![]() GetStockPriceWithValueTaskAsync | 1.519 us | 1.09 | - | 0 B |Īs you may see the ValueTask-based version is just a bit faster than the Task-based version. GetPricesDirectlyFromCache | 1.260 us | 0.90 | - | 0 B | Throw new InvalidOperationException($"Can't find price for ' Method | Mean | Scaled | Gen 0 | Allocated | Private decimal DoGetPriceFromCache(string name) Public decimal GetPriceFromCacheFor(string companyId) InitializeMapIfNeededAsync().GetAwaiter().GetResult() Public decimal GetStockPriceFor(string companyId) Public async Task GetStockPriceForAsync(string companyId) ![]() To measure an overhead of async methods will use a slightly modified example that we used in the first blog post. The TPL was designed with this workload in mind but it’s not magic, it has some overhead. But today even relatively simple application could have hundreds if not thousands asynchronous operations per second. Obviously, all of that logic has its own cost, but how much do we pay?īack in pre-TPL days, asynchronous operations usually were fairly coarse-grained so the overhead of an asynchronous operation was likely negligible. But to do that the compiler creates a state machine instance, pass it around to an async method builder, that calls task awaiter etc. ![]() Today we’re going to explore the performance characteristics of async methods.Īs you should already know from the first post of the series, the compiler does a lot of transformations to make asynchronous programming experience very similar to a synchronous one. In the last two blog posts we’ve covered the internals of async methods in C# and then we looked at the extensibility points the C# compiler provides to adjust the behavior of async methods.
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