Oberon VS FrameworkBenchmarks

> Sure there's a small overhead to smart pointers

Not so small, and it has the potential to significantly speed down an application when not used wisely. Here are e.g. some measurements where the programmer used C++11 and did everything with smart pointers: https://github.com/smarr/are-we-fast-yet/issues/80#issuecomm.... There was a speed down between factor 2 and 10 compared with the C++98 implementation. Also remember that smart pointers create memory leaks when used with circular references, and there is an additional memory allocation involved with each smart pointer.

> Garbage collection has an overhead too of course

The Boehm GC is surprisingly efficient. See e.g. these measurements: https://github.com/rochus-keller/Oberon/blob/master/testcase.... The same benchmark suite as above is compared with different versions of Mono (using the generational GC) and the C code (using Boehm GC) generated with my Oberon compiler. The latter only is 20% slower than the native C++98 version, and still twice as fast as Mono 5.

Great, thanks!

There are books online for free, e.g.

https://people.inf.ethz.ch/wirth/ProgInOberonWR.pdf

and https://ssw.jku.at/Research/Books/Oberon2.pdf

Oberon+ is a superset of Oberon 90 and Oberon-2. Here is more information: https://oberon-lang.github.io/, and here is the current language specification: https://github.com/oberon-lang/specification/blob/master/The.... I already had valuable feedback here on HN concerning the channel extensions. Further research brought me to the conclusion, that Oberon+ should support both, channels and also monitors, because even in Go, the sync package primitives are used twice as much as channels. Mutexes and condition variables can be emulated with channels (I tried my luck here: https://www.quora.com/How-can-we-emulate-mutexes-and-conditi...), but for efficiency reasons I think monitors should be directly supported in the language as well, even if it might collide with the goal of simplicity.

Feel free to comment here or e.g. in https://github.com/rochus-keller/Oberon/discussions/45.

> Does anyone know why Wirth never modernized his style?

Readability. It's easier to read the source code with uppercase keywords. (I think Wirth once said that code is written once but read many times). See this source code - https://raw.githubusercontent.com/rochus-keller/OberonSystem... - to get an idea of this (the uppercase keywords allow you to easily scan the blocks of code). Ofcourse, one can claim that the same can be achieved better today with colour-coded keywords.

If I remember right, the Oberon+ IDE - https://github.com/rochus-keller/Oberon - gives you an option to disable this and use lowercase keywords.

> gain a deep understanding of it .. generate smaller subsets of the system

You can use the OberonViewer for this purpose with the original source code, or the Oberon IDE with a version of the Project Oberon System which runs with SDL on all platforms, see https://github.com/rochus-keller/oberon/#binary-versions and https://github.com/rochus-keller/OberonSystem/tree/FFI

> Regardless, which one is more likely to be ported to a different architecture in the future?

Not sure I understand the question. I'm talking about CPU architectures. The current implementation is in x86 assembler. So if you want to run it on AMD64 or ARM, then you have to replace all assembler files, in the present case probable the full source code.

> what are the comparative performance benchmarks of the low-level language versus the high-level language?

I don't have any measurements. But consider that many operating systems are implemented in C (e.g. Linux) with only isolated parts in assembler, so it is easier to port to other architectures. Linux apparently is fast enough and available for nearly every CPU. Oberon in contrast to C is garbage collected, which also affects performance. I have measurements comparing the same benchmark suite implemented in C++ and in Oberon, where the former is about 22% faster (see https://github.com/rochus-keller/Oberon/blob/master/testcase...).

I actually had a similar problem some years ago and finally moved away from LLVM because of complexity, continuous research effort and performance. My current Oberon+ implementation works like this: the CIL code generator together with Mono is used during development, integrated with the IDE, using the debugging features integrated in Mono; to deploy the application and to gain another factor 2 of performance C99 instead of CIL can be generated and compiled with any compatible toolchain. Here are some performance measurements: https://github.com/rochus-keller/Oberon/blob/master/testcases/Are-we-fast-yet/Are-we-fast-yet_results_linux.pdf. Compiling to CIL is very fast and the time Mono needs to compile and run is barely noticable.

> annoying aspects was requiring the .NET runtime ... OpenJDK is a blessed implementation in a way that Mono never was

Which is unjustified, because Mono CLR is just a single executable less than 5 MB which you can download and run without a complicated installation process (see e.g. https://github.com/rochus-keller/Oberon/#binary-versions ). AOT compilation on the other hand is a huge and complex installation depending on a lot of stuff including LLVM, and the resulting executables are not really smaller than the CLR + mscorlib + app.

Neat. Thanks for sharing!

Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].

[1] https://www.techempower.com/benchmarks/

[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...

ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.

ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.

It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.

If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.

*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources

Although that seems to have improved in recent years.

https://www.techempower.com/benchmarks/#hw=ph&test=json§...

RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.

On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.

https://www.techempower.com/benchmarks

Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.

There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.

And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.

https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...

oh what machine? with how many workers? doing what?

search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21

JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...

In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21

Or, at least, they would be after applying optimizations to them.

In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.