259 citations · 894 across the 32 of their papers we have counts for
6 papers · 1 filter
Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers
Alexander Brace, Rafael Vescovi, Ryan Chard +4
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…
APPFLx: Providing Privacy-Preserving Cross-Silo Federated Learning as a Service
Zilinghan Li, Shilan He, Pranshu Chaturvedi +9
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…
nelli: a lightweight frontend for MLIR
Maksim Levental, Alok Kamatar, Ryan Chard +2
Multi-Level Intermediate Representation (MLIR) is a novel compiler infrastructure that aims to provide modular and extensible components to facilitate building domain specific comp…
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources
Anakha V Babu, Tekin Bicer, Saugat Kandel +7
We present an end-to-end automated workflow that uses large-scale remote compute resources and an embedded GPU platform at the edge to enable AI/ML-accelerated real-time analysis o…
OpenHLS: High-Level Synthesis for Low-Latency Deep Neural Networks for Experimental Science
Maksim Levental, Arham Khan, Ryan Chard +3
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 s…
Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources
Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson +7
Applications that fuse machine learning and simulation can benefit from the use of multiple computing resources, with, for example, simulation codes running on highly parallel supe…