Engineering topics

Wegner, Tobias

Publications and source records attributed to Wegner, Tobias.

4 records

DOE OSTI2024

Extending Rucio with modern cloud storage support

Rucio is a software framework designed to facilitate scientific collaborations in efficiently organising, managing, and accessing extensive volumes of data through customizable policies. The framework enables data distribution across globally distributed locations and heterogeneous data centres, integrating various storage and network technologies into a unified federated entity. Rucio offers advanced features like distributed data recovery and adaptive replication, and it exhibits high scalability, modularity, and extensibility. Originally developed to meet the requirements of the high-energy physics experiment ATLAS, Rucio has been continuously expanded to support LHC experiments and diverse scientific communities. Recent R&D projects within these communities have evaluated the integration of both private and commercially-provided cloud storage systems, leading to the development of additional functionalities for seamless integration within Rucio. Furthermore, the underlying systems, FTS and GFAL/Davix, have been extended to cater to specific use cases. This contribution focuses on the technical aspects of this work, particularly the challenges encountered in building a generic interface for self-hosted cloud storage, such as MinIO or CEPH S3 Gateway, and established providers like Google Cloud Storage and Amazon Simple Storage Service. Additionally, the integration of decentralised clouds like SEAL is explored. Key aspects, including authentication and authorisation, direct and remote access, throughput and cost estimation, are highlighted, along with shared experiences in daily operations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2021

Mid-Wavelength and Long-Wavelength Infrared Focal Planes for SmallSat Applications

In this presentation, we will report our recent efforts in achieving high performance in Antimonides type-II superlattice (T2SL) based infrared photodetectors using the barrier infrared detector (BIRD) architecture. The high operating temperature (HOT) BIRD focal plane arrays (FPAs) offer the same high performance, uniformity, operability, manufacturability, and affordability advantages as InSb. However, mid-wavelength infrared (MWIR) HOT-BIRD FPAs can operate at significantly higher temperatures (>150K) than InSb FPAs (typically 80K). Moreover, while InSb has a fixed cutoff wavelength (~5.4 µm), the HOT-BIRD offers a continuous adjustable cutoff wavelength, ranging from ~4 µm to >15 µm, and is therefore also suitable for long wavelength infrared (LWIR) as well. The LWIR detectors based on the BIRD architecture has also demonstrated significant operating temperature advantages over those based on traditional p-n junction designs. Two 6U SmalSat missions CIRAS (Cubesat Infrared Atmospheric Sounder) and HyTI (Hyperspectral Thermal Imager) are based on JPL’s T2SL BIRD focal plane arrays (FPAs). Based on III-V compound semiconductors, the BIRD FPAs offer a breakthrough solution for the realization of low cost (high yield), high-performance FPAs with excellent uniformity and pixel-to-pixel operability. We have also exploring the possibilities of integrating either metasurface resonator cavity or metasurface based flatlens with individual pixels to improve the signal-to-noise ratio of the detectors. Furthermore, we will discuss the advantages of the utilization of all digital read out integrated circuits with HOT-BIRDs.

Ghuman, Parminder↗

DOE OSTI2021

Seamless integration of commercial Clouds with ATLAS Distributed Computing

The CERN ATLAS Experiment successfully uses a worldwide dis-tributed computing Grid infrastructure to support its physics programme at the Large Hadron Collider (LHC). The Grid workflow system PanDA routinely manages up to 700,000 concurrently running production and analysis jobs to process simulation and detector data. In total more than 500 PB of data are distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing data rate in future LHC runs new developments are underway to embrace industry accepted protocols and technologies, and utilize opportunistic resources in a standard way. This paper reviews how the Google and Amazon Cloud computing ser-vices have been seamlessly integrated as a Grid site within PanDA and Rucio. Performance and brief cost evaluations will be discussed. Such setups could offer advanced Cloud tool-sets and provide added value for analysis facilities that are under discussions for LHC Run-4.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Rucio: Scientific Data Management

Rucio is an open-source software framework that provides scientific collaborations with the functionality to organize, manage, and access their data at scale. The data can be distributed across heterogeneous data centers at widely distributed locations. Rucio was originally developed to meet the requirements of the high-energy physics experiment ATLAS, and now is continuously extended to support the LHC experiments and other diverse scientific communities. In this article, we detail the fundamental concepts of Rucio, describe the architecture along with implementation details, and report operational experience from production usage.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