Programming language ray tracing benchmarks project

[kenhwang]

Ordered by realtime, fastest to slowest for those like me who got annoyed by the scrolling up and down trying to compare:

  Rust (1.13.0-nightly)         1m32.392s
  Nim (0.14.2)                  1m53.320s
  C                             1m59.116s
  Julia (0.4.6)                 2m01.166s
  Crystal (0.18.7)              2m01.735s
  C Double Precision            2m26.546s
  Java (1.7.0_111)              2m36.949s
  Nim Double Precision (0.14.2) 3m19.547s
  OCaml                         3m59.597s
  Go 1.6                        6m44.151s
  node.js (6.2.1)               7m59.041s
  node.js (5.7.1)               8m49.170s
  C#                           12m18.463s
  PyPy                         14m02.406s
  Lisp                         24m43.216s
  Haskell                      26m34.955s
  Elixir                      123m59.025s
  Elixir MP                   138m48.241s
  Luajit                      225m58.621s
  Python                      348m35.965s
  Lua                         611m38.925s

[weberc2]

I rewrote the Go benchmark to be a mechanical translation of C and it performs much better.

    C        (gcc -O3):       23.8s
    Julia    (julia 1.1.0):   32.8s
    Go (alt) (go 1.12):       39.3s
    Java     (java 1.8.0_60): 44.2s
    Go (org) (go 1.12):       64.8s
    OCaml    (ocaml 4.07.1):  79.1s
    JS       (node 11.14.0):  137.0s
    Pypy     (pypy 6.0.0):    139.4s
    C#       (mono 4.2.1):    187.3s

    Rust: DOES NOT COMPILE

So Go is only twice as slow as C, not thrice as slow. This puts it just ahead of Java and just behind Julia.

[z92]

Julia was astonishing. It's a high level language that's performing almost like C.

Last time I checked, many years back, the spec was changing and the run time did crash. Guess it has gone a long way since.

The other one is Lua. My assumption was that it's one of the lightest and fastest language around. Looks like "fastest" isn't true in some cases.

[weberc2]

That's a big jump between OCaml and Go. I'm not familiar with ray tracing, but skimming the source code it mostly looks like it's doing floating point math; it doesn't look like it's using the runtime (no allocations, no virtual function calls, no scheduling, etc), so I'm surprised that Go is performing relatively poorly.

I wonder if the performance gap is attributable to some overhead in Go's function calls? I know Go passes parameters on the stack instead of via registers... Maybe it's due to passing struct copies instead of references (looks like the C version passes references)? Generally poor code generation?

Anyone else have ideas or care to profile?

EDIT: From my 2015 MBP, Go (version 1.12) is indeed quite a lot slower than C, but only if you're doing an optimized build `-03`:

    tmp $  time ./gorb
    real    1m15.128s
    user    1m9.366s
    sys     0m6.754s

    tmp $  clang crb.c
    tmp $  time ./a.out
    real    1m13.041s
    user    1m10.284s
    sys     0m0.624s

    tmp $  gcc crb.c -o crb -std=c11 -O3 -lm -D_XOPEN_SOURCE=600
    tmp $  time ./crb
    real    0m22.703s
    user    0m22.550s
    sys     0m0.073s

    tmp $  clang crb.c -o crb -std=c11 -O3 -lm -D_XOPEN_SOURCE=600
    tmp $  time ./crb
    real    0m22.689s
    user    0m22.564s
    sys     0m0.060s

EDIT2: I re-modified the Go version (https://gist.github.com/weberc2/2aed4f8d3189d09067d564448367...) to pass references and that seems to put it on par with C (or I mistranslated, which is also likely):

    $ time ./gorb 
    real    0m19.282s
    user    0m14.467s
    sys     0m7.523s

[Shish2k]

Python gets 20% faster if you use `__slots__` on the Vector class which is created and destroyed millions of times. It's still the second-slowest, but it's a nice improvement :P

[krull10]

I wouldn’t give much weight to those benchmark numbers at this point. Some of those language versions are quite out of date...

[Someone]

This times performance like this:

  $ time ./crb

That means time spent writing the .ppm file is included.

In the implementations I browsed, that is about a million print calls, each of which might flush the output buffer, and whose performance may depend on locale.

To benchmark ray tracing I would, instead, just output the sum of the pixel values, or set the exit code depending on that value.

Even though ray tracing is cpu intensive, it also wouldn’t completely surprise me if some of the implementations in less mature languages spent significant time writing that output because their programmers haven’t come around to optimizing such code.

[weberc2]

The Go version spends 8 seconds writing data. This is probably par for the course for most implementations.

