151 citations · 219 across the 24 of their papers we have counts for
26 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…
Strategies for Deploying AI Agents in Production at Scientific User Facilities
Ming Du, Xiangyu Yin, Michael Prince +40
Agentic artificial intelligence (AI) is moving beyond research demonstrations toward production use at scientific user facilities, including light sources, neutron sources, nanosci…
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…
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…
CoCoDiff: Optimizing Collective Communications for Distributed Diffusion Transformer Inference Under Ulysses Sequence Parallelism
Bin Ma, Xingjian Ding, Tekin Bicer +2
Diffusion Transformers (DiTs) are increasingly adopted in scientific computing, yet growing model sizes and resolutions make distributed multi-GPU inference essential. Ulysses sequ…
mLR: Scalable Laminography Reconstruction based on Memoization
Bin Ma, Viktor Nikitin, Xi Wang +2
ADMM-FFT is an iterative method with high reconstruction accuracy for laminography but suffers from excessive computation time and large memory consumption. We introduce mLR, which…
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…
Training-Free Inference for High-Resolution Sinogram Completion
Jiaze E, Srutarshi Banerjee, Tekin Bicer +3
High-resolution sinogram completion is critical for computed tomography reconstruction, as missing projections can introduce severe artifacts. While diffusion models provide strong…
ZenFlow: Enabling Stall-Free Offloading for LLM Training
Tingfeng Lan, Yusen Wu, Bin Ma +7
Fine-tuning large language models (LLMs) often exceeds GPU memory limits, prompting systems to offload model states to CPU memory. However, existing offloaded training frameworks l…
Ptychographic Image Reconstruction from Limited Data via Score-Based Diffusion Models with Physics-Guidance
Refik Mert Cam, Junjing Deng, Rajkumar Kettimuthu +2
Ptychography is a data-intensive computational imaging technique that achieves high spatial resolution over large fields of view. The technique involves scanning a coherent beam ac…
Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification
Canberk Ekmekci, Tekin Bicer, Zichao Wendy Di +2
Ptychography is a scanning coherent diffractive imaging technique that enables imaging nanometer-scale features in extended samples. One main challenge is that widely used iterativ…
Deep learning-based spatio-temporal fusion for high-fidelity ultra-high-speed x-ray radiography
Songyuan Tang, Tekin Bicer, Tao Sun +2
Full-field ultra-high-speed (UHS) x-ray imaging experiments have been well established to characterize various processes and phenomena. However, the potential of UHS experiments th…
FCDM: A Physics-Guided Bidirectional Frequency Aware Convolution and Diffusion-Based Model for Sinogram Inpainting
Jiaze E, Srutarshi Banerjee, Tekin Bicer +3
Computed tomography (CT) is widely used in scientific imaging systems such as synchrotron and laboratory-based nano-CT, but acquiring full-view sinograms requires high radiation do…
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…
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources
Anakha V Babu, Tekin Bicer, Saugat Kandel +7
We present an end-to-end automated workflow that uses large-scale remote compute resources and an embedded GPU platform at the edge to enable AI/ML-accelerated real-time analysis o…
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
Baixi Sun, Xiaodong Yu, Chengming Zhang +7
CNN-based surrogates have become prevalent in scientific applications to replace conventional time-consuming physical approaches. Although these surrogates can yield satisfactory r…
Deep learning at the edge enables real-time streaming ptychographic imaging
Anakha V Babu, Tao Zhou, Saugat Kandel +15
Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from…
Linking Scientific Instruments and HPC: Patterns, Technologies, Experiences
Rafael Vescovi, Ryan Chard, Nickolaus Saint +10
Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subset…
High-Performance Ptychographic Reconstruction with Federated Facilities
Tekin Bicer, Xiaodong Yu, Daniel J. Ching +5
Beamlines at synchrotron light source facilities are powerful scientific instruments used to image samples and observe phenomena at high spatial and temporal resolutions. Typically…
Scalable and accurate multi-GPU based image reconstruction of large-scale ptychography data
Xiaodong Yu, Viktor Nikitin, Daniel J. Ching +3
While the advances in synchrotron light sources, together with the development of focusing optics and detectors, allow nanoscale ptychographic imaging of materials and biological s…
Deep Learning-based Low-dose Tomography Reconstruction with Hybrid-dose Measurements
Ziling Wu, Tekin Bicer, Zhengchun Liu +3
Synchrotron-based X-ray computed tomography is widely used for investigating inner structures of specimens at high spatial resolutions. However, potential beam damage to samples of…
Petascale XCT: 3D Image Reconstruction with Hierarchical Communications on Multi-GPU Nodes
Mert Hidayetoglu, Tekin Bicer, Simon Garcia de Gonzalo +6
X-ray computed tomography is a commonly used technique for noninvasive imaging at synchrotron facilities. Iterative tomographic reconstruction algorithms are often preferred for re…
Joint ptycho-tomography with deep generative priors
Selin Aslan, Zhengchun Liu, Viktor Nikitin +3
Joint ptycho-tomography is a powerful computational imaging framework to recover the refractive properties of a 3D object while relaxing the requirements for probe overlap that is…