.NET Runtime
vgpu_unlock
.NET Runtime | vgpu_unlock | |
---|---|---|
611 | 144 | |
14,177 | 4,264 | |
1.9% | - | |
10.0 | 0.0 | |
1 day ago | about 1 year 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.
.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
vgpu_unlock
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Tinygrad: Hacked 4090 driver to enable P2P
This isn’t even the first time a hacked driver has been used to unlock some HW feature - https://github.com/DualCoder/vgpu_unlock
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Is there specific hardware to make passthrough GPU easier?
Alternatively enable vGPU for the 2070 and use it for both Jellyfin LXC and Windows VM. https://github.com/DualCoder/vgpu_unlock
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GPU virtualization?
I'm on Linux and I'm running a 3070 Ti (Nvidia). I have always wanted to do GPU virtualization but because NVIDIA won't release vGPU for consumer card no one can do it without crossing legal red tape or problems with bricking your GPU. I did find this [https://github.com/jamesstringerparsec/Easy-GPU-PV] however it is only for windows, I found this [https://github.com/Arc-Compute/LibVF.IO/] and does not work with my GPU, and this [https://github.com/DualCoder/vgpu_unlock] and can't get it to work. Done any one know an alternative on Linux that work just like this, overcoming these problems (on KVM)?
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GPU pass-through/Sharing between multiple VMs
Otherwise, your only other option is the real hardware virtualization options that are available. NVIDIA's enterprise vGPU solution is for expensive compute cards however some have had good luck making vGPUs work on consumer NVIDIA cards with tools such as vgpu_unlock
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SR-IOV with RTX 3090 Ti
There was a hack to enable it on some consumer cards, but it’s not available on Ampere/30x0 cards: https://github.com/DualCoder/vgpu_unlock/issues/8
- Gaming PC for Proxmox
- GPU virtualization, RTX 3000, Nvidia, and KVM?
- Hi, I need help building my VMware home-lab environment
- cheap gpu for virtualization and stable diffusion
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GPU Passthrough
Pci passthrough https://github.com/mbilker/vgpu_unlock-rs https://github.com/DualCoder/vgpu_unlock https://github.com/DualCoder/vgpu_unlock/issues/91 https://gitlab.com/polloloco/vgpu-proxmox https://github.com/joeknock90/Single-GPU-Passthrough https://gitlab.com/YuriAlek/vfio#start-here https://www.reddit.com/r/homelab/comments/b5xpua/the_ultimate_beginners_guide_to_gpu_passthrough/ https://forum.level1techs.com/t/single-gpu-passthrough-with-proxmox/113282/2 https://forum.proxmox.com/threads/problem-with-gpu-passthrough.55918/
What are some alternatives?
Ryujinx - Experimental Nintendo Switch Emulator written in C#
Easy-GPU-PV - A Project dedicated to making GPU Partitioning on Windows easier!
ASP.NET Core - ASP.NET Core is a cross-platform .NET framework for building modern cloud-based web applications on Windows, Mac, or Linux.
nvidia-patch - This patch removes restriction on maximum number of simultaneous NVENC video encoding sessions imposed by Nvidia to consumer-grade GPUs.
actix-web - Actix Web is a powerful, pragmatic, and extremely fast web framework for Rust.
LibVF.IO - A vendor neutral GPU multiplexing tool driven by VFIO & YAML.
WASI - WebAssembly System Interface
OSX-KVM - Run macOS on QEMU/KVM. With OpenCore + Monterey + Ventura + Sonoma support now! Only commercial (paid) support is available now to avoid spammy issues. No Mac system is required.
CoreCLR - CoreCLR is the runtime for .NET Core. It includes the garbage collector, JIT compiler, primitive data types and low-level classes.
vgpu_unlock-rs - Unlock vGPU functionality for consumer grade GPUs
runtimelab - This repo is for experimentation and exploring new ideas that may or may not make it into the main dotnet/runtime repo.
vga-passthrough - Up to date (2021) reference for setting up a VGA passthrough on (Ubuntu) Linux.