In today’s post, we will finally take a look at the last remaining piece of the new job system: adding dependencies between jobs.
Continuing from where we left off last time, today we are going to discuss how to build high-level algorithms such as parallel_for using our job system.
This week, we will finally tackle the heart of the job system: the implementation of the lock-free work-stealing queue. Read on for a foray into low-level programming.
As promised in the last post, today we will be looking at how to get rid of new and delete when allocating jobs in our job system. Allocations can be dealt with in a much more efficient way, as long as we are willing to sacrifice some memory for that. The resulting performance improvement is huge, and certainly worth it..
Back in 2012, I wrote about the task scheduler implementation in Molecule. Three years have passed since then, and now it’s time to give the old system a long deserved lifting.
Even though a task scheduler can help with alleviating the burden of having to distribute small pieces of work to different threads, it cannot help preventing a few issues common in multi-threaded programming, especially in multi-processor environments.
Continuing from where we left off last time, this post explains how parent-child relationships are handled inside the task scheduler, and how streaming tasks can be split automatically by the scheduler.