Looks like a MinGW-specific issue. In English In Russian. Codeforces c Copyright Mike Mirzayanov. Desktop version, switch to mobile version. User lists. B enq. M iracle R adewoosh. Countries Cities Organizations. Well, it's of course because of safety features in Rust, but can we quantify that? There are only two major differences between the idiomatic Rust and C implementations:.
However, the Rust wrapper objects can be stack-allocated and effectively replace the pointer used by C with a smart pointer, mitigating the locality penalty. The main performance disadvantage is therefore bounds checking. Looking at CPU performance counters while forwarding packets shows interesting results. This table shows relevant performance counters divided by forwarding speed, i. Wow, looks like we should really be asking how Rust manages to be so fast!
Modern superscalar out-of-order CPUs this was run on an Intel Xeon E v3 are really good at hiding these safety checks.
The C code just didn't use the CPU to it's full potential. Thank you so much Mark for putting this forward! There is just so much going behind the scenes for every language that it made it difficult for me to pin down on a common conclusion.
I totally agree with your point that this article does not cover every aspect. When I was researching about this, there was no place where I could practically understand it. So I just took and initiative to make it simple so that beginners like me would get an idea.
Thanks to experienced people like you who can provide us with knowledge that even the internet can't. I'll research on the memory aspect and improve my article. This kind of discussion is very academic. When choosing a language other metrics are more important than how fast the language is.
How fast are the developers producing results in the chosen language? Is my application that time critical? What about: How is your data organized? How is the ecosystem of the product: Databases, caches etc. Whether a language is fast or not is from my POV a nice question for sitting in a pub with a nice drink at hand and having nerd conversations :].
You made it seem so easy. I like the illustrations, too! Would you be willing to write some tutorials for our us? Happy to pay. You can either DM me on twitter at twitter. Some comments have been hidden by the post's author - find out more. Jatin Sharma - Nov Igor Irianto - Nov Because you don't always need to use the and I use this loosely "fastest" language?
I don't drive to work in a Ferrari just because it's faster Their method and process are still fascinating and the conclusions still hold today - and I'm not aware of any better attempt to give an informed answer. They noted that a discussion of potential reasons for differences in performance is hypothetical and futile, and a true discussion must have some empirical basis for the real world impact of such differences.
Afterwards, several iterations of optimizations ensued. This dialogue of titans is exceptionally educational and I whole heartily recommend to dive in - but if you lack the time or patience, Jeff Atwood compiled the bottom lines beautifully :. As Rico sums up :. So am I ashamed by my crushing defeat?
The managed code achieved a very good result for hardly any effort. To defeat the managed version, Raymond had to:. Of course he used available lower level libraries to do this, but that's still a lot of work. Can you call what's left an STL program? I don't think so. That is no coincidence, of course, as these two languages spectacularly achieve their vastly different design goals.
With C , I don't get to handle memory and I have literally tons of resources available for me to do my job. What you need to question yourself is more about which one saves you time. Machines are incredibly powerful now and most of your code should be done in a language that allows you to get the most value in the least amount of time. BTW, time critical applications are not coded in C or Java, primarily due to uncertainty of when the Garbage Collection will be performed.
In modern times, application or execution speed is not as important as was previously. Development schedules, correctness and robustness are higher priorities. A high speed version of an application is no good if it has lots of bugs, crashes a lot or worse, misses an opportunity to get to market or be deployed. Since development schedules are a priority, new languages are coming out that speed up development.
C is one of these. Choose a language that is best suited for the developers, platform and projects. Work towards the goals of correctness, robustness and deployment. The speed of an application should be treated as a bug: prioritize it, compare to other bugs, and fix as necessary. It's called systems programming for a reason, you program against the grain or bare metal. Doing so also grants you speed you cannot achieve with other languages like C or Java. But alas C roots are all about doing things the hard way, so your mostly going to be writing more code and spending more time debugging it.
Example a purple ice cream cone may not be the same as a blue ice cream cone, though they might be cones they may not necessarily belong to the cone family and if you forget to define what cone is you bug out.
Thus the properties of ice cream may or may not be clones. With the boost library you can achieve incredible speeds unfortunately most game studios stick to the standard library. Also take note all operating systems are written in C so generally why must we ask the question what could be faster?! Also caching is not faster than pure memory management, sorry but this just doesn't fan out. Memory is something physical, caching is something software does in order to gain a kick in performance.
One could also reason that without physical memory caching would simply not exist. It doesn't void the fact memory must be managed at some level whether its automated or manual. Getting an exact answer to your question is not really possible unless you perform benchmarks on specific systems. Executing C code requires an additional step where the code is JIT'ed. However, The JIT compiler is able to optimize the generated machine code to closely match the underlying hardware enabling it to take advantage of additional hardware features if they exist.
To my knowledge the. If the memory area used for the first generation is small enough in can stay within the CPU cache increasing performance. Again, this is highly dependent on the application.
A study Python of performance demonstrates that a specific managed Python application is able to scale much better than the compiled version as a result of more optimal memory access patterns.
Basically higher level language has less performance if uses in best case. Many other situations between these situations is possible. For choosing a language you should note the circumstances of the project and its subject.
For a general business project you should use C. If you prefer to get some more info in practice as an expert, see this. It is about Java but it also applies to C. The primary concern would not be speed, but stability across windows versions and upgrades. Win32 is mostly immune across windows versions making it highly stable. When servers are decommissioned and software migrated, A lot of anxiety happens around anything using.
Net and usually a lot of panic about. Cache performance often needs to be considered. A great deal of STL code is re written and often runs many times faster. Maths and code which makes heavy use of data can be re written with spectacular results, as the CPU approaches its optimum performance. None of this is possible in C.
To compare their relative real time performance is really a staggeringly ignorant question. Where each required memory movement works in harmony with the cache. Where the final algorithm cannot be improved, based on the exact real time requirements, considering accuracy and functionality. To compare C with this ideal situation is staggering. In fact, I am currently re writing a whole bunch of C code when I say re writing I mean removing and replacing it completely because it is not even in the same city, let alone ball park when it comes to heavy lifting real time performance.
So please, stop fooling yourselves. C is slow. Dead slow. All software is slowing down, and C is making this speed decline worse.
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