[tptacek]

I've been following this whole business card raytracer story and wonder if people might be missing the forest for the trees.

It would be a little nutty to suggest that Golang 1.1 is going to give optimized C code a run for its money. Nobody could seriously be suggesting that.

What is surprising is that the naive expression of an "interesting" compute-bound program in both languages are as close as they are.

Most C/C++ code --- the overwhelming majority, in fact --- is not especially performance sensitive. It often happens to have performance and memory footprint demands that exceed the capabilities of naive Python, but that fit squarely into the capabilities of naive C.

The expectation of many C programmers, myself included, is that there'd still be marked difference between Go and C for this kind of code. But it appears that there may not be.

This doesn't suggest that I'd want to try to fit Golang into a kernel module and write a driver with it, but it does further suggest that maybe I'd be a little silly to write my next "must be faster than Python" program in C.

[npalli]

That's interesting. I had the opposite reaction regarding Golang capabilities while following this saga. Not sure how 'idiomatic' the Golang code is, at first glance it just seems less expressive (more lines of code) than either c++ or java!. I didn't think that was possible.

So whenever people talk about expressiveness of Golang it just seems like a design gone bad. The designers wanted a programming language with the expressiveness of python and the speed of C, they ended up with a language with the expressiveness of C and the speed of python.

[pbsd]

I agree, I honestly don't see where the expressiveness claims of Go come from. I've always put it in the Java-like bin of languages (which is not necessarily a bad thing).

I suppose the one thing that Go does well (compared to C++ or Java) is builtin concurrency and communication across tasks.

[tptacek]

My first impression of it was that it was like a cross between Java and Python. It is unmistakably similar to Java conceptually and syntactically; they are sibling languages, both designed to streamline, simplify, or modernize C.

I'm a Java-literate C/C++ programmer. I would avoid writing straight Java code at all costs; I find it immiserating. Here are some reasons off the top of my head that Golang is more pleasant to work in:

* The syntax is deliberately streamlined, including implicit declarations, semicolon insertion, lightweight expression syntax, the capital-letter-exports-a-symbol thing

* It has fully functional idiomatic closures

* Interfaces get rid of adapter class BS

* The table type (maps, in Golang) is baked into the language, like Python, not a library, like C++ and Java

* Clearer, more direct control over memory layout; data structures in Golang feel like C

I don't know if Golang's standard library is that much better than Java's, but it was obviously designed carefully by and for systems programmers, so I find it remarkably easy to work with.

It also feels like a much smaller system than Java. Almost every time I write a significant amount of Golang code, I find myself answering questions by just reading the standard library source code. It's easy to get your head around. I've written compiler/runtime-level code for the JVM and I still don't have a great grip on all of Java.

[georgemcbay]

I agree with all of the above and I write Java code for a living currently (Android/Dalvik though, not for the JVM).

Another cool aspect of the last point (Go being small and lightweight) is that if you've got gcc and mercurial on a supported platform, building latest go from source is as easy as:

hg clone http://code.google.com/p.go cd go/src ./make.bash

Got to build a local copy of the JVM and/or JDK for some reason? Good luck with that (even ignoring all the licensing, OpenJDK vs closed, etc)

[lmm]

Have you compared it with ML or Haskell?

[RamiK]

Brevity and expressiveness are not the same.

[yohanatan]

Are you sure about that? Given that any [Turing-complete] language feature can be implemented in any other [Turing-complete] language, the only conceivable difference is in fact length of implementation.

In other words, it is possible to express anything in one Turing-complete language that is possible to express in another.

[hetman]

Except my brain isn't a Turing machine. What expressiveness means then is how easily I can fit the concepts of the code in my head (not on my harddrive). This is not the same as how short the code is, though the two are often closely related.

