Ryan Chard
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View article: Radio Afterglow Detection and AI-driven Response (RADAR): A Federated Framework for Gravitational-wave Event Follow-up
Radio Afterglow Detection and AI-driven Response (RADAR): A Federated Framework for Gravitational-wave Event Follow-up Open
The landmark detection of both gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 has spurred efforts to streamline the follow-up of GW alerts in current and future observing runs of g…
View article: Toward a persistent event-streaming system for high-performance computing applications
Toward a persistent event-streaming system for high-performance computing applications Open
High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications betwe…
View article: RADAR-Radio Afterglow Detection and AI-driven Response: A Federated Framework for Gravitational Wave Event Follow-Up
RADAR-Radio Afterglow Detection and AI-driven Response: A Federated Framework for Gravitational Wave Event Follow-Up Open
The landmark detection of both gravitational waves (GWs) and electromagnetic (EM) radiation from the binary neutron star merger GW170817 has spurred efforts to streamline the follow-up of GW alerts in current and future observing runs of g…
View article: Empowering Scientific Workflows with Federated Agents
Empowering Scientific Workflows with Federated Agents Open
Agentic systems, in which diverse agents cooperate to tackle challenging problems, are exploding in popularity in the AI community. However, the agentic frameworks used to build these systems have not previously enabled use with research c…
View article: Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx
Enabling end-to-end secure federated learning in biomedical research on heterogeneous computing environments with APPFLx Open
Facilitating large-scale, cross-institutional collaboration in biomedical machine learning (ML) projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health…
View article: Parsl+CWL: Towards Combining the Python and CWL Ecosystems
Parsl+CWL: Towards Combining the Python and CWL Ecosystems Open
The Common Workflow Language (CWL) is a widely adopted language for defining and sharing computational workflows. It is designed to be independent of the execution engine on which workflows are executed. In this paper, we describe our expe…
View article: Employing artificial intelligence to steer exascale workflows with colmena
Employing artificial intelligence to steer exascale workflows with colmena Open
Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of their capabilities. We created Colmena to leverage the massive…
View article: Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning
Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning Open
Federated Learning (FL) is a decentralized machine learning paradigm where models are trained on distributed devices and are aggregated at a central server. Existing FL frameworks assume simple two-tier network topologies where end devices…
View article: Employing Artificial Intelligence to Steer Exascale Workflows with Colmena
Employing Artificial Intelligence to Steer Exascale Workflows with Colmena Open
Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of their capabilities. We created Colmena to leverage the massive…
View article: Enabling Remote Management of FaaS Endpoints with Globus Compute Multi-User Endpoints
Enabling Remote Management of FaaS Endpoints with Globus Compute Multi-User Endpoints Open
Globus Compute implements a hybrid Function as a Service (FaaS) model in which a single cloud-hosted service is used by users to manage execution of Python functions on user-owned and -managed Globus Compute endpoints deployed on arbitrary…
View article: Zero Code and Infrastructure Research Data Portals
Zero Code and Infrastructure Research Data Portals Open
Data portals are web applications that facilitate data discovery, access, and sharing. They are essential to meet the FAIR data principles and for advancing open science, fostering interdisciplinary collaborations, and enhancing the reprod…
View article: Octopus: Experiences with a Hybrid Event-Driven Architecture for Distributed Scientific Computing
Octopus: Experiences with a Hybrid Event-Driven Architecture for Distributed Scientific Computing Open
Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting…
View article: BraggHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science
BraggHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science Open
In many experiment-driven scientific domains, such as high-energy physics, material science, and cosmology, high data rate experiments impose hard constraints on data acquisition systems: collected data must either be indiscriminately stor…
View article: An End-to-End Programming Model for AI Engine Architectures
An End-to-End Programming Model for AI Engine Architectures Open
The proliferation of deep learning in various domains has led to remarkable advancements in artificial intelligence applications, such as large-language models for scientific use cases.However, the concomitant exponential growth in computa…
View article: RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring
RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring Open
Precision horticulture is evolving due to scalable sensor deployment and machine learning (ML) integration. These advancements boost the operational efficiency of individual farms, balancing the benefits of analytics with autonomy requirem…
View article: UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving
UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving Open
Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputers, clouds, and accelerators. Such applications call for new…
View article: Steering a Fleet: Adaptation for Large-Scale, Workflow-Based Experiments
Steering a Fleet: Adaptation for Large-Scale, Workflow-Based Experiments Open
Experimental science is increasingly driven by instruments that produce vast volumes of data and thus a need to manage, compute, describe, and index this data. High performance and distributed computing provide the means of addressing the …
View article: Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision Open
Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries. As the demand for more capable AI models continues to grow, we are now entering an era of Trillion Parameter Models (TPM),…
View article: Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx Open
Facilitating large-scale, cross-institutional collaboration in biomedical machine learning projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health info…
View article: Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision Open
Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries. As the demand for more capable AI models continues to grow, we are now entering an era of Trillion Parameter Models (TPM),…
View article: Empowering Scientific Discovery Through Computing at the Advanced Photon Source
Empowering Scientific Discovery Through Computing at the Advanced Photon Source Open
This paper explores the challenges and solutions for managing and processing the vast amount of data generated by the Advanced Photon Source (APS), a synchrotron light source facility producing ultra-bright x-rays for diverse scientific do…
View article: Demonstrating Cross-Facility Data Processing at Scale With Laue Microdiffraction
Demonstrating Cross-Facility Data Processing at Scale With Laue Microdiffraction Open
In February and April 2023 live, at-scale data processing demonstrations were conducted between the Advanced Photon Source (APS), a synchrotron light source, and the Argonne Leadership Computing Facility (ALCF). These tests were run as par…
View article: Deep learning at the edge enables real-time streaming ptychographic imaging
Deep learning at the edge enables real-time streaming ptychographic imaging Open
Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the constru…
View article: The Globus Compute Dataset
The Globus Compute Dataset Open
We present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, f…
View article: The Globus Compute Dataset
The Globus Compute Dataset Open
We present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, f…
View article: Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers Open
The Dynamic PicoProbe at Argonne National Laboratory is undergoing upgrades that will enable it to produce up to 100s of GB of data per day. While this data is highly important for both fundamental science and industrial applications, ther…
View article: APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service Open
Cross-silo privacy-preserving federated learning (PPFL) is a powerful tool to collaboratively train robust and generalized machine learning (ML) models without sharing sensitive (e.g., healthcare of financial) local data. To ease and accel…
View article: nelli: a lightweight frontend for MLIR
nelli: a lightweight frontend for MLIR Open
Multi-Level Intermediate Representation (MLIR) is a novel compiler infrastructure that aims to provide modular and extensible components to facilitate building domain specific compilers. However, since MLIR models programs at an intermedia…