Computing Project (ECP) is invested in co-design to assure that key applications are ready for exascale computing. Within ECP, the Co-design Center for Particle Applications (CoPA) is addressing challenges faced by particle-based applications across four sub-motifs: short-range particle-particle interactions (e.g., those which often dominate molecular dynamics (MD) and smoothed particle hydrodynamics (SPH) methods), long-range particle-particle interactions (e.g., electrostatic MD and gravitational N-body), particle-in-cell (PIC) methods, and linear-scaling electronic structure and quantum molecular dynamics (QMD) algorithms. Our crosscutting co-designed technologies fall into two categories: proxy applications (or apps) and libraries. Proxy apps are vehicles used to evaluate the viability of incorporating various types of algorithms, data structures, and architecture-specific optimizations and the associated trade-offs; examples include ExaMiniMD, CabanaMD, CabanaPIC, and ExaSP2. Libraries are modular instantiations that multiple applications can utilize or be built upon; CoPA has developed the Cabana particle library, PROGRESS/BML libraries for QMD, and the SWFFT and fftMPI parallel FFT libraries. Success is measured by identifiable lessons learned that are translated either directly into parent production application codes or into libraries, with demonstrated performance and/or productivity improvement. The libraries and their use in CoPA's ECP application partner codes are also addressed.

cs.DC↗

arXiv2020

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.

q-bio.BM↗