18 citations · 39 across the 41 of their papers we have counts for
45 papers
LLM Agents as Resilience Engineers for Scientific Applications
Hai Duc Nguyen, Tekin Bicer, Kyle Chard +2
Efficient checkpoint/restart support is essential for resilient HPC scientific applications, but implementing it requires substantial expertise: developers must identify recoverabl…
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…
Interpreting Language Model Hidden States at Scale
Jordan Pettyjohn, Mansi Sakarvadia, Nathaniel Hudson +3
Lens methods interpret large language models (LLMs) by mapping intermediate activations to the output vocabulary, revealing how next-token predictions develop through the network.…
Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap
Rafael Ferreira da Silva, Milad Abolhasani, Peter Beaucage +25
One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The fi…
Towards Transparent Checkpointing with AI-driven Code Generation
Hai Duc Nguyen, Tekin Bicer, Kyle Chard +2
Adding reliable checkpoint/restart support to an MPI scientific application is a time-consuming expert effort that requires deep knowledge of both the application and resilience. W…
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…
Beyond Fixed Budgets: Characterizing the Inelasticity and Limitations of Tree-of-Thought Reasoning Strategies
Atkia Mahila, Avinash Maurya, M. Mustafa Rafique +1
Tree of Thought (ToT) search has become a promising direction for improving the reasoning capabilities of large language models, but deploying these methods in practice raises a qu…
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…
Exploring Distributed Vector Databases Performance on HPC Platforms: A Study with Qdrant
Seth Ockerman, Amal Gueroudji, Song Young Oh +5
Vector databases have rapidly grown in popularity, enabling efficient similarity search over data such as text, images, and video. They now play a central role in modern AI workflo…
The False Promise of Zero-Shot Super-Resolution in Machine-Learned Operators
Mansi Sakarvadia, Kareem Hegazy, Amin Totounferoush +4
A core challenge in scientific machine learning, and scientific computing more generally, is modeling continuous phenomena which (in practice) are represented discretely. Machine-l…
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…
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…
Topology-Aware Knowledge Propagation in Decentralized Learning
Mansi Sakarvadia, Nathaniel Hudson, Tian Li +2
Decentralized learning enables collaborative training of models across naturally distributed data without centralized coordination or maintenance of a global model. Instead, device…
Empowering Scientific Workflows with Federated Agents
Alok Kamatar, J. Gregory Pauloski, Yadu Babuji +5
Agentic systems, in which diverse agents cooperate to tackle challenging problems, are exploding in popularity in the AI community. However, existing agentic frameworks take a rela…