Adaptive Computing Announces Release of Moab HPC Suite 9.1.2
NAPLES, Fla., February 19, 2018 -- Adaptive Computing announced the release of Moab 9.1.2, an update which has undergone thousands of quality tests and includes scores of customer-requested enhancements.
The RPM bundle contains the following component versions:
• Moab Workload Manager 9.1.2
• Torque Resource Manager 6.1.2
• Moab Accounting Manager 9.1.2
• Moab Web Services 9.1.2
• Moab Insight 9.1.2
• Moab Viewpoint 9.1.2
• Moab Viewpoint Reporting 9.1.2
• Moab Reporting Web Services 9.1.2
• Moab File Manager 9.1.2
• Remote Viz (StarNetFastX2) 2.2-77.3
• RLM 12.1.2
• Nitro 2.1.1
• Nitro Web Services 2.1.1
Some of the features that were added to this release include Cross-Platform, an improved Report Creation Page SQL Editor, a Default Job Script for Remote Visualization Application Template, a Job Template Priority that can be set up per user, the ability to Bypass Memory Utilization Enforcement for Specific Users, and an Optional Separate Client Configuration File.
Moab is a world leader in dynamically optimizing large-scale computing environments. It intelligently places and schedules workloads and adapts resources to optimize application performance, increase system utilization, and achieve organizational objectives.
Moab decision engine is unique in its ability to accelerate and automate both complex IT decisions and processes through multi-dimensional policies. Only Moabcan automate decisions and processes across business priorities and SLAs, current and future time horizons, and heterogeneous physical and virtual resources and management tools, as well as many other dimensions.
About Adaptive Computing
Adaptive Computing manages some of the world’s largest computing installations. Our leadership in IT decision engine software has been recognized with over 45 patents and over a decade of battle-tested performance resulting in a solid Fortune 500 and Top500 supercomputing customer base.
Adaptive Computing’s mission is to bring higher levels of decision, control, and self-optimization to the challenges of deploying and managing large and complex IT environments so they accelerate business performance at a reduced cost.
Source: Adaptive Computing
