Search Results for author: Aristeidis Tsaris

Found 7 papers, 2 papers with code

Ultra-Long Sequence Distributed Transformer

no code implementations4 Nov 2023 Xiao Wang, Isaac Lyngaas, Aristeidis Tsaris, Peng Chen, Sajal Dash, Mayanka Chandra Shekar, Tao Luo, Hong-Jun Yoon, Mohamed Wahib, John Gouley

This paper presents a novel and efficient distributed training method, the Long Short-Sequence Transformer (LSS Transformer), for training transformer with long sequences.

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

no code implementations12 May 2022 Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob Hinkle

In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles.

Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors

no code implementations25 Mar 2020 Xiangyang Ju, Steven Farrell, Paolo Calafiura, Daniel Murnane, Prabhat, Lindsey Gray, Thomas Klijnsma, Kevin Pedro, Giuseppe Cerati, Jim Kowalkowski, Gabriel Perdue, Panagiotis Spentzouris, Nhan Tran, Jean-Roch Vlimant, Alexander Zlokapa, Joosep Pata, Maria Spiropulu, Sitong An, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy Usher

Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision.

Instrumentation and Detectors High Energy Physics - Experiment Computational Physics Data Analysis, Statistics and Probability

FPGA-accelerated machine learning inference as a service for particle physics computing

1 code implementation18 Apr 2019 Javier Duarte, Philip Harris, Scott Hauck, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Suffian Khan, Benjamin Kreis, Brian Lee, Mia Liu, Vladimir Lončar, Jennifer Ngadiuba, Kevin Pedro, Brandon Perez, Maurizio Pierini, Dylan Rankin, Nhan Tran, Matthew Trahms, Aristeidis Tsaris, Colin Versteeg, Ted W. Way, Dustin Werran, Zhenbin Wu

New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains.

Data Analysis, Statistics and Probability High Energy Physics - Experiment Computational Physics Instrumentation and Detectors

Novel deep learning methods for track reconstruction

3 code implementations14 Oct 2018 Steven Farrell, Paolo Calafiura, Mayur Mudigonda, Prabhat, Dustin Anderson, Jean-Roch Vlimant, Stephan Zheng, Josh Bendavid, Maria Spiropulu, Giuseppe Cerati, Lindsey Gray, Jim Kowalkowski, Panagiotis Spentzouris, Aristeidis Tsaris

The second set of models use Graph Neural Networks (GNNs) for the tasks of hit classification and segment classification.

High Energy Physics - Experiment Data Analysis, Statistics and Probability

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