The paper 'A serverless gateway for event-driven machine learning inference in multiple clouds' has been published by the Universitat Politècnica de València. The paper presents serverless web-based gateways in scalable applications in the cloud. The research has been conducted in cooperation with the AI-SPRINT project team.
"TaScaaS: A Multi-Tenant Serverless Task Scheduler and Load Balancer as a Service" is a new scientific work published in cooperation with the AI-SPRINT project.
The scientific publication "Network Function Decomposition and Offloading on Heterogeneous Networks With Programmable Data Planes" was supported by the work performed by
IBM and Technische Universität Dresden have designed and implemented Perun, a framework for confidential multi-stakeholder machine learning that allows users to make a trade-off between security and performance. The new architecture executes ML training on hardware accelerators (e.g., GPU) while providing security guarantees using trusted computing technologies, such as trusted platform module and integrity measurement architecture. The research conducted has received funding from the European Union’s Horizon 2020 Research and Innovation program under the AI-SPRINT project.
The paper introduces an open-source platform to support serverless computing for scientific data-processing workflow-based applications across the Cloud continuum, work conducted in cooperation with the AI-SPRINT project.
