ESnet staff at SC26
23Events
5Days
Nov 15, 2026 – Nov 19, 2026Program window
Sunday, November 15
-
Workshop
13th Annual International Workshop on Innovating the Network for Data Intensive Science — INDIS
Full description
Data networks are the circulatory system for science, discovery, society and industry. But scientific data networking is not a solved problem, and significant challenges remain. These challenges reflect scientists’ persistent needs from data networks: the needs for ever increasing capacity, flexibility, consistency, and collaboration. The theme for the 13th INDIS workshop is Connected Science: Bridging Research and Industry — reflecting not only the role of networking in connecting scientific infrastructure, but also our community’s collaborations across different types of organizations to advance data-intensive science. This year INDIS plans to continue its tradition of having a discussion- and interaction-oriented schedule; based on past feedback, this is always well received. INDIS 2026 delivers an essential complement to the HPC-focused SC26 Technical Program, providing a dedicated platform for HPC researchers to explore data-intensive computing, interconnects, and networking.- Session Chairs
- Ezra KisselEnergy Sciences Network (ESnet)
- Fatema Bannat WalaEnergy Sciences Network (ESnet)
- David MartinLawrence Berkeley National Laboratory (LBNL); Energy Sciences Network (ESnet)
- Cees de LaatUniversity of Amsterdam; Lawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
-
Workshop
The 2nd International Workshop for Software Frameworks and Workload Management on Quantum-HPC Ecosystems
Full description
The integration of quantum computing (QC) with high performance computing (HPC) is emerging as a transformative paradigm for addressing complex scientific and engineering challenges. Given current quantum hardware limitations, such as noise, limited qubit counts, and constrained circuit depth, hybrid quantum–HPC (Q-HPC) ecosystems provide a practical path forward by combining complementary strengths. This workshop focuses on software frameworks, AI-enabled orchestration, and workload management strategies essential for scalable Q-HPC integration. Topics include architecture co-design, heterogeneous resource management, networking, fault tolerance, error mitigation, programming models, middleware, benchmarking, and large-scale distributed Q-HPC systems. Emphasis will be placed on open, interoperable ecosystems such as openQSE and on ML/AI techniques for adaptive workflow orchestration, topology-aware scheduling, performance prediction, and autonomous runtime control. Through invited talks, technical presentations, panels, and special sessions, the workshop will foster collaboration across academia, industry, national laboratories, and funding agencies to define research priorities and accelerate AI-driven Q-HPC ecosystems.- Session Chairs
- Katie KlymkoNational Energy Research Scientific Computing Center (NERSC); ESnet; Lawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
-
Workshop
Security Panel
Full description
SC26 has not supplied a description for this event.
- Panelists
- Adam SlagellEnergy Sciences Network (ESnet)
-
Workshop
Navigating the Spectrum of Science Workloads with ESnet JLab FPGA Accelerated Transport (EJFAT)
Full description
Cross-facility workflows are no longer optional but a requirement for the success of current and future science campaigns. From remote labs to multi-institutional science campaigns, advances in instrumentation and technological innovation are enabling experimental and observational scientific user facilities to generate data faster than processing and storage can handle. Our work explores EJFAT as a potential solution to these challenges. While EJFAT has been shown to be performant and scalable, this paper explores considerations for integrating EJFAT into real-world scientific experiments. We explore two applications: one highly integrated, the other highly generalizable. The first is a highly tuned and optimized workflow for pushing data as fast as possible to meet the goals of scientific experiments, while the second is a general ecosystem lowering the barrier for scientists to leverage HPC resources with minimal effort representing two common classes of applications typical found in scientific user facilities.- Author/Presenters
- Yatish KumarLawrence Berkeley National Laboratory
-
Workshop
Short Talk: Portable AI Workflows and Federated Agents for Experiment-in-the-Loop Synchrotron Science
Full description
SC26 has not supplied a description for this event.
