taichi
go
taichi | go | |
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38 | 2,093 | |
24,876 | 120,346 | |
0.5% | 0.6% | |
8.6 | 10.0 | |
10 days ago | 5 days ago | |
C++ | Go | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" 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.
taichi
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This Week In Python
taichi – Productive, portable, and performant GPU programming in Python
- Taichi: Accessible GPU programming, embedded in Python
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The GIL can now be disabled in Python's main branch
ETH Zurich is using it for their physics sim courses, University of Utah is using it for simulations (SIGGRAPH 2022), OPPO (they make smart devices running Android), Kuaishou uses it for liquid and gas simulation on GPUs. Lots of GPU accelerated sim stuff.
https://www.taichi-lang.org/
https://www.researchgate.net/publication/337118128_Taichi_a_...
https://github.com/taichi-dev/taichi
- Julia and Mojo (Modular) Mandelbrot Benchmark
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Taichi v1.5.0 Released! See what's new👇
Check our the realease note (https://github.com/taichi-dev/taichi/releases) for more improvements.
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You Don't Know Jax
I've recently started using Taichi (https://taichi-lang.org/) for numerical codes and the fact it doesn't try to trick you into thinking it's numpy is a nice "feature". ;)
- How can I get into this type of animation with programming?
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Taichi v1.4.0 released!
Taichi v1.4.0 is released! See what's new: - Taichi AOT, along with a native Taichi Runtime library: Native applications can now load compiled AOT modules and launch Taichi kernels without a Python interpreter. - Taichi ndarray: An array object that holds contiguous multi-dimensional data to allow easy data exchange with external libraries. - Dynamic index: Use variable indices whenever necessary on all backends without affecting the performance of those matrices with only constant indices. See deprecation and more improvements in the release note.
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Is Nvidia CUDA Used in VFX Software Tools?
Oh, then if you're not already tied to any particular VFX software, I might as well recommend Taichi again.
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Marching squares algorithm implemented with Taichi: Struct Taichi fields and dynamic SNodes are used to represent line segments, and linear interpolation applied to smoothen the boundaries.
It's an upgrade of a basic version. See changes to the source code here: https://github.com/taichi-dev/taichi/pull/6851
go
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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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Go: the future encoding/json/v2 module
A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.
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Evolving the Go Standard Library with math/rand/v2
I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles
The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397
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Microsoft Maintains Go Fork for FIPS 140-2 Support
There used to be the GO FIPS branch :
https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...
But it looks dead.
And it looks like https://github.com/golang-fips/go as well.
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Borgo is a statically typed language that compiles to Go
I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:
- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644
- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412
Here are some excerpts from the latest Go survey [1]:
- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."
- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."
I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.
[1]: https://go.dev/blog/survey2024-h1-results
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.
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How to use Retrieval Augmented Generation (RAG) for Go applications
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!
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From Homemade HTTP Router to New ServeMux
net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements
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Building a Playful File Locker with GoFr
Make sure you have Go installed https://go.dev/.
- Fastest way to get IPv4 address from string
What are some alternatives?
Halide - a language for fast, portable data-parallel computation
v - Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies. Supports automatic C => V translation. https://vlang.io
dolfinx - Next generation FEniCS problem solving environment
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
Data-Science-For-Beginners - 10 Weeks, 20 Lessons, Data Science for All!
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
difftaichi - 10 differentiable physical simulators built with Taichi differentiable programming (DiffTaichi, ICLR 2020)
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
open-im-server - IM Chat
Angular - Deliver web apps with confidence 🚀
copilot.vim - Neovim plugin for GitHub Copilot
golang-developer-roadmap - Roadmap to becoming a Go developer in 2020