jmh
.NET Runtime
jmh | .NET Runtime | |
---|---|---|
26 | 618 | |
2,048 | 14,308 | |
1.6% | 1.5% | |
5.9 | 10.0 | |
3 days ago | 5 days ago | |
Java | C# | |
GNU General Public License v3.0 only | 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.
jmh
- Experimenting with GC-less (heap-less) Java
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Any library you would like to recommend to others as it helps you a lot? For me, mapstruct is one of them. Hopefully I would hear some other nice libraries I never try.
JMH for benchmarks
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Scala collections benchmark - revisited
I would recommend using JMH instead.
- What are some advantages to Java devs learning assembly?
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Is calling a method with reflection slower than calling a method normally? If so, by how much?
Reflection is probably very roughly between 10 and 1000 times slower. Why don't you measure it yourself using JMH?
- I benchmarked kotlin rust and go. The results will shock you , or not.
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Need help navigating the Java ecosystem (coming from C++)
Aleksey Shipilev is another such leader, whom is especially knowledgeable about the internals of the JVM. His writings are invaluable. He is (was) the lead of the Java microbenchmark framework (JMH} which is how one would write small performance experiments in Java, and learn what really makes a difference or now.
- Are Long better than Integer as keys for a Map?
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Threads vs Coroutines - ParallelMap Performance
In the last episode we implemented a parallelMap operation using streams, raw threads, a threadpool with futures, and coroutines. At first glance the raw threads was quickest, followed by futures, coroutines and then streams. In this, part 56 of an exploration of where a Test Driven Development implementation of the Gilded Rose stock control system might take us in Kotlin, we investigate the performance of the different functions further, in particular digging down into why coroutines seem to be slow and finding a way to speed them up. We also find a way to use a particular ForkJoinPool to run the streams code, making it as fast as the others (bar the raw threads). Frankly we only use very rough benchmarks here, with no statistical testing except 'it looks like'. That's OK for gross differences, but is highly suspect when deciding which of two similarly performant approaches is faster. For that check out JMH and you could watch my video from KotlinConf 2017
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Just another way to run JMH benchmark with Eclipse
A few months ago, we started to use JMH in our project to test and find performance issues. The tool provides multiple modes and profilers, and we found this useful for our purposes.
.NET Runtime
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The search for easier safe systems programming
.NET has explicit tailcalls - they are heavily used by and were made for F#.
https://learn.microsoft.com/en-us/dotnet/api/system.reflecti...
https://github.com/dotnet/runtime/blob/main/docs/design/feat...
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Arena-Based Parsers
The description indicates it is not production ready, and is archived at the same time.
If you pull all stops in each respective language, C# will always end up winning at parsing text as it offers C structs, pointers, zero-cost interop, Rust-style struct generics, cross-platform SIMD API and simply has better compiler. You can win back some performance in Go by writing hot parts in Go's ASM dialect at much greater effort for a specific platform.
For example, Go has to resort to this https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f... in order to efficiently scan memory, while in C# you write the following once and it compiles to all supported ISAs with their respective SIMD instructions for a given vector width: https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (there is a lot of code because C# covers much wider range of scenarios and does not accept sacrificing performance in odd lengths and edge cases, which Go does).
Another example is computing CRC32: you have to write ASM for Go https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f..., in C# you simply write standard vectorized routine once https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (its codegen is competitive with hand-intrinsified C++ code).
There is a lot more of this. Performance and low-level primitives to achieve it have been an area of focus of .NET for a long time, so it is disheartening to see one tenth of effort in Go to receive so much spotlight.
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Airline keeps mistaking 101-year-old woman for baby
It's an interesting "time is a circle" problem given that a century only has 100 years and then we loop around again. 2-digit years is convenient for people in many situations but they are very lossy, and horrible for machines.
It reminds me of this breaking change to .Net from last year.[1][2] Maybe AA just needs to update .Net which would pad them out until the 2050's when someone born in the 1950s would be having...exactly the same problem in the article. (It is configurable now so you could just keep pushing it each decade, until it wraps again).
Or they could use 4-digit years.
[1] https://github.com/dotnet/runtime/issues/75148
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The software industry rapidly convergng on 3 languages: Go, Rust, and JavaScript
These can also be passed as arguments to `dotnet publish` if necessary.
Reference:
- https://learn.microsoft.com/en-us/dotnet/core/deploying/nati...
