Month: February 2019

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New publication: “Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey”

We are thrilled to announce that we have published a new paper entitled “Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey” on the Springer Artificial Intelligence Review Journal. The paper, that is published as Open Access and can be downloaded following its doi: 10.1007/s10462-018-09679-z, is authored by Giang Nguyen, Stefan Dlugolinsky, […]

D4.2 – First implementation of software platform for accessing accelerators and HPC

This deliverable describes the first implementation of the software platform for accessing accelerators and HPC. The list of components included in the software platform is based on the analysis provided by Deliverable D4.1. This document provides detailed descriptions of software components used in the platforms, the work done on each component and its current status. Evaluation of achieved […]

D5.2 – High Level Hybrid Cloud solutions prototype

This document complements deliverable D5.1 Definition of the Architecture of the Hybrid Cloud (D5.1) with the specific prototype developments carried out to support the deployment of hybrid infrastructures across multiple IaaS Cloud sites. The document describes the technical challenges, the evolution of the components to support this prototype and a roadmap of implementation towards the final release of the […]

D6.3 – First prototype of the DEEP as a Service

This document provides an updated description of the prototype implementation of the DEEP as a Service solution that is being developed within the DEEP-Hybrid-DataCloud project Work Package 6 (WP6). As such it provides an overview of the state of the art of the relevant components and technologies, as well as a technology readiness level assessment […]

D3.2 – Pilot testbed and integration architecgture with EOSC large scale infrastructures

The deliverable contains the plan, design, architecture and deployment of the Pilot Preview testbed based on technical requirements and descriptions from the WP2 use cases. The services and components developed during the DEEP-HybridDataCloud by the teams part of the WP4, 5 and 6 are deployed, tested and validated by end-users in this testbed. It also describes how the […]

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 777435.

Unless otherwise indicated, all materials created by the DEEP-Hybrid-DataCloud consortium are licensed under a Creative Commons Attribution 4.0 International License.

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