arXiv subjects

Alexander Kanitz

Publications and source records attributed to Alexander Kanitz.

4 recordsLinked to original sources

arXiv2026

Hybrid Cloud Architectures for Research Computing: Applications and Use Cases

Scientific research increasingly depends on robust and scalable IT infrastructures to support complex computational workflows. With the proliferation of services provided by research infrastructures, NRENs, and commercial cloud providers, researchers must navigate a fragmented ecosystem of computing environments, balancing performance, cost, scalability, and accessibility. Hybrid cloud architectures offer a compelling solution by integrating multiple computing environments to enhance flexibility, resource efficiency, and access to specialised hardware. This paper provides a comprehensive overview of hybrid cloud deployment models, focusing on grid and cloud platforms (OpenPBS, SLURM, OpenStack, Kubernetes) and workflow management tools (Nextflow, Snakemake, CWL). We explore strategies for federated computing, multi-cloud orchestration, and workload scheduling, addressing key challenges such as interoperability, data security, reproducibility, and network performance. Drawing on implementations from life sciences, as coordinated by the ELIXIR Compute Platform and their integration into a wider EOSC context, we propose a roadmap for accelerating hybrid cloud adoption in research computing, emphasising governance frameworks and technical solutions that can drive sustainable and scalable infrastructure development.

cs.DC↗

arXiv2024

The GA4GH Task Execution API: Enabling Easy Multi Cloud Task Execution

The Global Alliance for Genomics and Health (GA4GH) Task Execution Service (TES) API is a standardized schema and API for describing and executing batch execution tasks. It provides a common way to submit and manage tasks to a variety of compute environments, including on premise High Performance Compute and High Throughput Computing (HPC/HTC) systems, Cloud computing platforms, and hybrid environments. The TES API is designed to be flexible and extensible, allowing it to be adapted to a wide range of use cases, such as "bringing compute to the data" solutions for federated and distributed data analysis or load balancing across multi cloud infrastructures. This API has been adopted by a number of different service providers and utilized by several workflow engines. Using its capabilities, genomes research institutes are building hybrid compute systems to study life science.

cs.DC↗

arXiv2023

Recording provenance of workflow runs with RO-Crate

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain. A corresponding RO-Crate for this article is at https://w3id.org/ro/doi/10.5281/zenodo.10368989

cs.DL↗

arXiv2018

Optimization of femtosecond laser processing in liquids

In this paper we analyze femtosecond laser processing of metals in liquids searching for optimal conditions for predictable ablation. Incident laser pulses are stretched or compressed, self-focused and scattered on bubbles and on surface waves in the liquid environment. Influence of these effects on the laser intensity distribution on the target surface is discussed and optimal processing parameters are suggested.

physics.app-ph↗