Chapter 18. Memory Efficiency

As Chapter 7 described, the CLR is able to perform automatic memory management thanks to its garbage collector (GC). This comes at a price: when a CPU spends time on garbage collection, that stops it from getting on with more productive work. On laptops and phones, GC work drains power from the battery. In a cloud computing environment where you may be paying for CPU time based on consumption, extra work for the CPU corresponds directly to increased costs. More subtly, on a computer with many cores, spending too much time in the GC can dramatically reduce throughput, because many of the cores may end up blocked, waiting for the GC to complete before they can proceed.

In many cases, these effects will be small enough not to cause visible problems. However, when certain kinds of programs experience heavy load, GC costs can come to dominate the overall execution time. In particular, if you write code that performs relatively simple but highly repetitive processing, GC overhead can have a substantial impact on throughput.

As Microsoft’s ASP.NET Core team worked to improve the performance of their web server framework, in early versions they frequently ran into hard limits due to GC overhead. To enable .NET applications to break through these barriers, C# 7.2 introduced various features that can enable dramatic reductions in the number of allocations. Fewer allocations means fewer blocks of memory for the GC to recover, so this translates directly to lower ...

Get Programming C# 8.0 now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.