About a year and a half ago I posted a few C++ tips on Twitter. Because not all of my blog’s readers are on Twitter and Twitter is not the best medium for archiving things, I decided to write a blog post instead, accumulating all tips in one place.
Additionally, this also allows me to go into more detail where necessary and comment on a few things noted on Twitter.
I will keep updating this post as I add more tips.
Update on 21th Dec 2017: Added tips #5-#7.
The last post of this series basically concluded with the following questions: how do we efficiently allocate memory for individual command packets in the case of multiple threads adding commands to the same bucket? How can we ensure good cache utilization throughout the whole process of storing and submitting command packets?
This is what we are going to tackle today. I want to show how bad allocation behavior for command packets can affect the performance of the whole multi-threaded rendering process, and what our alternatives are.
In the previous part of this series, I’ve talked a bit about how to design the stateless rendering API, but left out a few details. This time, I’m going to cover those details as well as some questions that came up in the comments in the meantime, and even show parts of the current implementation.
Continuing where we left off last time, today I want to present a few ideas about how to design the API that enables us to do stateless rendering.
In this post, I would like to describe what features and performance characteristics I want from a modern rendering system: it should support stateless rendering, rendering in different layers/buckets, and rendering that can run in parallel on as many cores as are available.
Some time ago, I announced that the Molecule Engine uses C++ as a scripting language. Today, I can share implementation details and a few additional tricks that were used to keep compilation times and executable sizes down.
Serialization, reflection, and other mechanisms are often used for saving data in an editor or a tool like the asset pipeline, and then loading that data into the engine at run-time. This process is well-known, flexible, and allows us to store the data in any format conceivable. Still, all those techniques show certain weaknesses when it comes to keeping iteration times to an absolute minimum.