[piinbinary]

The haskell version can be made >= 3x faster by making the computations non-lazy, e.g.

    -data Vector3 = Vector3 {vx::Float, vy::Float, vz::Float} deriving (Show)
    +data Vector3 = Vector3 {vx :: !Float, vy :: !Float, vz :: !Float} deriving (Show)

[niofis]

This seems like a nice improvement, could you send a PR for it?

[kyberias]

I don't think the C# time is representative. I suspect Mono is really slow here. I just ran it with VS 2015 in 1 min 24 sec.

[mikece]

If I'm not mistaken, Miguel himself said that Mono was meant for portability (can run on Linux) and not performance. Would be a far better test to use .NET Core as you could still run this test on Linux or any other place where Core runs.

[ygra]

For some workloads Mono seems awfully slow. The compiler I'm maintaining at work takes about twice as long on Mono on Windows and about four times as long as Mono on Linux compared to NET. I guess NET Core would be comparable or faster than .NET Framework and similar on both platforms.

[alkonaut]

The C# implementation looks flawed (uses reference types for vectors etc). Using value types and .NET Core should give a much better result than that. Will try to remember doing a PR.

[ilitirit]

Interesting that Nim is slightly faster than C it considering that it compiles down to C.

[Lerc]

That's possibly because of the "Code must follow best practices" restriction.

Oftentimes compile to C is "It's C Jim, but not as we know it"

You can write C as if it is a SSA VM or similar intermediate representation that leaves very little work for the first stages of the compiler.

[kev6168]

I am surprised PyPy has such a huge lead over Python.

    $ time python pyrb.py 

    real    348m35.965s
    user    345m51.776s
    sys     0m22.880s

    $ time pypy pyrb.py

    real    14m2.406s
    user    13m55.292s
    sys     0m1.416s

[X6S1x6Okd1st]

Raytracing is a pretty great place to apply pypy, you have a very heavy loop that will hit the JIT.

I've certainly seen speedups like that on stuff like project euler code.

[FartyMcFarter]

10-100x speedup seems normal for CPython vs well compiled code. I don't have experience with PyPy though, so in this specific case I'm not sure.

[fnord77]

> rustc 1.13.0-nightly

what's an ancient version of rust. Interesting it is faster than C, though.

[Lerc]

To be fair, The README.md seems to be three years old.

It would actually be quite interesting to see a comparison with all of the languages using more recent builds to see which ones are developing their performance.

[niofis]

Yeah, I've meant to update it and add more language implementations, but haven't really got the time. Might as well do so soon as almost all compilers/interpreters have new versions which I suspect have many nice optimizations.

[mratsim]

Nim 0.14 is also from more than 3 years ago.

[JoshuaScript]

You should see a performance boost in the Haskell implementation by compiling with GHC's LLVM backend[0]. Another Haskell ray tracer ran 30 % faster than the native codegen this way[1].

[0]https://gitlab.haskell.org/ghc/ghc/wikis/commentary/compiler...

[1]http://blog.llvm.org/2010/05/glasgow-haskell-compiler-and-ll...

[azhenley]

This is awesome! More good press for Nim.

There is a big variation in performance, some of which I find surprising. Do you know what exactly causes some languages to be so slow (e.g., small objects being created and garbage collected frequently)?

[niofis]

Did some testing and found that it boils down to three things: RNG algorithm used in the standard library, forced use of double precision floating point numbers (the case for OCaml and javascript), and like you mentioned, memory management.

EDIT: forgot to mention the obvious things: compiler/interpreter maturity and inherent overhead.

[technological]

Wonder how would D lang would have been placed

[xiphias2]

Looking at the Julia implementation fast math wasn't used. In my experience it's usually worth experimenting with turning it on (also of course for the other LLVM based languages), though I understand that this benchmark tries to keep the program correct at all costs.

[stevelosh]

I looked over the Common Lisp version at https://github.com/niofis/raybench/blob/master/lisprb.lisp and it's… really bad, in a lot of ways.

    (declaim (optimize (speed 3) (safety 0) (space 0) (debug 0) (compilation-speed 0)))

Never use `(optimize (safety 0))` in SBCL — it throws safety completely out the window. We're talking C-levels of safety at that point. Buffer overruns, the works. It might buy you 10-20% speed, but it's not worth it. Lisp responsibly, use `(safety 1)`.

    (defconstant WIDTH 1280)

People generally name constants in CL with +plus-muffs+. Naming them as uppercase doesn't help because the reader uppercases symbol names by default when it reads. So `(defconstant WIDTH ...)` means you can no longer have a variable named `width` (in the same package).

