We're hiring!
*

Implementing a performance boosting algorithm in Coccinelle

Jaskaran Singh avatar

Jaskaran Singh
January 21, 2021

Share this post:

Last year, from June to September, I worked on the kernel development tool Coccinelle under Collabora. I implemented a performance boosting algorithm for one of Coccinelle's use cases. Here's a look at this work.

What is Coccinelle?

Coccinelle is a tool used to refactor C source code. It's used for development in the Linux Kernel. You write an abstract patch (called a Semantic patch in Coccinelle terms), basically to remove a few lines of code and add some, to make a tree-wide change.

Coccinelle uses the semantic patch language for this purpose. Following is a basic example of a semantic patch:

@@
expression E;
constant c;
type T;
@@

-kzalloc(c * sizeof(T), E)
+kcalloc(c, sizeof(T), E)

When applied to the tree, the above semantic patch replaces every instance of kzalloc with kcalloc.

For more information, check out this page.

How it works

On the inside, Coccinelle has a semantic patch parser and a C parser. When fed a semantic patch and a C file, Coccinelle parses the semantic patch to create an AST, and parses the C file to create an AST as well.

Following this, it compares the semantic patch AST with the C AST. If matches are found, the changes detailed in the semantic patch are made to the C file.

Implementing the algorithm

During my work on Coccinelle, I implemented a performance boosting algorithm to speed up recursive parsing of header files in the Linux Kernel.

Coccinelle has an option to parse included header files recursively to figure out types of certain C constructs such as struct fields and typedefs. This is necessary in some cases, as Coccinelle can only look at one C file at a time.

Initially, this recursive parsing would take close to 7 hours for the entire Linux Kernel. Since the target userbase of Coccinelle is kernel developers, 7 hours wasn't a very good benchmark.

Implementation of the performance boosting algorithm resulted in that time coming down to 45 minutes. For the curious, following is the algorithm:

  • While parsing a C file, Parse its included header files recursively. Parse each header file only once.
  • While parsing a header file, figure out types of relevant C constructs (struct fields, typedefs) and store the names of each in a cache. Map a name to the file its declared in and the type associated to the name.
  • While parsing a header file, create a dependency graph to figure out what header file is reachable from which C file.
  • When parsing a C file, and encountering a variable with an unknown type:
    • Lookup the name cache for the variable.
    • Determine reachability of the header file that variable is declared in using the dependency graph.
    • Grab the type of the reachable file's variable.

Result

The algorithm isn't perfect, as it still takes 45 minutes to get everything done. There's a lot more that could be done, like leveraging multiprocessing (a whole other can of worms), or conditionally parsing the files based on the semantic patch's matches. However, it works relatively fine on a moderately fast PC.

Thank you Collabora for financially supporting this project!

Comments (0)


Add a Comment






Allowed tags: <b><i><br>Add a new comment:


Search the newsroom

Latest Blog Posts

Adding VP9 and MPEG2 stateless support in v4l2codecs for GStreamer

23/06/2021

Earlier this year, from January to April 2021, I worked on adding support for stateless decoders for GStreamer as part of a multimedia internship…

Bag of Freebies for XR Hand Tracking: Machine Learning & OpenXR

17/06/2021

In our previous post, we presented a project backed by INVEST-AI which introduces a multi-stage neural network-based solution. Now let's…

Testing cameras with lc-compliance on KernelCI

15/06/2021

Initiated as a joint effort by the Google Chrome OS team and Collabora, the recent KernelCI hackfest brought the addition of new tests including…

Zink: Summer 2021 update

14/06/2021

There's a lot that has happened in the world of Zink since my last update, so let's see if I can bring you up to date on the most important…

Open Source OpenGL ES 3.1 on Mali GPUs with Panfrost

11/06/2021

Panfrost, the open source driver for Arm Mali, now supports OpenGL ES 3.1 on both Midgard (Mali T760 and newer) and Bifrost (Mali G31, G52,…

Optimizing 3D performance with virglrenderer

17/05/2021

Collabora has been investing into Perfetto to enable driver authors & users to get deep insights into driver internals and GPU performance.…

Open Since 2005 logo

We use cookies on this website to ensure that you get the best experience. By continuing to use this website you are consenting to the use of these cookies. To find out more please follow this link.

Collabora Ltd © 2005-2021. All rights reserved. Privacy Notice. Sitemap.

Collabora Limited is registered in England and Wales. Company Registration number: 5513718. Registered office: The Platinum Building, St John's Innovation Park, Cambridge, CB4 0DS, United Kingdom. VAT number: 874 1630 19.