- Presenters
- Justas BalcasEnergy Sciences Network (ESnet)
-
Workshop
ORBIT: An AI-Powered Assistant for NOC Operations in a Data-Intensive Science Network
Full description
High-performance networks are critical infrastructure for data-intensive science, and their effective management relies on efficient incident response in Network Operations Centers (NOCs). This paper introduces the Operations Response \& Business Intelligence Toolkit (ORBIT), an AI-powered assistant that enhances incident response by consolidating information from disparate, siloed systems. ORBIT delivers synthesized results directly into the operator's primary work interface, applying agentic AI principles through a centralized reasoning service and a common model-access gateway. The system ensures transparency by logging all AI-generated outputs for operator review and rigorously controls access to sensitive data. In this paper, we describe the ORBIT architecture, present a selection of initial results from operational testing within ESnet’s NOC, and share lessons learned during its development and deployment; the complete findings are available in a companion technical report. Our findings highlight the importance of prompt engineering and a human-in-the-loop design for building trust and facilitating adoption.- Author/Presenters
- Bin DongEnergy Sciences Network (ESnet)
- Sukhada GholbaEnergy Sciences Network (ESnet)
- Brooklin GoreEnergy Sciences Network (ESnet)
- Shawn KwangEnergy Sciences Network (ESnet)
- David MitchellEnergy Sciences Network (ESnet)
- Samuel OehlertEnergy Sciences Network (ESnet)
- Garrett StewartEnergy Sciences Network (ESnet)
- Brendan WhiteEnergy Sciences Network (ESnet)
- Luke BakerEnergy Sciences Network (ESnet)
- Edward BalasEnergy Sciences Network (ESnet)
- Britt GathrightEnergy Sciences Network (ESnet)
- Chin GuokEnergy Sciences Network (ESnet)
- John Paul HerronEnergy Sciences Network (ESnet)
- John MaCauleyEnergy Sciences Network (ESnet)
- Scott RichmondEnergy Sciences Network (ESnet)
- Chris RobbEnergy Sciences Network (ESnet)
- Christopher TracyEnergy Sciences Network (ESnet)
- Kesheng (John) WuLawrence Berkeley National Laboratory (LBNL); ESnet
Monday, November 16
-
Workshop
Stress-Testing Exascale Scientific Data Output - ADIOS2 Configuration Strategies for WarpX under Extreme Load Imbalance
Full description
Spatially imbalanced, temporally irregular simulation output challenges I/O configurations tuned for balanced workloads. This work evaluates ADIOS2 BP5 configurations through openPMD-api using WarpX on Frontier at ORNL and Perlmutter at NERSC, contrasting balanced 3D Cartesian output with boosted-frame back-transformed diagnostics (BTD). BTD combines rank-level output skew with snapshot contributions spanning multiple simulation steps. Balanced output reaches 3.64~TB/s without compression on 2,048 Frontier nodes and over 1~TB/s on 512 Perlmutter nodes; lossless Blosc2 compression achieves approximately 7~TB/s application-level effective throughput on Frontier. In the tested BTD configurations, SPAN combined with asynchronous writing provides the highest throughput on Frontier, FlattenSteps supports assembly of complete lab-frame snapshots for checkpointing without reader modification and with negligible write-time overhead and no penalty on read performance, and DataSizeBased aggregation improves throughput when subfile counts are constrained. These results identify complementary mechanisms for handling irregular output and provide configuration guidance for these workloads and systems.- Author/Presenters
- Alexander SimLawrence Berkeley National Laboratory
- Kesheng (John) WuLawrence Berkeley National Laboratory (LBNL); ESnet; Lawrence Berkeley National Laboratory (LBNL)
-
Workshop
Fair, Random IO Operations are Hard
Full description
The IO500 Committee continuously works to improve and expand what the IO500 benchmarks cover to keep them both current and relevant. The latest change we have been working on is a random 4 KiB read phase. Our first attempt yielded some unexpected results prompting a deep dive and re-implementation from scratch. Where we are now requires community feedback to ensure the best path forward.- Author/Presenters
- Jean Luca BezESnet; Lawrence Berkeley National Laboratory (LBNL)
-
Demo
IRI 2.0: A Common Language for DOE Research Infrastructure
Full description
The DOE's Integrated Research Infrastructure (IRI) provides consistent, machine-readable descriptions of facility resources, capabilities, access paths, and services. We'll show how these descriptions support both human-driven workflows and agentic systems that discover and interact with DOE research infrastructure.- Speakers
- John MacAuleyESnet/LBL
- Justas BalcasESnet/LBL
-
Featured booth talk
ESnet's 40th Anniversary Celebration
Full description
The DOE's sole high-performance network for science, the Energy Sciences Network (ESnet), was formally created in 1986. On Nov. 16 at 7:30pm in the DOE Booth (#4829), ESnet Executive Director Inder Monga will give a brief presentation followed by lightning talks by DOE leadership and ESnet partners and staff, including Dylan Jacob, SCinet 2026 Chair and ESnet core routing and optical networking group lead. Come raise a toast to 40 years of accelerating discoveries in fusion, physics, cosmology, and more across the DOE complex. More info: www.es.net/40- Speakers
