15 citations · 39 across the 14 of their papers we have counts for
15 papers
High-Performance Resilient Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations at Scale
Jeremy J. Williams, Stefan Costea, David Tskhakaya +13
The increasing demand for high-performance computing in plasma physics has driven scalable and resilient simulation methods capable of efficiently exploiting modern multi-GPU archi…
Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
Jeremy J. Williams, Jordy Trilaksono, Stefan Costea +13
Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchr…
Integrating High Performance In-Memory Data Streaming and In-Situ Visualization in Hybrid MPI+OpenMP PIC MC Simulations Towards Exascale
Jeremy J. Williams, Stefan Costea, Daniel Medeiros +11
Efficient simulation of complex plasma dynamics is crucial for advancing fusion energy research. Particle-in-Cell (PIC) Monte Carlo (MC) simulations provide insights into plasma be…
Parallel I/O Characterization and Optimization on Large-Scale HPC Systems: A 360-Degree Survey
Hammad Ather, Jean Luca Bez, Chen Wang +3
Driven by artificial intelligence, data science, and high-resolution simulations, I/O workloads and hardware on high-performance computing (HPC) systems have become increasingly co…
Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ Analysis
Jeremy J. Williams, Stefan Costea, Allen D. Malony +7
Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling a…
STaKTAU: profiling HPC applications' operating system usage
Camille Coti, Kevin Huck, Allen D. Malony
This paper presents a approach for measuring the time spent by HPC applications in the operating system's kernel. We use the SystemTap interface to insert timers before and after s…
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization
Matthieu Dorier, Romain Egele, Prasanna Balaprakash +5
Distributed data storage services tailored to specific applications have grown popular in the high-performance computing (HPC) community as a way to address I/O and storage challen…
The Ghost of Performance Reproducibility Past
Srinivasan Ramesh, Mikhail Titov, Matteo Turilli +2
The importance of ensemble computing is well established. However, executing ensembles at scale introduces interesting performance fluctuations that have not been well investigated…
SKaMPI-OpenSHMEM: Measuring OpenSHMEM Communication Routines
Camille Coti, Allen D. Malony
Benchmarking is an important challenge in HPC, in particular, to be able to tune the basic blocks of the software environment used by applications. The communication library and di…
Measuring OpenSHMEM Communication Routines with SKaMPI-OpenSHMEM User's manual
Camille Coti, Allen D Malony
This document presents the OpenSHMEM extension for the Special Karlsruhe MPI benchmark and the measurement algorithms used to measure the routines.
On-the-fly Optimization of Parallel Computation of Symbolic Symplectic Invariants
Joseph Ben Geloun, Camille Coti, Allen D. Malony
Group invariants are used in high energy physics to define quantum field theory interactions. In this paper, we are presenting the parallel algebraic computation of special invaria…
Checkpoint/restart approaches for a thread-based MPI runtime
Julien Adam, Maxime Kermarquer, Jean-Baptiste Besnard +6
Fault-tolerance has always been an important topic when it comes to running massively parallel programs at scale. Statistically, hardware and software failures are expected to occu…
Exploring Hyper-Parameter Optimization for Neural Machine Translation on GPU Architectures
Robert Lim, Kenneth Heafield, Hieu Hoang +2
Neural machine translation (NMT) has been accelerated by deep learning neural networks over statistical-based approaches, due to the plethora and programmability of commodity heter…
A Similarity Measure for GPU Kernel Subgraph Matching
Robert Lim, Boyana Norris, Allen Malony
Accelerator architectures specialize in executing SIMD (single instruction, multiple data) in lockstep. Because the majority of CUDA applications are parallelized loops, control fl…
Autotuning GPU Kernels via Static and Predictive Analysis
Robert V. Lim, Boyana Norris, Allen D. Malony
Optimizing the performance of GPU kernels is challenging for both human programmers and code generators. For example, CUDA programmers must set thread and block parameters for a ke…