V
Vinh Dang
Researcher at Sandia National Laboratories
Publications - 40
Citations - 506
Vinh Dang is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Fast multipole method & Speedup. The author has an hindex of 11, co-authored 38 publications receiving 332 citations. Previous affiliations of Vinh Dang include The Catholic University of America & University of Virginia.
Papers
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Journal ArticleDOI
Kokkos 3: Programming Model Extensions for the Exascale Era
Christian Robert Trott,Damien Lebrun-Grandie,Daniel Arndt,Jan Ciesko,Vinh Dang,Nathan Ellingwood,Rahulkumar Gayatri,Evan Harvey,Daisy S. Hollman,Dan Ibanez,Nevin Liber,Jonathan Madsen,Jeff Miles,David Poliakoff,Amy Jo Powell,Sivasankaran Rajamanickam,Mikael Simberg,Dan Sunderland,Bruno Turcksin,Jeremiah J. Wilke +19 more
TL;DR: The novel abstractions that have been added to Kokkos version 3 such as hierarchical parallelism, containers, task graphs, and arbitrary-sized atomic operations to prepare for exascale era architectures are described.
Proceedings ArticleDOI
ANMLzoo: a benchmark suite for exploring bottlenecks in automata processing engines and architectures
Jack Wadden,Vinh Dang,Nathan Brunelle,Tommy Tracy,Deyuan Guo,Elaheh Sadredini,Ke Wang,Chunkun Bo,Gabriel Robins,Mircea R. Stan,Kevin Skadron +10 more
TL;DR: ANMLZoo is presented, a benchmark repository for automata-based applications as well as automata engines for both von-Neumann and reconfigurable dataflow architectures, and insights from five experiments are presented showing how it can be used to expose bottlenecks in both Automata-processing software engines and hardware architectures.
Journal ArticleDOI
Analysis of Moving Human Micro-Doppler Signature in Forest Environments
TL;DR: This paper attempts to develop an accurate model accounting for the key contributions to the Doppler signature for the human motion in a forest environment and combines analytical techniques with full wave numerical methods to achieve a realistic representation of the signature from the scene.
Journal ArticleDOI
Parallelizing Fast Multipole Method for Large-Scale Electromagnetic Problems Using GPU Clusters
TL;DR: This letter investigates the solution of large-scale electromagnetic problems by using the single-level Fast Multipole Method using a parallel implementation of FMM on a 13-node graphics processing unit (GPU) cluster that populates Nvidia Tesla M2090 GPUs.
Proceedings ArticleDOI
REAPR: Reconfigurable engine for automata processing
TL;DR: REAPR: Reconfigurable Engine for Automata PRocessing is presented, a flexible framework that synthesizes RTL for automata processing applications as well as I/O to handle data transfer to and from the kernel.