Unity 2018.3 brings us even more thread-safe APIs that we can call from the C# job system. Today we’ll look at a systematic way to find them all so we know what’s safe to use and what’s not.
Today we conclude the series by looking at all the remaining features in C# 7.3 that we get access to in Unity 2018.3. Read on to learn about new kinds of structs,
in parameters, new
where constraints, discards,
default literals, generalized
async returns, and new preprocessor symbols!
Continuing the series, today we’ll dive into local functions,
fixed blocks on arbitrary types with
stackalloc initializers to see how they’re all implemented in C++ and what assembly code ends up actually running on the CPU.
Unity 2018.3 officially launched last Thursday and with it comes support for the very latest version of C#: 7.3. This includes four new versions—7.0, 7.1, 7.2, and 7.3—so it’s a big upgrade from the C# 6 that we’ve had since 2018.1. Today we’ll begin an article series to learn what happens when we use some of the new features with IL2CPP. We’ll look at the C++ it outputs and even what the C++ compiles to so we know what the CPU will end up executing. Specifically, we’ll focus on the new tuples feature and talk about creating, naming, deconstructing, and comparing them.
Some errors can be handled and some cannot. Nevertheless, it’s extremely common to see codebases chock-full of ineffective error handling for these unrecoverable issues. The result is a lot of extra code to write, maintain, and test that often serves to make debugging harder. Today’s article shows you how to make debugging internal errors so much easier by effectively writing code to handle them.
Native collections are funny things. On one hand they’re structs, which are supposed to be value types that get copied on assignment. On the other hand, they act like reference types because they contain a hidden pointer internally. This can make using and implementing them difficult to understand, especially in the context of a ParallelFor job. Today we’ll examine more closely how to properly support ParallelFor jobs, especially with ranged containers like
Last week we looked at a new native collection type:
NativeChunkedList<T>. This type saved us a lot of memory and gave us a faster way to dynamically grow an array. Unfortunately, iterating over it was quite a lot slower. Today we’ll speed it up for both
IJobParallelFor. In doing so, we’ll learn more about how to create custom Unity job types and about how
Today’s article is about a new native collection type: NativeChunkedList<T>. This type is great when you need a dynamically-resizable array that’s fast to add to and doesn’t waste a lot of memory. Read on to see how it’s implemented, see the performance report, and get the source code.