[yohanatan]

Expressiveness is power and it applies to the act of writing code, not reading it. I agree that it is ideal if one's code can be read and comprehended easily by others although that has little to do with expressiveness.

http://www.paulgraham.com/power.html

[cgag]

To me, expressiveness is about expressing an idea with as little incidental complexity as possible, which is definitely different from as in as few characters as possible.

[yohanatan]

I don't think it is different actually. 'Kolmogorov complexity' (which is essentially the global minimum 'essential complexity' of a particular algorithm) is specified in terms of length.

[kvb]

See Felleisen's "On the Expressive Power of Programming Languages"[1] for one formalization that differs from conciseness. Essentially, Turing complete languages can express the same programs at the very coarse "whole program" level, but the paper advocates taking a more local view to assess expressiveness (e.g. what programs in L1 can you write in L2 without having to do a whole program transformation). See also Neal Gafter's related commentary[2] (in the context of the various proposals for closures in Java).

[1] http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.4...

[2] http://gafter.blogspot.com/2007/03/on-expressive-power-of-pr...

[yohanatan]

One doesn't have to look far before he finds a fatal flaw in the commentary. Particularly this:

"In my mind, a language construct is expressive if it enables you to write (and use) an API that can't be written (and used) without the construct." - Neil Gafter

Once more, there is no such construct. All APIs can be written and consumed without language support. Otherwise, Boost would not have had all the new C++ goodies (as an add-on library) before they became part of the language itself. And, of course, one can always put the 'human compiler' to work to produce boilerplate that would be produced by the compiler if the language in question supported the feature in question (if there isn't an add-on library providing the feature in question). One can always do this but the discriminating one tries to avoid it and instead chooses 'expressive' (i.e., conciseness-facilitating) languages. [In the case of closures in Java, one [human-compiler] would merely use one-off interfaces or anonymous classes].

I will take a look at the other links but I gave up on the commentary after seeing such a blatant falsehood.

[cmccabe]

Are you sure about that?

Yes.

[yohanatan]

You can be sure if you want but unless you back up your claim with some reasoning, others will consider you wrong.

[charlieflowers]

He gets points for brevity. You gotta admit that :)

[cgag]

I'm not sure if it's because the JVM has a bad rep or people like the familiar feeling of Go (smaller learning curve) or some other reason, but it surprises me so many people jump to Go for performance similar to what you'd get on a modern JVM language (Clojure, Scala), but with less expressiveness, fewer libraries, and (I believe) less tooling.

Of course this only really applies to long running apps (web servers), if startup time matters then certainly Go wins.

Perhaps I need to try Go out, but I just don't see what the selling point is.

[fauigerzigerk]

People are trying to get as much space as possible between themselves and the Java community's culture of complexity. I don't think it's a technology issue.

[adamc]

"the Java community's culture of complexity" -- great evocative phrase.

[pjmlp]

s/Java/Enterprise/g

[azth]

> but it surprises me so many people jump to Go for performance similar to what you'd get on a modern JVM language

In a word: hype. If Go did not have the Google brand name attached to it, it wouldn't have gone anywhere.

[kkowalczyk]

You're empirically wrong.

I actually did write a fair amount of Go code (my primary languages are C++ and Python).

On real, non-toy programs it is significantly more concise than C++, in the ballpark of Python code.

This isn't visible on code snippets (less than 500 loc) like the toy raytracer, but trust me: you'll see a big difference on 10k loc codebase.

[m0th87]

I've just wrapped up a go program that's not a toy, albeit not as large as 10k - it's a little over 3k. It was not nearly as terse as python, although the performance increases made it well worth it. This is something that surely varies a great deal from one application to another.

[npalli]

Without knowing what your program did, it is hard to see what language features caused the difference. In any case, why was Java not a better option than Golang?

[TylerE]

Go outputs a statically linked binary that just RUNS. Java needs a quite heavyweight runtime to be installed, that imposes quite a bit of startup overhead. That's just one reason - for short runtime CLI-type utilities it's not in the same ballpark.

