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James Juno

dblp:211/1634 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
0000-0001-6835-273XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 50% Parallel and multicore computing · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational science and engineering · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
High-performance computing
scientific computing
0.412020
Alias-free, matrix-free, and quadrature-free discontinuous galerkin algorithms for (plasma) kinetic equations · SC 2020
Parallel and multicore computing › parallel programming models
shared-memory parallelization
0.412020
Alias-free, matrix-free, and quadrature-free discontinuous galerkin algorithms for (plasma) kinetic equations · SC 2020
Computational science and engineering › computational physics
plasma physics simulation
0.112020
Alias-free, matrix-free, and quadrature-free discontinuous galerkin algorithms for (plasma) kinetic equations · SC 2020

Methods — techniques the papers use, named apart from their topics

modal basis functions · 0.9discontinuous galerkin · 0.9automatic kernel generation · 0.9JIT compilation · 0.9
YearPublicationVenuePosition
2020 Alias-free, matrix-free, and quadrature-free discontinuous galerkin algorithms for (plasma) kinetic equations
abstract
Understanding fundamental kinetic processes is important for many problems, from plasma physics to gas dynamics. A first-principles approach to these problems requires a statistical description via the Boltzmann equation, coupled to appropriate field equations. In this paper we present a novel version of the discontinuous Galerkin (DG) algorithm to solve such kinetic equations. Unlike Monte-Carlo methods, we use a continuum scheme in which we directly discretize the 6D phase-space using discontinuous basis functions. Our DG scheme eliminates counting noise and aliasing errors that would otherwise contaminate the delicate field-particle interactions. We use modal basis functions with reduced degrees of freedom to improve efficiency while retaining a high formal order of convergence. Our implementation incorporates a number of software innovations: use of JIT compiled top-level language, automatically generated computational kernels and a sophisticated shared-memory MPI implementation to handle velocity space parallelization.
Ammar Hakim, James Juno
SC2