    (defstruct (vec
                 (:conc-name v-)
                 (:constructor v-new (x y z))
                 (:type (vector float)))
      x y z)

Using `:type (vector float)` here is trying to make things faster, but failing. The type designator `float` covers all kinds of floats, e.g. both `single-float`s and `double-float`s in SBCL. So all SBCL knows is that the struct contains some kind of float, and it can't really do much with that information. This means all the vector math functions below have to fall back to generic arithmetic, which is extremely slow. SBCL even warns you about this when it's compiling, thanks to the `(optimize (speed 3))` declaration, but I guess they ignored or didn't understand those warnings.

    (defconstant ZERO (v-new 0.0 0.0 0.0))

This will cause problems because if it's ever evaluated more than once it'll try to redefine the constant to a new `vec` instance, which will not be `eql` to the old one. Use `alexandria:define-constant` or just make it a global variable.

All the vector math functions are slow because they have no useful type information to work with:

    (disassemble 'v-add)
    ; disassembly for V-ADD
    ; Size: 160 bytes. Origin: #x52D799AF
    ; 9AF:       488B45F8         MOV RAX, [RBP-8]                ; no-arg-parsing entry point
    ; 9B3:       488B5001         MOV RDX, [RAX+1]
    ; 9B7:       488B45F0         MOV RAX, [RBP-16]
    ; 9BB:       488B7801         MOV RDI, [RAX+1]
    ; 9BF:       FF1425A8001052   CALL QWORD PTR [#x521000A8]     ; GENERIC-+
    ; 9C6:       488955E8         MOV [RBP-24], RDX
    ; 9CA:       488B45F8         MOV RAX, [RBP-8]
    ; 9CE:       488B5009         MOV RDX, [RAX+9]
    ; 9D2:       488B45F0         MOV RAX, [RBP-16]
    ; 9D6:       488B7809         MOV RDI, [RAX+9]
    ; 9DA:       FF1425A8001052   CALL QWORD PTR [#x521000A8]     ; GENERIC-+
    ; 9E1:       488BDA           MOV RBX, RDX
    ; 9E4:       488B45F8         MOV RAX, [RBP-8]
    ; 9E8:       488B5011         MOV RDX, [RAX+17]
    ; 9EC:       488B45F0         MOV RAX, [RBP-16]
    ; 9F0:       488B7811         MOV RDI, [RAX+17]
    ; 9F4:       48895DE0         MOV [RBP-32], RBX
    ; 9F8:       FF1425A8001052   CALL QWORD PTR [#x521000A8]     ; GENERIC-+
    ; 9FF:       488B5DE0         MOV RBX, [RBP-32]
    ; A03:       49896D40         MOV [R13+64], RBP               ; thread.pseudo-atomic-bits
    ; A07:       498B4520         MOV RAX, [R13+32]               ; thread.alloc-region
    ; A0B:       4C8D5830         LEA R11, [RAX+48]
    ; A0F:       4D3B5D28         CMP R11, [R13+40]
    ; A13:       772E             JNBE L2
    ; A15:       4D895D20         MOV [R13+32], R11               ; thread.alloc-region
    ; A19: L0:   C600D9           MOV BYTE PTR [RAX], -39
    ; A1C:       C6400806         MOV BYTE PTR [RAX+8], 6
    ; A20:       0C0F             OR AL, 15
    ; A22:       49316D40         XOR [R13+64], RBP               ; thread.pseudo-atomic-bits
    ; A26:       7402             JEQ L1
    ; A28:       CC09             BREAK 9                         ; pending interrupt trap
    ; A2A: L1:   488B4DE8         MOV RCX, [RBP-24]
    ; A2E:       48894801         MOV [RAX+1], RCX
    ; A32:       48895809         MOV [RAX+9], RBX
    ; A36:       48895011         MOV [RAX+17], RDX
    ; A3A:       488BD0           MOV RDX, RAX
    ; A3D:       488BE5           MOV RSP, RBP
    ; A40:       F8               CLC
    ; A41:       5D               POP RBP
    ; A42:       C3               RET
    ; A43: L2:   6A30             PUSH 48
    ; A45:       FF142520001052   CALL QWORD PTR [#x52100020]     ; ALLOC-TRAMP
    ; A4C:       58               POP RAX
    ; A4D:       EBCA             JMP L0

If they had done the type declarations correctly, it would look more like this:

