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In the AI-for-science era, scientific computing scenarios such as concurrent learning and high-throughput computing demand a new generation of infrastructure that supports scalable computing resources and automated workflow management on…
Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. These software combinations and…
Automated laboratory experiments have the potential to propel new discoveries, while increasing reproducibility and improving scientists' safety when handling dangerous materials. However, many automated laboratory workflows have not fully…
Edge computing addresses critical limitations of cloud computing such as high latency and network congestion by decentralizing processing from cloud to the edge. However, the need for software replication across heterogeneous edge devices…
Computational reproducibility is fundamental to scientific research, yet many published code supplements lack the necessary documentation to recreate their computational environments. While researchers increasingly share code alongside…
Computational micromagnetics has become an essential tool in academia and industry to support fundamental research and the design and development of devices. Consequently, computational micromagnetics is widely used in the community, and…
CRISTAL is a distributed scientific workflow system used in the manufacturing and production phases of HEP experiment construction at CERN. The CRISTAL project has studied the use of a description driven approach, using meta- modelling…
Linux container technologies such as Docker and Singularity offer encapsulated environments for easy execution of software. In high performance computing, this is especially important for evolving and complex software stacks with…
A key feature of collaboration in science and software development is to have a {\em log} of what and how is being done - for private use and reuse and for sharing selected parts with collaborators, which most often today are distributed…
Workflows specify collections of tasks that must be executed under the responsibility or supervision of human users. Workflow management systems and workflow-driven applications need to enforce security policies in the form of access…
The adoption of heterogeneous computing systems based on diverse architectures to achieve exascale computing power has worsened the performance portability problem of scientific applications that were designed to run on these platforms. To…
Running scientific workflows on a supercomputer can be a daunting task for a scientific domain specialist. Workflow management solutions (WMS) are a standard method for reducing the complexity of application deployment on high performance…
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,…
The advent of experimental science facilities-instruments and observatories, such as the Large Hadron Collider, the Laser Interferometer Gravitational Wave Observatory, and the upcoming Large Synoptic Survey Telescope-has brought about…
With the advances in e-Sciences and the growing complexity of scientific analyses, more and more scientists and researchers are relying on workflow systems for process coordination, derivation automation, provenance tracking, and…
The reproducibility of experiments is one of the main principles of the scientific method. However, numerical N-body experiments, especially those of planetary systems, are currently not reproducible. In the most optimistic scenario, they…
Modern scientific simulations and instruments generate data volumes that overwhelm memory and storage, throttling scalability. Lossy compression mitigates this by trading controlled error for reduced footprint and throughput gains, yet…
Recent studies have shown that the majority of published computational models in systems biology and physiology are not repeatable or reproducible. There are a variety of reasons for this. One of the most likely reasons is that given how…
Beyond sharing datasets or simulations, we believe the Recommender Systems (RS) community should share Task Environments. In this work, we propose a high-level logical architecture that will help to reason about the core components of a RS…
High Performance Computing (HPC) centers provide advanced infrastructure that enables scientific research at extreme scale. These centers operate with hardware configurations, software environments, and security requirements that differ…