The Settings menu, triggered by a button at the top of the window, brings together some extra features. You click on Optimize Now and within a few seconds, the program has optimized usage, freeing up a little more of this feature so your computer works better. To avoid restarting the machine whenever it happens, Wise Memory Optimizer works to reuse the total amount of RAM on your PC. However, the amount of RAM is limited, ie it is possible that the system will become a little slower after a certain amount of time. RAM well usedĪs you use a computer, more RAM is being used so that various machine features are accessible in a more agile way. A single button is displayed prominently well on the initial screen of the program, which also has an expandable settings menu.
#Wise memory optimizer turn off requests windows#
It also gives some information about this component on your computer, can run along with Windows and dispenses with any installation.įor easy understanding of the information, it displays the total, free, and in-use amount of RAM in a two-color pie chart. It is possible to use some settings so that the program works automatically, optimizing the use of RAM whenever a certain quantity is occupied. You need to give just one click for this to be done within a few seconds. It is important to be aware that all the parameters in the tm1s.cfg file are now dynamic in IBM Planning Analytics, meaning they can be changed with immediate effect.Wise Memory Optimizer is a smart system for optimizing RAM memory that defies the amount of this feature currently used by the PC. It manages all user sandbox commits into a job queue so users don’t wait. JobQueueThreadPoolSize: Job queue is specific for using contributor/application web which uses sandbox by default. JobQueuing: Turns on queuing for Personal Workspace or Sandbox submissions. UseLocalCopiesForPublicDynamicSubsets: Improve performance by not invalidating and causing write lock of the public dynamic subset just the user’s local copy. SubsetElementBreatherCount: Allows lock on subset to be released when there are other requests pending To avoid the first user to wait a bit more, you could set up a chore which ran when the server starts to cache views then this could give users better performance. If a second a user open the same view, it will be faster because the view would have already been cached.
StartupChores: A stargate view is created the first time a user opens the view. LogReleaseLineCount: If admins are doing transaction log queries this stops users getting locked for a long time. MaximumUserSandboxSize: Stop server using excessive memory in case users try to do very large sandbox changes MaximumViewSize: if the view memory when accessing this view reaches the threshold it will abort view construction rather than client waiting forever the view.ĬheckFeedersMaximumCells: if a user tries to check feeders in the cube viewer from cell that is too many cells in the consolidation it will refuse, rather than a very long client hang or eventual crash.
Set to a low number to maximize caching but increase memory. It increases the performance but increases the amount of memory required for a given view.ĬalculationThresholdForStorage: The number of cells needed as minimum before stargate view creation is triggered. ViewConsolidationOptimization enables or disables view consolidation optimization. UseStargateForRules By default when retrieving a calculated cell, the value will be retrieved from a stargate view stored in memory, in some unique instances using a stargate view can be slower than requesting the value from the server, so you can turn off Stargate views for rules by using UseStargateForRules=F. Other parameters which will improve user experienceĪllRuleCalcStargateOptimization can improve performance in calculating views that contain only rule-calculated consolidations. For instance, if your cubes are small and don’t have many rules/feeders it may be more beneficial to leave this off. feeders file and allow TM1 to re-generate the file.Īlthough this is a greater feature, judgment is required on when to use it. Therefore, even if you remove a particular feeder from the rule file it will remain in the. In many cases start-up time can be significantly reduced, examples of a 80-90% reduction are common.įeeders are saved to the. It is best practice to activate persistent feeders if you have large cubes which have an extensive number of fed cells. feeders files and will re-load the feeders for cubes. Upon server startup the tm1 server will reference the. feeders file for each cube that has rules.
When you active persistent feeders, it will create a. Persistent Feeders allows you to improve the loading of cubes with feeders, which will also improve the server start-up time.
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