11 citations · 25 across the 19 of their papers we have counts for
20 papers
XaaS Containers: Performance-Portable Representation With Source and IR Containers
Marcin Copik, Eiman Alnuaimi, Alok Kamatar +6
High-performance computing (HPC) systems and cloud data centers are converging, and containers are becoming the default method of portable software deployment. Yet, while container…
Addressing Reproducibility Challenges in HPC with Continuous Integration
Valérie Hayot-Sasson, Nathaniel Hudson, André Bauer +3
The high-performance computing (HPC) community has adopted incentive structures to motivate reproducible research, with major conferences awarding badges to papers that meet reprod…
RADAR-Radio Afterglow Detection and AI-driven Response: A Federated Framework for Gravitational Wave Event Follow-Up
Parth Patel, Alessandra Corsi, E. A. Huerta +11
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 follo…
DynoStore: A wide-area distribution system for the management of data over heterogeneous storage
Dante D. Sanchez-Gallegos, J. L. Gonzalez-Compean, Maxime Gonthier +6
Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and improved performance by processin…
D-Rex: Heterogeneity-Aware Reliability Framework and Adaptive Algorithms for Distributed Storage
Maxime Gonthier, Dante D. Sanchez-Gallegos, Haochen Pan +8
The exponential growth of data necessitates distributed storage models, such as peer-to-peer systems and data federations. While distributed storage can reduce costs and increase r…
AERO: An autonomous platform for continuous research
Valérie Hayot-Sasson, Abby Stevens, Nicholson Collier +10
The COVID-19 pandemic highlighted the need for new data infrastructure, as epidemiologists and public health workers raced to harness rapidly evolving data, analytics, and infrastr…
WRATH: Workload Resilience Across Task Hierarchies in Task-based Parallel Programming Frameworks
Sicheng Zhou, Zhuozhao Li, Valérie Hayot-Sasson +6
Failures in Task-based Parallel Programming (TBPP) can severely degrade performance and result in incomplete or incorrect outcomes. Existing failure-handling approaches, including…
Core Hours and Carbon Credits: Incentivizing Sustainability in HPC
Alok Kamatar, Maxime Gonthier, Valerie Hayot-Sasson +6
Realizing a shared responsibility between providers and consumers is critical to manage the sustainability of HPC. However, while cost may motivate efficiency improvements by infra…
Accelerating Python Applications with Dask and ProxyStore
J. Gregory Pauloski, Klaudiusz Rydzy, Valerie Hayot-Sasson +2
Applications are increasingly written as dynamic workflows underpinned by an execution framework that manages asynchronous computations across distributed hardware. However, execut…
Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning
Nathaniel Hudson, Valerie Hayot-Sasson, Yadu Babuji +5
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…
Employing Artificial Intelligence to Steer Exascale Workflows with Colmena
Logan Ward, J. Gregory Pauloski, Valerie Hayot-Sasson +6
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 the…
TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks
J. Gregory Pauloski, Valerie Hayot-Sasson, Maxime Gonthier +5
Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tas…
Octopus: Experiences with a Hybrid Event-Driven Architecture for Distributed Scientific Computing
Haochen Pan, Ryan Chard, Sicheng Zhou +7
Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Even…
Object Proxy Patterns for Accelerating Distributed Applications
J. Gregory Pauloski, Valerie Hayot-Sasson, Logan Ward +4
Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fi…
GreenFaaS: Maximizing Energy Efficiency of HPC Workloads with FaaS
Alok Kamatar, Valerie Hayot-Sasson, Yadu Babuji +6
Application energy efficiency can be improved by executing each application component on the compute element that consumes the least energy while also satisfying time constraints.…
Steering a Fleet: Adaptation for Large-Scale, Workflow-Based Experiments
Jim Pruyne, Valerie Hayot-Sasson, Weijian Zheng +5
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…
Accelerating Communications in Federated Applications with Transparent Object Proxies
J. Gregory Pauloski, Valerie Hayot-Sasson, Logan Ward +5
Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute -- such as when fast networks make it cost-effective to compute on remot…
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery
Ashka Shah, Arvind Ramanathan, Valerie Hayot-Sasson +1
Causal discovery of genome-scale networks is important for identifying pathways from genes to observable traits - e.g. differences in cell function, disease, drug resistance and ot…
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…
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…