[npalli]

Ok, so lets go with your use case. You can run basic java ("hello world") under 3MB with a startup time of about 0.1 second. So that is the true overhead if you really care about tight code. The default values are pretty large. Everything else (memory/startup) is added due to external libraries that are needed and additional memory as the program grows.

Given that "kkowalczyk" talked about 10K line programs, what applications are you thinking of that are 10K lines and cannot tolerate a 0.1 second/3 MB overhead. Would you restart java everytime? Note that even a simple helloworld c program has about 0.01second/0.5MB overhead.

[m0th87]

I was going to say there's no way java programs boot in 0.1 seconds, but looked it up to be sure. Here's the results on my mac/i7, defaulted to server mode:

    $ time java HelloWorld
    Hello, world!

    real	0m0.101s

Touche. 0.1 seconds is exactly right, at least on my setup. That said, javac is slow given the program is 5 lines of code:

    $ time javac HelloWorld.java 

    real	0m0.511s
    user	0m0.833s
    sys	0m0.050s

And I'd ventured to guess that there must be something to the JIT being pretty slow for real-world applications, otherwise people wouldn't complain so frequently about it. Maybe aspects of JIT optimizations increase linearly-ish with the amount/complexity of code?

FWIW, we went with go at my work instead of java because our application is memory-intensive, and there's huge gains there in go over java.

[tptacek]

You are off by two orders of magnitude in the C case, at least with my trivial test case of writing hello world, and then a runner program that forks/execs/waitpids 10,000 times.

If you know what crt0.c does, you can see C is also pretty much the asymptote of what you're going to get from program startup, so it's a little silly to make the comparison.

[eliasmacpherson]

Is that with the JVM already running or not?

[pjmlp]

> Java needs a quite heavyweight runtime to be installed, that imposes quite a bit of startup overhead.

One can always use one of the commercial native compilers for Java, any of them can easily produce static binaries with fast startup times.

Don't measure Java the language, by Oracle JVM the implementation.

[myg204]

A lot of the verbosity in Go comes from error handling; the language forces you to deal with errors (I think it's a good thing, some may disagree). Expressiveness is real, 'duck typing' does give it a feel of scripting language like Python, and it is way less verbose than Java (apart from error handling). And to be fair, Go is faster than Python (the numbers tell you that), and (slightly?) more expressive than C --and just in a league of its own for concurrency.

[azth]

> and just in a league of its own for concurrency.

Not really. Other languages are far superior in this regard (see Scala or Rust for instance).

[nly]

I think the reason both versions lack conciseness is because they're faithful translations of one another. I wouldn't call either well structured, but maybe that's because I don't understand the problem domain well enough. T() in the C++ versions especially looks awful.

[corresation]

To concur with what kkowalczyk, there is little expressiveness advantages to be gained for this specific example -- math is math, and outside of compressing it down to a couple of library calls, what could possibly be done better?

"they ended up with a language with the expressiveness of C and the speed of python."

This is just pure troll. Apparently you have a Python variant of this renderer that matches the already impressive Go performance? Please reveal it.

[plorkyeran]

> It would be a little nutty to suggest that Golang 1.1 is going to give optimized C code a run for its money. Nobody could seriously be suggesting that.

AFAICT, the entire situation started only because the article was submitted to /r/Golang and /r/C++ with the trollbait title "Business Card Ray Tracer: Go faster than C++", and not because of anything in the article itself (which was actually a pretty good article).

[noelwelsh]

Ray-tracing, especially the simple kind in this example, is all about vector maths. CPUs are extremely good at this type of task. Finding Go performs well at this shouldn't be surprising. Any decent compiler will be able to produce good code for this task as it maps very closely to what CPUs do best, meaning you don't need much fancy analysis.

I think the majority of languages in popular use are faster than Python. I believe that Go is popular with the Python / Ruby crowd because idiomatic Go is quite close to what they do already. I.e. you don't need to learn much to shift from Python or Ruby to Go. Using a language like Scala, for instance, is a much bigger jump.

