Experimental Physics Software and Computing Infrastructure
EPSCI Group activities including Hydra, AIEC, AIOP, AIOPP, EJFAT, ERSAP, and JANA.
Lawrence, David↗
Engineering topics
Roy, Ayan
Publications and source records attributed to Roy, Ayan.
RTDP: Streaming Readout Real-Time Development and Testing Platform
The Thomas Jefferson National Accelerator Facility (JLab) has created and is currently working on various tools to facilitate streaming readout (SRO) for upcoming experiments. These include reconstruction frameworks with support for Artificial Intelligence/Machine Learning, distributed High Throughput Computing (HTC), and heterogeneous computing which all contribute significantly to swift data processing and analysis. Designing SRO systems that combine such components for new experiments would benefit from a platform that would combine both simulation and execution components for simulation, testing, and validation before large investments are made. The Real-Time Development Platform (RTDP) is being developed as part of an LDRD funded project at JLab. RTDP aims to establish a seamless connection between algorithms, facilitating the seamless processing of data from SRO to analysis, as well as enabling the execution of these algorithms in various configurations on compute and data centers. Individual software components simulating specific hardware can be replaced with actual hardware when it is available.
Gyurjyan, Vardan↗
Hydra: Computer Vision for Data Quality Monitoring
Hydra: Computer Vision for Data Quality Monitoring Mar 13, 2024, 4:15 PM 30m Charles B. Wang Center, Stony Brook University Poster Track 1: Computing Technology for Physics Research Poster session with coffee break Speaker Ayan Roy Description Hydra is an extensible framework for training, managing, and deploying machine learning models for near real-time data quality monitoring. It is designed to take some of the burden off of shift crews by providing ‘round-the-clock’ monitoring of plots representing the data being collected. The Hydra system is backed by a database which is leveraged for near push button training and is primarily controlled and viewed through a set of web interfaces. This web interface contains a simple-to-use web based GUI for labeling of the datasets used in training; making it possible to label thousands of images quickly and efficiently. To aid in the analysis of Hydra inferences gradCAM, a method of interpretability, is performed and overlaid on the target image, highlighting regions of interest, making diagnosis of problems much faster. Development began in 2019 for the GlueX Experiment in Hall-D, the Hydra system has grown to encompass all of the experimental halls at Jefferson Laboratory. This talk will focus on the features of Hydra as well as provide details of the challenges present with deploying to disparate experimental halls. With a roadmap of development established, Hydra aims to continue to grow in richness of feature set and expand to encompass other monitoring tasks in differing communities.
Roy, Ayan↗