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Adaptive Computing releases Moab 8.0
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Adaptive Computing releases Moab 8.0 

“This latest version of Moab underscores our commitment to innovation in the technical computing sectors,” said Rob Clyde, CEO, Adaptive Computing, in a press release. “HPC’s powerful engine is at the core of extracting insights from big data, and these updates will enable enterprises to capitalize on HPC’s convergence with cloud and big data to garner faster insights for data-driven decisions.”

Adaptive’s Big Data workflow solution offers scheduling, provisioning and management of application services across HPC, cloud and big data environments. Moab 8.0 supports Big Data’s core services, such as unifying data centre resources, optimizing analysis processes and guaranteeing mission-critical services.

Adaptive Computing breaks down siloed environments to unify data resources with the Moab 8.0 update, allowing users to utilize available resources across platforms, environments and locations. Moab 8.0 enhances resource unification with its OpenStack Integration, a virtual and physical resource provisioning for Information-as-a-Service and Platform-as-a-Service.

Moab 8.0 enables users to achieve improvement in overall workload optimization performance by reducing command latency, decreasing scheduling times, improving multi-threading, faster communication between Moab and TORQUE and a high throughput computing thanks to the Nitro task manager, reducing command latency – a combination of cached data and use of background threads, decreased scheduling cycle time and improved multi-threading.

The latest version of Moab gives end users a 15 to 30 percent energy savings with clock frequency control and power state options. With clock frequency control, administrators can adjust CPU speeds to align with workload processing speeds and administrators can manage multiple power states and automatically place compute nodes in low-power or no-power states (suspend, hibernation and shutdown modes). Moab 8.0 runs data staging in a scheduling out-of-band process to enable improved cluster utilization, multiple transfer methods, new transfer types and more reliable job execution time consistency. In addition, the updates allow Moab to account for data staging in resource scheduling decisions within Grid environments.

Moab hopes that its updates help data centres maintain SLAs, maximize uptime and ensure that services and resources are allocated in an equitable manner. One such update, the graphical user interface known as Moab Viewpoint, monitors and reports on workload and resource utilization.

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