    ; disassembly for V-ADD
    ; Size: 122 bytes. Origin: #x52C33A78
    ; 78:       F30F104A05       MOVSS XMM1, [RDX+5]              ; no-arg-parsing entry point
    ; 7D:       F30F105F05       MOVSS XMM3, [RDI+5]
    ; 82:       F30F58D9         ADDSS XMM3, XMM1
    ; 86:       F30F104A0D       MOVSS XMM1, [RDX+13]
    ; 8B:       F30F10670D       MOVSS XMM4, [RDI+13]
    ; 90:       F30F58E1         ADDSS XMM4, XMM1
    ; 94:       F30F104A15       MOVSS XMM1, [RDX+21]
    ; 99:       F30F105715       MOVSS XMM2, [RDI+21]
    ; 9E:       F30F58D1         ADDSS XMM2, XMM1
    ; A2:       49896D40         MOV [R13+64], RBP                ; thread.pseudo-atomic-bits
    ; A6:       498B4520         MOV RAX, [R13+32]                ; thread.alloc-region
    ; AA:       4C8D5820         LEA R11, [RAX+32]
    ; AE:       4D3B5D28         CMP R11, [R13+40]
    ; B2:       7734             JNBE L2
    ; B4:       4D895D20         MOV [R13+32], R11                ; thread.alloc-region
    ; B8: L0:   66C7005903       MOV WORD PTR [RAX], 857
    ; BD:       0C03             OR AL, 3
    ; BF:       49316D40         XOR [R13+64], RBP                ; thread.pseudo-atomic-bits
    ; C3:       7402             JEQ L1
    ; C5:       CC09             BREAK 9                          ; pending interrupt trap
    ; C7: L1:   C7400103024F50   MOV DWORD PTR [RAX+1], #x504F0203  ; #<SB-KERNEL:LAYOUT for VEC {504F0203}>
    ; CE:       F30F115805       MOVSS [RAX+5], XMM3
    ; D3:       F30F11600D       MOVSS [RAX+13], XMM4
    ; D8:       F30F115015       MOVSS [RAX+21], XMM2
    ; DD:       488BD0           MOV RDX, RAX
    ; E0:       488BE5           MOV RSP, RBP
    ; E3:       F8               CLC
    ; E4:       5D               POP RBP
    ; E5:       C3               RET
    ; E6:       CC0F             BREAK 15                         ; Invalid argument count trap
    ; E8: L2:   6A20             PUSH 32
    ; EA:       E8F1C64CFF       CALL #x521001E0                  ; ALLOC-TRAMP
    ; EF:       58               POP RAX
    ; F0:       EBC6             JMP L0

The weirdness continues:

    (defstruct (ray
                 (:conc-name ray-)
                 (:constructor ray-new (origin direction))
                 (:type vector))
      origin direction)

The `:conc-name ray-` is useless, that's the default conc-name. And again with the `:type vector`… just make it a normal struct. I was going to guess that they were doing it so they could use vector literals to specify the objects, but then why are they bothering to define a BOA constructor here? And the slots are untyped, which, if you're looking for speed, is not doing you any favors.

I took a few minutes over lunch to add some type declarations to the slots and important functions, inlined the math, cleaned up the broken indentation and naming issues:

https://gist.github.com/sjl/005f27274adacd12ea2fc7f0b7200b80...

The old version runs in 5m12s on my laptop, the new version runs in 58s. So if we unscientifically extrapolate that to their 24m time, it puts it somewhere around 5m in their list. This matches what I usually see from SBCL: for numeric-heavy code generic arithmetic is very slow, and some judicious use of type declarations can get you to within ~5-10x of C. Getting more improvements beyond that can require really bonkers stuff that often isn't worth it.

[armitron]

I did some quick changes to your code (inlining, stack allocating) and got a further ~2x speedup which makes SBCL performance equivalent to Julia.

[PorterDuff]

It would be interesting to take that C version and hammer on it a bit for speed.

...and then add SIMD.

[omaranto]

The results are more or less in line with what I would have expected, except for SBCL and Luajit, which I would have expected to be much faster.

[armitron]

The Lisp code is terrible performance-wise and written by someone who obviously doesn't know Common Lisp very well.

Look at Steve Losh's comment here for something a lot better. My own (further) improvements put SBCL performance in the same order as Julia.

[iainmerrick]

The most impressive result here is Lua -- not far behind C! LuaJIT is amazing.

Good to see a few languages like Nim and Rust actually beating C for raw performance, too.

[wlesieutre]

Am I reading it wrong or did LuaJIT take 113x as long as C?

[Narishma]

You should look again. Lua seems to be the slowest of the bunch.

[Mac2125]

Sarcasm?