Difference between revisions of "SPO600 Profiling Lab"
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− | [[Category:SPO600 Labs]]{{Admon/lab|Purpose of this Lab|In this lab, you will do a build of a software package with profiling enabled, execute the program, and analyze the data produced by the profiling system to find potential places for optimization in the software.}} | + | [[Category:SPO600 Labs - Retired]]{{Admon/lab|Purpose of this Lab|In this lab, you will do a build of a software package with profiling enabled, execute the program, and analyze the data produced by the profiling system to find potential places for optimization in the software.}} |
− | + | {{Admon/important|This lab is not a required lab in the current semester of the SPO600 course.|Please refer to the other labs in the [[:Category:SPO600 Labs|SPO600 Labs]] category.}} | |
− | == Lab | + | == Optional Lab == |
=== Prerequisites === | === Prerequisites === |
Latest revision as of 08:33, 4 October 2018
Optional Lab
Prerequisites
- You must have working accounts on the SPO600 Servers or your own Fedora system.
- You must be able to build software.
As a Group
- Set up your pod (see note above).
- Select one of these software packages:
- Apache httpd
- Nginx http server
- Maria DB server
- MySQL server
- Python
- Perl
- PHP
- Or another non-trivial open source software package that does not have a user interface and which processes data, either transforming it (e.g., compression, compiling, editing) or serving network requests.
- Obtain the software (via git or other version control system if necessary, or by downloading the appropriate archive/tarball).
- Do a build with profile generation (
-pg
) enabled -- note that both the compiler and linker will require the-pg
option. You may need to install build dependencies. - Decide what data you're going to use for the profiling run.
- Execute your profiling plan and analyze the results using
gprof
. Record appropriate information about the data processed and the execution environment.
Individual Work
- Complete any of the tasks not completed by the group during the class.
- Analyze the results to find the portions of code that offer the best opportunity for optimization (these may not be the portions that consume the most time). You will probably want to look at the source code for the relevant function.
- Blog the execution environment, your results, your analysis of the results, and your experience doing this lab, including things that you learned and unanswered questions that have come up.
Extra Learning
If you have interest:
- Use another profiling tool to analyze the same software.
- Blog about the results.