[kid0m4n]

Actually, looking deeply at Go from a performance perspective (as I have been, the last couple of days) has revealed a bunch of low hanging fruits/missed optimization opportunities in the Go compiler. That was 50 % the intent of the grand father blog post

[packetslave]

Sure, there's plenty of work still to be done. Go 1.0 is only 18 months old, with 1.1 only 6 months old.

C++ has 30 years of history behind it, MS VC++ is 20 years old, Intel's C++ compiler is at least 10 years old, etc.

[corresation]

Finding Go performs well at this shouldn't be surprising.

Go doesn't do SIMD at all (see note 1). Personally I leverage Go coupled with the Intel Compiler (Go happily links with and uses very high performance C-built libraries, where I'm rocking out with SSE3 / AVX / AVX2).

To respond to something that Ptacek said above, many of us do expect Go to achieve C-level performance eventually. There is nothing stopping the Go compiler from using SIMD and automatic vectorization, it just doesn't yet. There is nothing about the language that prohibits it from a very high level of optimization, and indeed the language is generally sparse in a manner that allows for those optimizations.

*1 - For performance critical code you are supposed to use gccgo, which uses the same intermediary as the C compiler, allowing it to do all of the vectorization and the like. Unfortunately for this specific code gccgo generates terrible code, yielding a runtime that is magnitudes slower (albeit absolutely tiny). Haven't looked into why that is.

[pcwalton]

> There is nothing stopping the Go compiler from using SIMD and automatic vectorization, it just doesn't yet.

Those optimizations would almost certainly reduce the speed of the Go compiler (requiring SSA form and aliasing info).

> There is nothing about the language that prohibits it from a very high level of optimization, indeed the language is generally sparse in a manner that allows for those optimizations.

Autovectorization is very sensitive to good output from alias analysis. This is where the const and restrict keywords in C, absent in Go, are useful. I think you will at least need runtime guards in Go, whereas they are not necessary in well-written C.

[noelwelsh]

My understanding is that automatic vectorization is still quite sensitive to how code is written. The compiler may fail to vectorize one implementation of an algorithm, while vectorize another, due to details in the implementation of both the code and the compiler.

My point is not about vectorization though. Code that uses mostly vectors, math, and function calls has a very direct translation to machine code. I expect all compilers to generate approximately the same machine code for this type of code, assuming vectorization doesn't come into play. So I don't expect to see large differences in performance. Of course there will be some difference, but not the order of magnitude one sees between compiled (statically or JITed) languages and interpreted languages.

[sampo]

> assuming vectorization doesn't come into play.

Now that 256 bit AVX registers that process 4 numbers in one go, even when one uses 64bit floats (and 8 with 32bit floats), vectorization more and more comes into play.

Using 64bit floats with 128bit SSE registers, it was kinda possible to ignore the vectorization, as it was less than 2x speedup. But no more.

[hrjet]

"There is nothing stopping the Go compiler from using SIMD and automatic vectorization, it just doesn't yet. "

A JVM could compile byte code to SIMD instructions. Most of them don't, yet.

[cdtwigg]

Auto-vectorization is impossible for a lot of real-world code because it requires changing how data is laid out in memory. Notice that the AVX version of the raytracer actually involves packing blocks of x components into a single 256-bit-wide variable. Realistically, a compiler is not going to be smart enough to figure that out.

[corresation]

Absolutely true, though of course you could do the same memory layout with the Go code. If we're talking about compiler comparisons, a vectorization-suitable tighter inner loop that operates on contiguous memory would be a good high performance comparison. The standard Go compiler would not vectorize it...yet...though honestly I don't know what the state of gccgo is or whether it yields an intermediary that brings the gcc vectorization into play.

