Learn more about ProActive software with media resources and downloadable use cases
HPE, Intel, together with Activeeon and in the framework of HPE GreenLake, allow end-users, developers and data scientists to run pure HPC, pure AI and converged HPC/AI workflows, and to extend this environment to seamlessly manage workloads and data across off-premises managed cloud and public cloud systems. more...
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Learn more about Azure availability zones, its performance impact and how it can help you build high availability applications and reduce cost more...
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Learn how to use ProActive Workflows & Scheduling and ProActive Machine Learning in 5 training sessions more...
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Our microbiota is a key actor between food and our body and a major actor in well-being, health and desease more...
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While adopting a cloud strategy, businesses need a solution to help them build a workflow to run business applications in the cloud, often along with existing on-premise infrastructure... more...
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Distributed R environment for quantitative metagenomics platform and statistical analysis. more...
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Control your analytics at scale on large amount of IoT data generated every day more...
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CNES works with Activeeon on Sentinel satellite imagery analysis as part of PEPS (Plateforme d’exploitation des produits Sentinel) project. PEPS platform is part of PEPS aims to provide external users, in SaaS mode, the access to satellite imagery data, for research, education, agronomy or commercial use. more...
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Now, thanks to ProActive and additional optimizations we made along the way with Azure, the batch time which previously was taking us 18 hours, is now down to 5 hours more...
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Orchestrate third-party applications and schedule large jobs over 7 environments. more...
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Orchestration tools become more and more relevant to connect services, applications, multiple databases, compute over multi-clouds, custom analytics, automate and control processes. more...
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In this white paper, we will introduce the state of the art of big data processing: from parallel processing with the two main types of parallelisms, to several famous big data processing platforms such as Hadoop, Spark and YARN, and some Stream processing platforms like Spark Streaming, S4, Storm, Flink, etc. more...
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While the Big Data ecosystem is becoming more and more complex through additional storage tools, analytical tools, BI tools, etc., a stronger need for a comprehensive orchestrator is emerging. more...
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Workload management in the context of hybrid clouds brings an innovative and flexible solution that this whitepaper aims to clarify more...
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Explore some testimonials, demos, use cases, ... more...
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Automating IT systems at large scale can be a big challenge due to the complexity and the specificity of each IT infrastructure more...
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Big data analytics and machine learning orchestration, parallelisation of computations in R, Python, Matlab and much more more...
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