- https://github.com/dotnet/runtime/blob/main/src/coreclr/nati...
- https://github.com/dotnet/runtime/blob/5b4e770daa190ce69f402... (full list of recognized keys for IlcInstructionSet)
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The Performance Impact of C++'s `final` Keyword
Yes, that is true. I'm not sure about JVM implementation details but the reason the comment says "virtual and interface" calls is to outline the difference. Virtual calls in .NET are sufficiently close[0] to virtual calls in C++. Interface calls, however, are coded differently[1].
Also you are correct - virtual calls are not terribly expensive, but they encroach on ever limited* CPU resources like indirect jump and load predictors and, as noted in parent comments, block inlining, which is highly undesirable for small and frequently called methods, particularly when they are in a loop.
* through great effort of our industry to take back whatever performance wins each generation brings with even more abstractions that fail to improve our productivity
[0] https://github.com/dotnet/coreclr/blob/4895a06c/src/vm/amd64...
[1] https://github.com/dotnet/runtime/blob/main/docs/design/core... (mind you, the text was initially written 18 ago, wow)
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Java 23: The New Features Are Officially Announced
If you care about portable SIMD and performance, you may want to save yourself trouble and skip to C# instead, it also has an extensive guide to using it: https://github.com/dotnet/runtime/blob/69110bfdcf5590db1d32c...
CoreLib and many new libraries are using it heavily to match performance of manually intensified C++ code.
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Locally test and validate your Renovate configuration files
DEBUG: packageFiles with updates (repository=local) "config": { "nuget": [ { "deps": [ { "datasource": "nuget", "depType": "nuget", "depName": "Microsoft.Extensions.Hosting", "currentValue": "7.0.0", "updates": [ { "bucket": "non-major", "newVersion": "7.0.1", "newValue": "7.0.1", "releaseTimestamp": "2023-02-14T13:21:52.713Z", "newMajor": 7, "newMinor": 0, "updateType": "patch", "branchName": "renovate/dotnet-monorepo" }, { "bucket": "major", "newVersion": "8.0.0", "newValue": "8.0.0", "releaseTimestamp": "2023-11-14T13:23:17.653Z", "newMajor": 8, "newMinor": 0, "updateType": "major", "branchName": "renovate/major-dotnet-monorepo" } ], "packageName": "Microsoft.Extensions.Hosting", "versioning": "nuget", "warnings": [], "sourceUrl": "https://github.com/dotnet/runtime", "registryUrl": "https://api.nuget.org/v3/index.json", "homepage": "https://dot.net/", "currentVersion": "7.0.0", "isSingleVersion": true, "fixedVersion": "7.0.0" } ], "packageFile": "RenovateDemo.csproj" } ] }
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Chrome Feature: ZSTD Content-Encoding
https://github.com/dotnet/runtime/issues/59591
Support zstd Content-Encoding:
- Writing x86 SIMD using x86inc.asm (2017)
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Why choose async/await over threads?
We might not be that far away already. There is this issue[1] on Github, where Microsoft and the community discuss some significant changes.
There is still a lot of questions unanswered, but initial tests look promising.
Ref: https://github.com/dotnet/runtime/issues/94620
What are some alternatives?
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events [Moved to: https://github.com/async-profiler/async-profiler]
Ryujinx - Experimental Nintendo Switch Emulator written in C#
opentelemetry-java-instrumentation - OpenTelemetry auto-instrumentation and instrumentation libraries for Java
ASP.NET Core - ASP.NET Core is a cross-platform .NET framework for building modern cloud-based web applications on Windows, Mac, or Linux.
OpenJ9 - Eclipse OpenJ9: A Java Virtual Machine for OpenJDK that's optimized for small footprint, fast start-up, and high throughput. Builds on Eclipse OMR (https://github.com/eclipse/omr) and combines with the Extensions for OpenJDK for OpenJ9 repo.
actix-web - Actix Web is a powerful, pragmatic, and extremely fast web framework for Rust.
async-profiler - Sampling CPU and HEAP profiler for Java featuring AsyncGetCallTrace + perf_events
WASI - WebAssembly System Interface
go - The Go programming language
CoreCLR - CoreCLR is the runtime for .NET Core. It includes the garbage collector, JIT compiler, primitive data types and low-level classes.
Arthas - Alibaba Java Diagnostic Tool Arthas/Alibaba Java诊断利器Arthas
vgpu_unlock - Unlock vGPU functionality for consumer grade GPUs.