- Inder Monga
-
Demo
ESnet on AWS: A Cloud Facility Behind the IRI API
Full description
We'll show ESnet AWS cloud capabilities exposed through the Integrated Research Infrastructure (IRI), demonstrating how to make cloud infrastructure usable together with other DOE facility resources. We present AWS-backed compute (batch-scheduled, container-execution, GPU-capable) and storage endpoints (plus a Globus DTN for data transfer) through the same DOE-IRI interface enabled at the ASCR facilities. This demo facility implements AWS support through IRI, and the same adapter pattern could use Google Cloud or Azure resources without changing the interface. The demo runs the identical client seamlessly across all ASCR facilities - NERSC, ALCF, OLCF, and ESnet on the AWS Cloud, switching only the facility endpoint while the researcher workflow remains the same. As the science workload, the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory will run its containerized X-ray tomography and segmentation workflow on the AWS facility, submitted from the SSRL cross-facility workflow dashboard through the same IRI API calls it uses for NERSC and ALCF. SSRL is a Basic Energy Sciences user facility, so this is a beamline workload from outside ASCR running on the ASCR centers and the cloud facility from a single interface.- Speakers
- Justas BalcasESnet/LBL
- John MacAuleyESnet/LBL
Tuesday, November 17
-
Posters
Streaming Nuclear Physics at Scale
Full description
Nuclear physics experiments have long challenged the limits of high-rate and low-latency logic. Presently, streaming readout can move decision making from fixed detector electronics to software, allowing raw detector data to be processed continuously as they are produced. We highlight the state of Jefferson Lab and ESnet collaborative work with example workflows. First, existing data from the CLAS12 detector were replayed across ESnet through the EJFAT network load balancer to the Perlmutter supercomputer at NERSC, reaching 100 Gb/s as jobs dynamically scaled the workflow. Second, live data direct from the CLAS12 electromagnetic calorimeter were streamed, showing end-to-end capabilities and real-time cosmic ray identification. These demonstrations go beyond earlier transport benchmarks to physics-based streaming workflows, thus combining high-rate data transport with online scientific processing. We also discuss applying this approach to Jefferson Lab’s development of streaming-readout modules for positron emission tomography (PET) processing, enabling future whole-area, whole-body scanning otherwise considered impractical.- Authors
- Derek HowardEnergy Sciences Network (ESnet)
- Yatish KumarEnergy Sciences Network (ESnet)
- Stacey SheldonEnergy Sciences NetworkLab
-
Roundtable
IRI Developer & User Community Work Session
Full description
Join an open working session for Integrated Research Infrastructure developers, facility teams, and users to discuss current implementations, integration challenges, priorities, and future capabilities. Bring questions, use cases, and feedback to help shape the next steps for IRI.- Speakers
- John MacAuleyESnet/LBL
-
Roundtable
EJFAT Streaming Technology and User Feedback
Full description
The ESnet-JLab FPGA Accelerated Transport, or EJFAT (pronounced “Edge-Fat”) prototype was designed to seamlessly integrate edge and cluster computing in order to allow data from multiple types of scientific instruments to be streamed and processed in near real time by multiple HPC facilities — and, if needed, to redirect those data streams dynamically. EJFAT has progressed significantly since SC25 in terms of users and use cases. This is an opportunity to get updates, provide the team input and engage with new ideas and use cases.- Speakers
- Yatish KumarESnet/LBL
- Eli DartESnet/LBNL
-
SCinet Network Research Exhibition
ORBIT: An AI-Powered Assistant for NOC Operations in a Data-Intensive Science Network
Full description
ESnet shares its pragmatic journey developing AI tools that deliver measurable improvements to Network Operations Center efficiency. Rather than chasing trends, ESnet focused on AI-assisted ticket resolution. This presentation details two concrete applications — Intelligent Resolution Guidance that proactively surfaces relevant documentation, and Adaptive Incident Summarization that generates audience-tailored ticket summaries. Through systematic stakeholder engagement and incremental development, ESnet demonstrates how responsible AI implementation can genuinely augment operational capabilities. Attendees will gain practical insights on balancing AI capabilities with limitations, ensuring tools address real workflow pain points while integrating seamlessly into existing processes, and learn from both successes and challenges encountered.- Presenter
- John WuESnet
Wednesday, November 18
-
SCinet Network Research Exhibition
Customized End-to-End Services for Science Workflows via SENSE
Full description
nri114- Primary contact
- Tom LehmanEnergy Sciences Network (ESnet)
- Contributors
- Xi YangEnergy Sciences Network (ESnet)
- Justas BalcasEnergy Sciences Network (ESnet)
-
Birds of a Feather
Navigating Complexity: Achieving Performance Portability in the Evolving Landscape of Accelerated HPC Systems
