11 citations · 20 across the 22 of their papers we have counts for
25 papers
Bounding Queue Waits for Fair Scheduling of Bursty HPC Workloads via Hierarchical Algorithms
Karaen Senthilkumar, Suman Raj, Maxime Gonthier +3
HPC clusters are shared among many projects, each holding an allocation of node-hours, and ensuring fairness is becoming harder. Foundation models workflows and automated pipelines…
Reputation as Community Memory for the Agentic Web
Ryan Chard, Gus Ellerm, Alexander Brace +4
Agents can now externalize experience into memory, consolidating historical traces into semantic knowledge and procedural shortcuts that persist between sessions. Such memory is ty…
COMPASS: Steering Distributed Vector Search with Scientific Knowledge Graphs
Song Young Oh, Amal Gueroudji, Seth Ockerman +5
Vector databases use hashing to partition data across "shards," logical units for distributed execution. This placement, however, destroys semantic locality, forcing each query int…
ExaServe: Large-Scale LLM Serving on Exascale HPC Systems
Wenyi Wang, Shu Shi, Yadu Babuji +2
Cloud-native LLM serving frameworks have made deployment routine in data centers, yet deploying them on leadership-class supercomputers remains an engineering challenge requiring s…
Avatar: Toward Autonomous End-to-End Orchestration of Scientific Workflows using LLMs
Suman Raj, Hai Duc Nguyen, Haochen Pan +3
Scientific workflow management (WMSs) systems automate execution, yet orchestrate using fixed, hand-tuned rules. LLM agents promise more autonomous orchestration, but it remains un…
Diamond Agent: Agentic Control of Federated HPC Resources as a Service
Haotian Xie, Junlin Chen, Mingkai Zheng +9
Efficiently aggregating and orchestrating computing power across heterogeneous clusters for HPC workflows faces four practical challenges: preserving workflow context across indepe…
StreamGuard: Low-Overhead Resilience for Real-time HPC Data Streams
Hai Duc Nguyen, Bogdan Nicolae, Tekin Bicer +4
Real-time scientific workflows operate on continuous data streams and must produce timely, high-quality results despite executing on complex, failure-prone infrastructure. Hardware…
When More Cores Hurts: The Vector Database Scaling Paradox in HPC
Seth Ockerman, Song Young Oh, Amal Gueroudji +12
Vector databases have been designed and optimized for cloud environments; however, emerging scientific AI workloads (e.g., molecular search, meteorological trajectory detection, an…
Icicle: Scalable Metadata Indexing and Real-Time Monitoring for HPC File Systems
Haochen Pan, Ryan Chard, Song Young Oh +7
Modern HPC file systems can contain billions of files and hundreds of petabytes of data, making even simple questions increasingly intractable to answer. Traditional file system ut…
Scalable Cross-Facility Federated Learning for Scientific Foundation Models on Multiple Supercomputers
Yijiang Li, Zilinghan Li, Kyle Chard +4
Artificial Intelligence for scientific applications increasingly requires training large models on data that cannot be centralized due to privacy constraints, data sovereignty, or…
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…
Experiences with Model Context Protocol Servers for Science and High Performance Computing
Haochen Pan, Ryan Chard, Reid Mello +12
Large language model (LLM)-powered agents are increasingly used to plan and execute scientific workflows, yet most research cyberinfrastructure (CI) exposes heterogeneous APIs and…
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…
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…
Optimizing Fine-Grained Parallelism Through Dynamic Load Balancing on Multi-Socket Many-Core Systems
Wenyi Wang, Maxime Gonthier, Poornima Nookala +4
Achieving efficient task parallelism on many-core architectures is an important challenge. The widely used GNU OpenMP implementation of the popular OpenMP parallel programming mode…
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…