And of course the reason you code for auto-vectorization is for ease of platform support. The linked AVX code will not run on the vast majority of virtual machines, or any CPU made prior to 2012. Nor will it take advantage of AVX2. I use the Intel compiler and either yield builds that I can target to specific processors or technology levels or I can add support for virtually all technologies, such that the same code will vectorize on AVX2, failing that AVX, failing that SSE3.2, failing that... you get the picture. With a suitable ARM compiler the same code would vectorize to NEON, etc.

[samth]

There have been languages in this space for a very long time. Pascal and Algol 68 are both very old examples (see the Go vs Brand X comparison). Then there's Modula or Oberon not quite as long ago. In the last 20 years, everything from Java to OCaml to Scala to C# to F# to Haskell to Common Lisp to Lua have been developed.

So it's not especially interesting that Go is in this space as well. The most surprising thing about Go is that its developers seem never to have heard of any of the above languages (with the exception of Java).

[tptacek]

I don't think it's interesting that Go has this combination of attributes. I think it's interesting that the "right" boring systems programming language got a degree of tooling and traction sufficient to make it, unlike Modula and Oberon, a viable mainstream choice.

I am fine with boring languages. The first language love of my life is C. It's hard to get more boring than C. If a system I build is going to be clever or sophisticated, I'm fine with that being expressed in my code, rather than as the product of the environment I happen to be working in.

[Teckla]

It's hard to get more boring than C.

C... boring? I don't think so. Not with 200+ undefined or implementation defined behaviors. Not when even something as simple as "a = b + c" can evoke nasal demons.

C is so loosely defined that it keeps you on your toes constantly. Every single line is like walking down a dark corridor with poisonous snakes... and your torch just guttered out.

There's nothing boring about C. It's pure thrill and danger. If you're not experiencing that, you're probably writing terribly non-portable, brittle code, ready to unexpectedly invoke undefined or implementation defined behavior.

[samth]

First, Go isn't a systems programming language, any more than Java is.

Second, C is _far_ from boring. It's boring now because we all live in its shadow, but the idea that we should have high-level languages for writing low-level software in? That's C, right there.

Lots of other languages that now seem boring were interesting to start (Java, Perl, ...). What's frustrating about Go, and the hype it gets, is that it isn't interesting in any of those ways, and yet so many people, including its designers, seem to think it's revolutionary.

[pjmlp]

Seems to be pretty much similar to Oberon, used to build a few OS.

https://news.ycombinator.com/item?id=6498878

As you should be aware, since you mentioned Oberon.

[pjmlp]

Only because it has Google as the Goodfather, otherwise no one would care about Go.

[frozenport]

I don't think its nutty at all. Ideally the language shouldn't be tied to performance - the compiler and optimizer will do it. His method of optimization hints that the compiler is still immature.

From another angle, consider that in HPC FORTRAN codes will often get the best performance - and FORTRAN doesn't have real pointers.

[bluecalm]

C++ code is 5x faster after some standard optimizations so it's not really the same league. Faster than Python for sure but still unusable for anything CPU bound is the message I get from all of this.

This doesn't show anything new though, programming math/graphics is perfect use for C/C++ and you won't really benefit from anything Go has to offer and some of its features actually become annoyance for this kind of application. The biggest strength of of Go doesn't really really shine either as simple parallelism needed for ray tracer is matter of few lines of code in both C and C++.

[corresation]

C++ code is 5x faster after some standard optimizations

There is nothing standard about the optimizations -- direct AVX use is enormously uncommon, even among extremely high performance code.

[abelsson]

I'll grant you that - AVX is pretty uncommon. I originally wrote it with SSE2 (there's a working version in the next to last commit on the github repo), but rewrote it using AVX because.. well, I hadn't used it before.

But I wouldn't say writing media and signal processing inner loops using SIMD intrinsics is uncommon. The style of optimization I illustrate is pretty common, perhaps minus the AVX code path. Most widely used video/image processing, ray tracing and other compute bound libraries will probably be SIMD optimized in some fashion (probably with different code paths for different processors). You gain 1-8x performance, which is pretty significant. It's on the same order of magnitude speedup as threading your program.

