performance

Dynamic collections, such as the dynamic array (also known as a List in C#), are without a doubt one of the most common data structure, and not only in C# but in computer science in general. The dotnet base class library exposes plenty of dynamic collections to fulfil a wide number of usecases: (System.Collections.)List<T>, Dictionary<K, V>, HashSet<T>, Queue<T>, Stack<T>, and more. But they all share one thing in common: they are based on dynamic reallocation of backing arrays, which can lead to suboptimal performance and excessive memory allocation....

In this article I’d like to share my journey learning about caching, and my research on how to make it more efficient. This article is the first in a serie of articles about caching, and here we’ll start by discussing the challenges and memory considerations when doing in-memory caching. This was done as part of my day job as a Staff backend engineer at Equativ, a leading provider of digital advertising solutions, offering a range of products and services to help businesses reach their target audiences and achieve their marketing goals....

While developing GxHash over my spare time during my last parent leave (babies sleep a lot, I swear I’m a good father 😇), I went down the rabbit hole and came up with increasingly low-level optimizations. In this article, I want to talk about one of the nastiest ones, but to whom GxHash is owed to be the fastest non-cryptographic hashing algorithm up to this date. I called this optimization 🥁🥁🥁 “Unsafe Read Beyond of Death” (or URBD)....

Many languages and frameworks have been designed to make developers more productive. This is a good thing, but it has a side effect: it makes developers less aware of the performance implications of their code. While hardware has been getting faster and faster over the years, the place software has taken in our lives has also been growing. In the end, the performance of the code we write is still important, and it’s important to know when to care about it (and when not to)....