[PREVIEW-WIP] PERF: Improve startup time by 8% with lazy loading of wrapped libraries - #509
[PREVIEW-WIP] PERF: Improve startup time by 8% with lazy loading of wrapped libraries#509jcfr wants to merge 1 commit into
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*** WORK IN PROGRESS: For now, you have to make sure SlicerApp-real and Slicer launcher are built to ensure the successful generation of the json files *** Startup time reduced from 3.8s to 3.5s with a "cold cache" and from 2.7s to 2.38s with a "warm cache". For each logic/mrml/dm/widgets python modules, a json files listing the associated attributes is generated. Then, when the application is initialized, the "slicer" module is created as a "lazy" module with the attributes associated with logic/mrml/dm/widgets set as "not loaded". Finally, as soon as an attribute not yet loaded is accessed, the specialized __getattribute__ loads the associated python module and update the module dictionary. The "lazy" module has been adapted from "itkLazy.py" Results have been gathered on Ubuntu 15.10 on a workstation with the following specs: 64GB / M.2 PCIe NVMe SSD / Quad Core 3.80GHz
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Note: Timing performance obtained after applying the fixes associated with #508 |
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Today on the tcon it would help if we could discuss how to run these On Tue, May 31, 2016 at 3:30 AM, Jean-Christophe Fillion-Robin <
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*** WORK IN PROGRESS: For now, you have to make sure SlicerApp-real and
Slicer launcher are built to ensure the successful generation of the json
files ***
Startup time reduced from 3.8s to 3.5s with a "cold cache"
and from 2.7s to 2.38s with a "warm cache".
For each logic/mrml/dm/widgets python modules, a json files listing
the associated attributes is generated. Then, when the application is
initialized, the "slicer" module is created as a "lazy" module with
the attributes associated with logic/mrml/dm/widgets set as "not loaded".
Finally, as soon as an attribute not yet loaded is accessed, the specialized
__getattribute__loads the associated python module and update the moduledictionary.
The "lazy" module has been adapted from "itkLazy.py"
Results have been gathered on Ubuntu 15.10 on a workstation with the
following specs: 64GB / M.2 PCIe NVMe SSD / Quad Core 3.80GHz