15 citations · 54 across the 16 of their papers we have counts for
17 papers
Robust and Generalizable Background Subtraction on Images of Calorimeter Jets using Unsupervised Generative Learning
Yeonju Go, Dmitrii Torbunov, Yi Huang +8
Accurate separation of signal from background is one of the main challenges for precision measurements across high-energy and nuclear physics. Conventional supervised learning meth…
Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments
Yeonju Go, Dmitrii Torbunov, Timothy Rinn +6
Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational auto-encoders, and normalizing flows, have been widely used and studied…
Evaluating Portable Parallelization Strategies for Heterogeneous Architectures in High Energy Physics
Mohammad Atif, Meghna Battacharya, Paolo Calafiura +17
High-energy physics (HEP) experiments have developed millions of lines of code over decades that are optimized to run on traditional x86 CPU systems. However, we are seeing a rapid…
Portable Programming Model Exploration for LArTPC Simulation in a Heterogeneous Computing Environment: OpenMP vs. SYCL
Meifeng Lin, Zhihua Dong, Tianle Wang +6
The evolution of the computing landscape has resulted in the proliferation of diverse hardware architectures, with different flavors of GPUs and other compute accelerators becoming…
Unpaired Image Translation to Mitigate Domain Shift in Liquid Argon Time Projection Chamber Detector Responses
Yi Huang, Dmitrii Torbunov, Brett Viren +4
Deep learning algorithms often are trained and deployed on different datasets. Any systematic difference between the training and a test dataset may degrade the algorithm performan…
UVCGAN v2: An Improved Cycle-Consistent GAN for Unpaired Image-to-Image Translation
Dmitrii Torbunov, Yi Huang, Huan-Hsin Tseng +6
An unpaired image-to-image (I2I) translation technique seeks to find a mapping between two domains of data in a fully unsupervised manner. While initial solutions to the I2I proble…
OpenMP Advisor
Alok Mishra, Abid M. Malik, Meifeng Lin +1
With the increasing diversity of heterogeneous architecture in the HPC industry, porting a legacy application to run on different architectures is a tough challenge. In this paper,…
Portability: A Necessary Approach for Future Scientific Software
Meghna Bhattacharya, Paolo Calafiura, Taylor Childers +16
Today's world of scientific software for High Energy Physics (HEP) is powered by x86 code, while the future will be much more reliant on accelerators like GPUs and FPGAs. The porta…
Solving Simulation Systematics in and with AI/ML
Brett Viren, Jin Huang, Yi Huang +5
Training an AI/ML system on simulated data while using that system to infer on data from real detectors introduces a systematic error which is difficult to estimate and in many ana…
DUNE Software and High Performance Computing
Bonnie Fleming, Kyle Knoepfel, Meifeng Lin +6
DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by m…
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation
Dmitrii Torbunov, Yi Huang, Haiwang Yu +5
Unpaired image-to-image translation has broad applications in art, design, and scientific simulations. One early breakthrough was CycleGAN that emphasizes one-to-one mappings betwe…
Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations
Zhihua Dong, Kyle Knoepfel, Meifeng Lin +2
The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE).…
Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit
Haiwang Yu, Zhihua Dong, Kyle Knoepfel +3
The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to de…
Porting HEP Parameterized Calorimeter Simulation Code to GPUs
Zhihua Dong, Heather Gray, Charles Leggett +3
The High Energy Physics (HEP) experiments, such as those at the Large Hadron Collider (LHC), traditionally consume large amounts of CPU cycles for detector simulations and data ana…
Augmented Signal Processing in Liquid Argon Time Projection Chambers with a Deep Neural Network
Haiwang Yu, Mary Bishai, Wenqiang Gu +9
The Liquid Argon Time Projection Chamber (LArTPC) is an advanced neutrino detector technology widely used in recent and upcoming accelerator neutrino experiments. It features a low…
High-Performance Multi-Mode Ptychography Reconstruction on Distributed GPUs
Zhihua Dong, Yao-Lung L. Fang, Xiaojing Huang +6
Ptychography is an emerging imaging technique that is able to provide wavelength-limited spatial resolution from specimen with extended lateral dimensions. As a scanning microscopy…
Performance Portability Strategies for Grid C++ Expression Templates
Peter A. Boyle, M. A. Clark, Carleton DeTar +3
One of the key requirements for the Lattice QCD Application Development as part of the US Exascale Computing Project is performance portability across multiple architectures. Using…