Mario David

Ignacio Heredia, Álvaro López García, Germán Moltó et al.

In this paper, we describe a federated compute platform dedicated to support Artificial Intelligence in scientific workloads. Putting the effort into reproducible deployments, it delivers consistent, transparent access to a federation of physically distributed e-Infrastructures. Through a comprehensive service catalogue, the platform is able to offer an integrated user experience covering the full Machine Learning lifecycle, including model development (with dedicated interactive development environments), training (with GPU resources, annotation tools, experiment tracking, and federated learning support) and deployment (covering a wide range of deployment options all along the Cloud Continuum). The platform also provides tools for traceability and reproducibility of AI models, integrates with different Artificial Intelligence model providers, datasets and storage resources, allowing users to interact with the broader Machine Learning ecosystem. Finally, it is easily customizable to lower the adoption barrier by external communities.

Pablo Orviz Fernandez, Joao Pina, Alvaro Lopez Garcia et al.

Supporting e-Science in the EGI e-Infrastructure requires extensive and reliable software, for advanced computing use, deployed across over approximately 300 European and worldwide data centers. The Unified Middleware Distribution (UMD) and Cloud Middleware Distribution (CMD) are the channels to deliver the software for the EGI e-Infrastructure consumption. The software is compiled, validated and distributed following the Software Provisioning Process (SWPP), where the Quality Criteria (QC) definition sets the minimum quality requirements for EGI acceptance. The growing number of software components currently existing within UMD and CMD distributions hinders the application of the traditional, manual-based validation mechanisms, thus driving the adoption of automated solutions. This paper presents umd-verification, an open-source tool that enforces the fulfillment of the QC requirements in an automated way for the continuous validation of the software products for scientific disposal. The umd-verification tool has been successfully integrated within the SWPP pipeline and is progressively supporting the full validation of the products in the UMD and CMD repositories. While the cost of supporting new products is dependant on the availability of Infrastructure as Code solutions to take over the deployment and high test coverage, the results obtained for the already integrated products are promising, as the time invested in the validation of products has been drastically reduced. Furthermore, automation adoption has brought along benefits for the reliability of the process, such as the removal of human-associated errors or the risk of regression of previously tested functionalities.

Jorge Gomes, Isabel Campos, Emanuele Bagnaschi et al.

Containers are increasingly used as means to distribute and run Linux services and applications. In this paper we describe the architectural design and implementation of udocker, a tool which enables the user to execute Linux containers in user mode. We also present a few practical applications, using a range of scientific codes characterized by different requirements: from single core execution to MPI parallel execution and execution on GPGPUs.