On a multicore box, the java thread schedulers decisions are rather arbitrary, it assigns thread priorities based on when the thread was created, from which thread it was created etc.
The idea is to run a tuning process using pso that would randomly set thread priorities and then eventually reach optimal priorities where the fitness function is the total run time of the program?
Of course there would be more parameters, like the priorities would shift during the run to find an optimal priority function.
How practical, interesting does the idea sound? and any suggestions. Just some background, ive been programming in java/c/c++ for a few years now with various projects, another alternative would be making a thread scheduler based on this in c, where the default thread scheduler is the OS.
Your approach as described is a static approach, i.e. you need to run the program several times, then come up with a scheduling solution, then ship your scheduling information with the program.
The problem is that for most non-trivial programs, their performance will partly depend on the specific data they're working with. Even if you find an optimal way to schedule threads for one data set, there is absolutely no guarantee that it will improve speed on another one. In most cases, running what will be a long and arduous optimization every time they want to do a new release will not be worth it for devs, unless perhaps for large computation efforts (where the programs are likely to be manually tuned and not written in java anyway).
I'd say a self-learning thread scheduler is a nice idea, but you can't treat it as a classical optimization problem here. You either need to be sure that your scheduling order will remain optimal (unlikely) or find an optimization method that works at runtime. And the issue here might be that it wouldn't take much for the overhead of your scheduler to destroy any performance gain you might get.
I think this is a somewhat subjective question, but overall no, don't think it would work.
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