CrispyWaffle
NetFabric.Hyperlinq
CrispyWaffle | NetFabric.Hyperlinq | |
---|---|---|
1 | 4 | |
16 | 860 | |
- | 0.2% | |
9.3 | 0.0 | |
10 days ago | 3 months ago | |
C# | C# | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CrispyWaffle
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Last Week of Hacktoberfest
I kicked off my Hacktoberfest contributions by diving into CrispyWaffle, a project that caught my attention due to its importance in the .NET ecosystem. The maintainers had an open issue #211, which required assistance in removing a retry check within one of their classes. After discussing the changes and receiving their initial approval, they encouraged me to seek additional areas for improvement within the codebase. Eager to make a positive impact, I accepted the challenge.
NetFabric.Hyperlinq
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Classes vs. Structs in .NET. How not to teach about performance
> AVX instructions, which is implemented for quite a few LINQ methods
Are you sure? Any examples of such methods? And does AVX actually helps?
I don’t think that’s possible because IMO AVX and other SIMD can only help for dense inputs. The C# type is ReadOnlySpan, however ReadOnlySpan doesn’t implement IEnumerable and therefore incompatible with LINQ.
There’s even an alternative LINQ to workaround https://github.com/NetFabric/NetFabric.Hyperlinq but that thing is a third-party library most people aren’t using.
- Like Regular LINQ, but Faster and Without Allocations: Is It Possible?
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700,000 lines of code, 20 years, and one developer: How Dwarf Fortress is built
I know it C# it doesn't have to make heap allocations, here's a Linq-clone that mostly eliminates them: https://github.com/NetFabric/NetFabric.Hyperlinq
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Array iteration performance in C# — Branching and Parallelization
I'm the developer of one of the libraries and you may find in the benchmarks that it performs better than most others.
What are some alternatives?
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