104 citations · 323 across the 20 of their papers we have counts for
9 papers · 1 filter
Overcoming Orchestration Bottlenecks at Exascale: A Decentralized, Policy-Driven Approach for Sim-AI Ensembles
Harikrishna Tummalapalli, Christine M. Simpson, Riccardo Balin +4
Scientific computing is increasingly shifting from monolithic applications to coupled simulation-AI workflows composed of highly heterogeneous tasks with diverse hardware, scale, a…
FIRST: Federated Inference Resource Scheduling Toolkit for Scientific AI Model Access
Aditya Tanikanti, Benoit Côté, Yanfei Guo +9
We present the Federated Inference Resource Scheduling Toolkit (FIRST), a framework enabling Inference-as-a-Service across distributed High-Performance Computing (HPC) clusters. FI…
Aurora: Architecting Argonne's First Exascale Supercomputer for Accelerated Scientific Discovery
William E. Allcock, Benjamin S. Allen, James Anchell +106
Aurora is Argonne National Laboratory's pioneering Exascale supercomputer, designed to accelerate scientific discovery with cutting-edge architectural innovations. Key new technolo…
Workflows Community Summit 2022: A Roadmap Revolution
Rafael Ferreira da Silva, Rosa M. Badia, Venkat Bala +102
Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on workflows to orchestrate large and complex s…
Toward Real-time Analysis of Experimental Science Workloads on Geographically Distributed Supercomputers
Michael Salim, Thomas Uram, J. Taylor Childers +2
Massive upgrades to science infrastructure are driving data velocities upwards while stimulating adoption of increasingly data-intensive analytics. While next-generation exascale s…
Workflows Community Summit: Bringing the Scientific Workflows Community Together
Rafael Ferreira da Silva, Henri Casanova, Kyle Chard +42
Scientific workflows have been used almost universally across scientific domains, and have underpinned some of the most significant discoveries of the past several decades. Many of…
Toward an Automated HPC Pipeline for Processing Large Scale Electron Microscopy Data
Rafael Vescovi, Hanyu Li, Jeffery Kinnison +5
We present a fully modular and scalable software pipeline for processing electron microscope (EM) images of brain slices into 3D visualization of individual neurons and demonstrate…
Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows
Michael A. Salim, Thomas D. Uram, J. Taylor Childers +3
We introduce the Balsam service to manage high-throughput task scheduling and execution on supercomputing systems. Balsam allows users to populate a task database with a variety of…
Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping
Wushi Dong, Murat Keceli, Rafael Vescovi +9
Mapping all the neurons in the brain requires automatic reconstruction of entire cells from volume electron microscopy data. The flood-filling network (FFN) architecture has demons…