The full benchmark gist can be found here, but the important bit is the difference in code to parse each string value: We put this to the test with a benchmark parsing the taxi-fare-train.csv file, a 24MB CSV database from dotnet/machinelearning containing many duplicated text labels. It provides a mechanism that is somewhat similar to string interning, with the main differences being that the pool is configurable, can be reset, is implemented with an automatic replacement policy and doesn’t require to pre-instantiate string objects, so it can save the initial allocations as well when working on temporary buffers. It can be used to minimize allocations when creating multiple string instances from buffers of char or byte values, for instance when parsing text documents with many repeated values, like a CSV database, or when parsing tokens from web requests. The StringPool type implements a fast, thread-safe and configurable pool for string instances, using a least recently used (LRU) caching policy. Since one line of code is worth a thousand words, here is an example of how all these various APIs can be used to perform different operations: All the internal indexing operations are performed using nint values too, so that on 64 bit architectures it is possible to index much larger memory areas than it was before. ![]() NET arrays, the total size is exposed as a nint value. They also do not share the same int.MaxValue limitation as standard BCL types - while the length of each axis is still restricted to int for consistency with. ![]() They include several key features such as offering a flexible abstraction of discontiguous buffers due to their ability to slice 2D memory areas, meaning that each row might not be adjacent to the end of the previous one. The Memory2D and Span2D types are meant to be a natural extension for Memory and Span, but working in 2 dimensions. For instance, a 2D memory area of size 50.000x50.000 will be enough to exceed the int.MaxValue limit. This becomes a particularly noticeable constraint when working in multiple dimensions, as it is easy to exceed the maximum supported value even with individual indices on each axis being relatively small. This is both due to the fact that they lack useful helper methods and indexers to work in two dimensions, and because they inherit some restrictions from other parts of the ecosystem that make them not ideal for working with large underlying buffers, such as the fact that they can only store a length of size int. NET BCL (Base Class Library) that implement a nice abstraction over arbitrary buffers, but they offer no way to properly extend that same level of abstraction to arbitrary 2D memory areas. T he Memory and Span are two widely used types from the. In this blog post I wanted to through some of the new features being included in this new version of the HighPerformance package, explain how they work and how they can be used to help in performance oriented scenarios □ A brief introduction and the official docs are available in the MS docs website. NET 5), that includes a collection of extensions and helper methods that can help when working on performance and memory usage critical applications. ![]() NET 5 support out of the box.Īs a small recap on the HighPerformance package itself: this is a library part of the Windows Community Toolkit and targeting a number of different runtimes and profiles (ranging from. It also includes the second major public release of the package, with a large number of brand new APIs being included, performance improvements and. ![]() NET Conf), bug fixes and lots of changes and improvements also implemented thanks to the amazing support and feedbacks from the whole community. The 7.0 update of the Windows Community Toolkit is finally available, including a huge number of new features (like the new MVVM Toolkit, which we presented at. Windows Community Toolkit - background and logo by.
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