Full description
With the increasing demand for AI in HPC, there has been a rapid rise in accelerated architectures, portable programming models, and frameworks. The already-daunting task of programming for interconnected accelerated systems has become even more complex. This BoF, organized by IXPUG, will focus on portable programming across a wide range of heterogeneous architectures—including Intel, NVIDIA, AMD, and ARM supporting diverse simulation, data analytics, and AI workloads. The session will explore key challenges, state-of-the-art solutions, and emerging best practices for programming across these systems, identifying common principles and methodologies that support development and long-term maintenance across sites, architectures, and scientific applications.- Additional Session Leaders
- David MartinLawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
- TUT — Tutorial Reg Pass
- XO/EX — Exhibits Reg Pass
-
Demo
IRI 2.0: A Common Language for DOE Research Infrastructure
Full description
The DOE's Integrated Research Infrastructure (IRI) provides consistent, machine-readable descriptions of facility resources, capabilities, access paths, and services. We'll show how these descriptions support both human-driven workflows and agentic systems that discover and interact with DOE research infrastructure.- Speakers
- John MacAuleyESnet/LBL
- Justas BalcasESnet/LBL
-
Roundtable
Streaming Workflows to ASCR Supercomputers
Full description
ASCR compute facilities are often the desired end points for EJFAT (for ESnet-JLab FPGA Accelerated Transport) workflows. Real-time compute brings unique requirements on availability, scheduling and run control integration. Join this discussion to help the EJFAT team think through and shape the way we access resources in these unique high capacity environments.- Speakers
- Yatish KumarESnet/LBL
- Eli DartESnet/LBNL
-
SCinet Network Research Exhibition
StarLight Agentic AIDTN for High-Performance Data/Process Transport with Research Platforms
Full description
NRI103- Contributors
- Se-Young YuEnergy Sciences Network (ESnet)
-
Demo
ESnet on AWS: A Cloud Facility Behind the IRI API
Full description
We'll show ESnet AWS cloud capabilities exposed through the Integrated Research Infrastructure (IRI), demonstrating how to make cloud infrastructure usable together with other DOE facility resources. We present AWS-backed compute (batch-scheduled, container-execution, GPU-capable) and storage endpoints (plus a Globus DTN for data transfer) through the same DOE-IRI interface enabled at the ASCR facilities. This demo facility implements AWS support through IRI, and the same adapter pattern could use Google Cloud or Azure resources without changing the interface. The demo runs the identical client seamlessly across all ASCR facilities - NERSC, ALCF, OLCF, and ESnet on the AWS Cloud, switching only the facility endpoint while the researcher workflow remains the same. As the science workload, the Stanford Synchrotron Radiation Lightsource (SSRL) at SLAC National Accelerator Laboratory will run its containerized X-ray tomography and segmentation workflow on the AWS facility, submitted from the SSRL cross-facility workflow dashboard through the same IRI API calls it uses for NERSC and ALCF. SSRL is a Basic Energy Sciences user facility, so this is a beamline workload from outside ASCR running on the ASCR centers and the cloud facility from a single interface.- Speakers
- Justas BalcasESnet/LBL
- John MacAuleyESnet/LBL
Thursday, November 19
-
Paper
Fault Injection and Resilience Across Emerging Platforms
Full description
This session studies resilience across quantum, GPU, and systolic platforms. It combines transient-fault mitigation, cross-architecture injection, operational characterization, and radiation-induced error analysis.- Session Chair
- David MartinLawrence Berkeley National Laboratory (LBNL); Energy Sciences Network (ESnet)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
-
Birds of a Feather
Real-Time Scientific Data Streaming to HPC Nodes: Challenges and Innovations VI
Full description
Emerging scientific needs are driving a new class of workflows that require near real-time processing, urgent computing, and time-sensitive decision-making. The traditional "compute-store-analyze" paradigm, which relies on dumping massive datasets to file systems for post-processing, has become an unsustainable bottleneck. It introduces unacceptable latency, and often renders high-frequency data analysis practically impossible. This BoF discusses this challenge by exploring the architectural shift from file-based workflows to high-performance streaming. In this new paradigm, storage is treated not as a buffer for post-processing, but as a sink for final scientific results, while analysis, visualization, and reduction occur in-transit or in-situ.- Additional Session Leaders
- Eli DartEnergy Sciences Network (ESnet); Lawrence Berkeley National Laboratory (LBNL)
- Recordings
- Livestreamed, Recorded
- Registration Categories
- TP — Tech Program Reg Pass
- W — Workshop Reg Pass
- TUT — Tutorial Reg Pass
- XO/EX — Exhibits Reg Pass
No events match your search and selected filters. Try another search or clear these filters.
Source: SC26 Conference Program. Program details may change.
Last edited: November 9, 2026
