V8 VS go

https://chromium.googlesource.com/v8/v8.git/+/HEAD/include/c...

Due to the nature of web engine workloads migrating objects to being GC'd isn't performance negative (as most people would expect). With care it can often end up performance positive.

There are a few tricks that Oilpan can apply. Concurrent tracing helps a lot (e.g. instead of incrementing/decrementing refs, you can trace on a different thread), in addition when destructing objects, the destructors typically become trivial meaning the object can just be dropped from memory. Both these free up main thread time. (The tradeoff with concurrent tracing is that you need atomic barriers when assigning pointers which needs care).

This is on top of the safey improvements you gain from being GC'd vs. smart pointers, etc.

One major tradeoff that UAF bugs become more difficult to fix, as you are just accessing objects which "should" be dead.

> If that standard library would be written in JS, a new browser (or rather a new JS engine being a part of the browser) could just use some existing implementation

That sounds great, but I'm doubtful of the simplicity behind this approach.

If my understanding is correct, v8 has transitioned to C++[0] and Torque[1] code to implement the standard library, as opposed to running hard-coded JavaScript on setting up a new context.

I suspect this decision was made as a performance optimization, as there would obviously be a non-zero cost to parsing arbitrary JavaScript. Therefore, I doubt a JavaScript-based standard library would be an acceptable solution here.

[0]: https://github.com/v8/v8/tree/main/src/runtime

C++ lets you write anything you can imagine, and the language features and standard library often facilitate that. The committee espouses the view that they want to provide many "zero [runtime] cost," abstractions. Anybody can contribute to the language, although the committee process is often slow and can be political, each release the surface area and capability of the language gets larger.

I believe Hazard Pointers are slated for C++26, and these will add a form "free later, but not quite garbage collection" to the language. There was a talk this year about using hazard pointers to implement a much faster std::shared_ptr.

It's a language with incredible depth because so many different paradigms have been implemented in it, but also has many pitfalls for new and old users because there are many different ways of solving the same problem.

I feel that in C++, more than any other language, you need to know the actual implementation under the hood to use it effectively. This means knowing not just what the language specifies, but can occaissionally require knowing what GCC or Clang generate on your particular hardware.

Many garbage collected languages are written in or have parts of their implementations in C++. See JS (https://github.com/v8/v8)and Java GC (https://github.com/openjdk/jdk/tree/36de19d4622e38b6c00644b0...)

I am not an expert on Java (or C++), so if someone knows better or can add more please correct me.

Remember that we earlier established that every source gets parsed into an AST at some point before it gets compiled or interpreted. For example, platforms like Nodejs and chromium-based browsers use Gooogle's V8 engine behind the scenes to run JavaScript and of course, some AST parsing is always involved before the interpreter kicks in. I looked V8's source and I discovered it uses its own internal parser to achieve this.

In the source code of the Node.js opensource project, lib folder contains JavaScript code, mostly wrappers over C++ and function definitions. On the contrary, src folder contains C++ implementations of the functions, which pulls dependencies from the V8 project, the libuv project, the zlib project, the llhttp project, and many more - which are all placed at the deps folder.

Here is the implementation of of Array. prototype.map in V8. It's written in a language called Torque which appears to be a special language just for the v8 engine.

It sounds like you want to know how JavaScript is implemented in the browser. The thing is, there is no universal implementation for JavaScript. JavaScript defines a specification that must be adhered to, and then each browser vendor can implement it in whatever way they see fit, as long as it does the specified things. For example (and I'm not saying this is the case) it's entirely possible for Chrome to implement Array.sort() using merge sort, while Firefox implements it as quick sort. You can try to find the source code for the implementation in a certain browser, but that will not be universal. I imagine you can find out how it works in Chrome somewhere in https://chromium.googlesource.com/v8/v8.git, though I'm not sure exactly where.

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.

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.

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

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.

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

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.

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!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.