I have yet to see anyone truly and systematically trusting automatic vectorization, but perhaps there are libs out there I've missed. Anyone know of some?

[a_e_k]

Hi there, speaking of autovectorization, I actually tried it on this last night. After seeing kid0man's post, I decided to try optimizing it and selected that same loop as my target. (When I wrote the original C++ program, I was favoring conciseness and portability over performance, naturally.)

I made many of the same transformations as you did: switching the object's data to a structure of arrays, splitting out the computation of the normal from the loop, etc. (even an int hit = -1.) My goal was to coax Intel's compiler into autovectorizing that loop, without directly using vector intrinsics. I succeeded, but the result turned out to be noticeably slower than just compiling kid0man's with -fast. Part of that, I suspect is that it generated suboptimal code for the reduction over the minimum, where a human programmer would have used a movemask as you did.

That said, I'm fairly curious to experiment with seeing how it would perform with the kernel compiled via ispc [1].

Regarding direct use of SIMD intrinsics in inner loops, I have to agree with you that it's still reasonably common for this type of thing. I've certainly done it before in ray tracing contexts [2], and I've seen many others do it as well, e.g. [3] and [4]. Autovectorization and things like Intel's array notation extension [5] seem to be getting better all the time, but I don't think it's generally as performant yet as direct use of intrinsics. In the cases where it is, it usually seems to have taken a fair amount of coaxing and prodding.

[1] http://ispc.github.io/

[2] http://www.cs.utah.edu/~aek/research/triangle.pdf

[3] https://github.com/embree/embree

[4] http://visual-computing.intel-research.net/publications/pape...

[5] http://software.intel.com/en-us/blogs/2010/09/03/simd-parall...

[abelsson]

As an intermediate step, before starting with the SSE intrinsics I rewrote the code in a form that should have been reasonably suitable for an autovectorizer (an inner loop over a fixed number of elements - I imagine it probably looked fairly similar to your code), but my gcc with -ftree-vectorize didn't do much with it. I didn't really explore that path further though.

I actually did a version which did the reduction over minimum purely using SIMD and then a post step which reduced the SIMD minimums to a single scalar. It was somewhat tricky to get the index right, and in the end it turned out to not be faster (at least not for the little example of 32 objects, I imagine you would gain something on a more complex scene)

Anyway, it was a fun little exercise and it has sparked some interesting discussion. Thanks for posting the original.

[corresation]

But I wouldn't say writing media and signal processing inner loops using SIMD intrinsics is uncommon.

But at that point this has nothing to do with Go or C++, and I find this whole discussion rather disingenuous (at first I thought you were detailing the maturity of C(++) compilers and their superior support of auto-vectorization, which would be a reasonable angle): You can import the Intel math libraries and call them from Go (I know, as I do it regularly. See my submissions).

[abelsson]

No, it doesn't. I tried to make that point too, but perhaps it didn't come across very clearly. For these kind of tight inner loops a language only ever gets in the way, the difference is really only how difficult it is to get rid of the conveniences you don't want. (The much vaunted zero-cost of features you don't use in C++ lingo I guess)

I still think that a systems programming language need to offer escape hatches, whilst striving towards ease of use in the common case. C++ has plenty of hatches, at the cost of horrific complexity.

But suppose I'm willing to pay the cost of writing my code in 5 different code paths for different processors for that extra 2-4x of performance. Very few languages offer that possibility, and most of those who do only offer to call a C library. I'm the guy stuck writing the Intel math libraries of the world, and I want something more reasonable to do it in.

[cmccabe]

The point that corresation is making is that none of the optimizations you did had anything to do with C++. You could have easily done them for the Go version, but you didn't. Then you put up a chart and said "this is why C++ is better." Huh?

[pjmlp]

Funny, where in the ANSI C++ standard is the entry for AVX/SSE2?