Jun 27, 2018 from Activeeon
Grid computing represents a computer network where each computer’s resources are shared with other computers in the system. This solution allows coordinating computer resources on different networks. The concept of grid computing is to share load across multiple computers to complete tasks more efficiently and quickly. Every authorized computer in the grid would have access to enormous processing power and storage capacity.
Computer power is like electricity - it can hardly be stored if not used. The Grid is a service for sharing computer power and data storage capacity over the Internet. Many systems are tightly coupled by software and networks to work together on single or related problems. Optimizing the use of computing resources (e.g. available disk storage on the machines of the enterprise, putting together heterogeneous systems to create a large virtual computing system).
Activeeon offers grid computing solutions that will help you manage all your data processes in grids - learn more about ProActive Workflows & Scheduling and Big Data Automation. Thanks to our solutions you will be able to execute and manage data transfers on other desktop machines, clusters, Grids and Clouds.
ProActive Workflows & Scheduling allows you to federate your existing resources (clusters, native batch schedulers, desktop machines and virtualized infrastructures) and add on-demand extra resources from external environments such as clouds. Resources coming from multiple origins are unified as ProActive Nodes and can be accessed transparently: Desktop machines (Windows, Linux, MacOS X), all kind of stand-alone server machines, cluster nodes managed by common batch schedulers (Slurm, LSF, SGE) and private or public Clouds resources (OpenStack, CloudStack, VMWare, Windows Azure, Amazon EC2, etc.).
Control the resources acquisition behavior according to various policies such as load-based or time-based. With smart policy-driven decisions, control task placement, workload capacity (planning and elasticity) and energy saving strategies.
ProActive Workflows & Scheduling offers monitoring capabilities for your resources and your applications to collect and track the metrics on which you base your triggers.
Oct 23, 2020 from ML Team
Deep learning algorithms are a series of (deep) neural networks that learn to recognise patterns from data. However, finding high-performance neural networks architectures for a certain type of application can demand many years of research...
Sep 3, 2020 from Caroline Pacheco
Let’s suppose that you have a large infrastructure containing several machines that have different operating systems (e.g. Microsoft Windows, Linux, MacOS) and distinct hardware configurations...
Mar 13, 2020 from Activeeon
Users can interact with third-party systems in two ways: using ProActive web portals (Studio, Automation Dashboard, Scheduler, Resource Manager) or using APIs (REST, Java, CLI, etc.)...