LINQ’s CPU performance is quite poor, but how is it with memory? Does every LINQ function always create tons of garbage for the GC to collect, or are there exceptions that aren’t so bad? Today’s article tests out lots of LINQ functions to find out!
Posts Tagged performance
It’s been over three years since the last article on LINQ performance. That was all the way back in the Unity 5.0 days using Mono as a scripting backend. Today we’ll update that article’s test with Unity 2018.1 and IL2CPP to see how LINQ fares these days. Is it any better? Read on to find out!
A lot of powerful language features like LINQ require massive performance hits, but today we’ll discuss some easy, low-overhead ways to add some safety and usability to C#.
Writing multi-threaded code is one of the keys to maximizing performance. Currently, this means creating your own threads and synchronizing them with C# keywords like lock and volatile as well as .NET classes like [ThreadStatic] and Interlocked. Today we’ll take a look at how these are implemented behind the scenes by IL2CPP to get some understanding of what we’re really telling the computer to do when we use them.
C# has some powerful features like fixed-size buffers, pointers, and unmanaged local variable arrays courtesy of stackalloc. These are deemed “unsafe” since they all deal with unmanaged memory. We should know what we’re ultimately instructing the CPU to execute when we use these features, so today we’ll take a look at the C++ output from IL2CPP and the assembly output from the C++ compiler to find out just that.
Unity’s GC is a continual thorn in our sides. We’re constantly working around it by pooling objects, limiting use of language features, and avoiding APIs. We even call GC.Collect on load screens in the hopes that the GC won’t run during gameplay. Today’s article goes one step further and shows how to disable the GC completely so there’s zero chance it’ll run. We’ll also see how to turn it back on when we’re ready for it again.
There are many permutations of loops we can write, but what do they compile to? We should know the consequences of using an array versus a List<T>, for versus foreach, caching Length, and other factors. So today’s article dives into the C++ code that IL2CPP outputs when we write these various types of loops to examine the differences. We’ll even go further and look at the ARM assembly that the C++ compiles to and really find out how much overhead our choices are costing us.
This week we continue to look at the C++ that IL2CPP outputs for C# to get a better understanding of what our C# is really doing. Today we’ll look at how abstract methods work, whether casting of sealed classes is faster than non-sealed classes, and what happens when creating a delegate.
Today we continue looking at the C++ that IL2CPP generates for our C# code by calling various types of functions and using boxing and unboxing. Just how much performance overhead do these entail? Read on to find out!
The last time we looked at performance was way back in part four of the series. Ever since then we’ve been relentlessly adding more and more features to the C++ scripting system. So today we’ll take a break from feature additions to improve the system’s performance in a couple of key areas.
