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Tuesday, November 21, 2017
Floating Point Benchmark: Julia Language Added
I have posted a new edition of the floating point benchmark collection which adds the Julia language. Julia is a language intended for numerical computation in science and engineering. It combines aspects of object orientation, functional programming, and conventional imperative languages. It has a dynamic type system, automatic storage management with garbage collection, macros, and support for parallel processing in both the single instruction multiple data (SIMD) and symmetrical multiprocessing paradigms. An extensive mathematical function library is included, and support for complex numbers, multiple precision integers and floating point, and vector and matrix algebra are built in. An interactive evaluator is provided, and programs are compiled into machine code with a just in time (JIT) compiler based upon the LLVM compiler infrastructure. Implementation of the benchmark was straightforward, and based upon the C++ version. Some restructuring was required because Julia does not provide the class and method mechanism of C++, nor does it allow passing pointers as function arguments. As with all ports of the benchmark, I tried to do things in the style of the language. This means I adopted a style much like that of the Haskell and Scala benchmarks, using a trace context to manage the state as a ray is traced through the surfaces of the design. The transitSurface() function, which accounts for the bulk of the benchmark's run time, takes a TraceContext as an argument and returns a TraceContext updated to reflect the propagation of the ray through the current surface. This means on each call to the function a new TraceContext is allocated and one discarded to be cleaned up by garbage collection. You might think this overhead could be reduced by replacing the dynamically allocated TraceContext with global mutable variables, but that makes things dramatically worse. The program fbench_static.jl uses static variables as the original C and Fortran versions do, and runs almost four and a half times slower than fbench.jl. I did some preliminary timing tests to try different compiler options, none of which seemed to make much difference in run time. I ran the timing tests with code compiled with the “-O2 --check-bounds=no” options. The latter suppresses array bound checking. After initial runs to determine an iteration count resulting in a run time of around five minutes, I ran five timing tests. Julia's @time macro was used to time the inner loop. For an iteration count of 110,327,622, the mean time of of five runs on an idle system was 295.681 seconds, or 2.68 microseconds per iteration. My runs of the reference C benchmark on GCC 5.4.0 had a mean time of 296.536 seconds for 166,051,660 iterations, or 1.7858 microseconds per iteration. Thus, for this benchmark, the run time for Julia was 1.501 times longer than that of C or, equivalently, Julia was 50% slower than C. Download floating point benchmark collection| Language | Relative Time |
Details |
|---|---|---|
| C | 1 | GCC 3.2.3 -O3, Linux |
| JavaScript | 0.372 0.424 1.334 1.378 1.386 1.495 |
Mozilla Firefox 55.0.2, Linux Safari 11.0, MacOS X Brave 0.18.36, Linux Google Chrome 61.0.3163.91, Linux Chromium 60.0.3112.113, Linux Node.js v6.11.3, Linux |
| Chapel | 0.528 0.0314 |
Chapel 1.16.0, -fast, Linux Parallel, 64 threads |
| Visual Basic .NET | 0.866 | All optimisations, Windows XP |
| C++ | 0.939 0.964 31.00 189.7 499.9 |
G++ 5.4.0, -O3,
Linux, double long double (80 bit) __float128 (128 bit) MPFR (128 bit) MPFR (512 bit) |
| FORTRAN | 1.008 | GNU Fortran (g77) 3.2.3 -O3, Linux |
| Pascal | 1.027 1.077 |
Free Pascal 2.2.0 -O3, Linux GNU Pascal 2.1 (GCC 2.95.2) -O3, Linux |
| Swift | 1.054 | Swift 3.0.1, -O, Linux |
| Rust | 1.077 | Rust 0.13.0, --release, Linux |
| Java | 1.121 | Sun JDK 1.5.0_04-b05, Linux |
| Visual Basic 6 | 1.132 | All optimisations, Windows XP |
| Haskell | 1.223 | GHC 7.4.1-O2 -funbox-strict-fields, Linux |
| Scala | 1.263 | Scala 2.12.3, OpenJDK 9, Linux |
| FreeBASIC | 1.306 | FreeBASIC 1.05.0, Linux |
| Ada | 1.401 | GNAT/GCC 3.4.4 -O3, Linux |
| Go | 1.481 | Go version go1.1.1 linux/amd64, Linux |
| Julia | 1.501 | Julia version 0.6.1 64-bit -O2 --check-bounds=no, Linux |
| Simula | 2.099 | GNU Cim 5.1, GCC 4.8.1 -O2, Linux |
| Lua | 2.515 22.7 |
LuaJIT 2.0.3, Linux Lua 5.2.3, Linux |
| Python | 2.633 30.0 |
PyPy 2.2.1 (Python 2.7.3), Linux Python 2.7.6, Linux |
| Erlang | 3.663 9.335 |
Erlang/OTP 17, emulator 6.0, HiPE [native, {hipe, [o3]}] Byte code (BEAM), Linux |
| ALGOL 60 | 3.951 | MARST 2.7, GCC 4.8.1 -O3, Linux |
| PL/I | 5.667 | Iron Spring PL/I 0.9.9b beta, Linux |
| Lisp | 7.41 19.8 |
GNU Common Lisp 2.6.7, Compiled, Linux GNU Common Lisp 2.6.7, Interpreted |
| Smalltalk | 7.59 | GNU Smalltalk 2.3.5, Linux |
| Ruby | 7.832 | Ruby 2.4.2p198, Linux |
| Forth | 9.92 | Gforth 0.7.0, Linux |
| Prolog | 11.72 5.747 |
SWI-Prolog 7.6.0-rc2, Linux GNU Prolog 1.4.4, Linux, (limited iterations) |
| COBOL | 12.5 46.3 |
Micro Focus Visual COBOL 2010, Windows 7 Fixed decimal instead of computational-2 |
| Algol 68 | 15.2 | Algol 68 Genie 2.4.1 -O3, Linux |
| Perl | 23.6 | Perl v5.8.0, Linux |
| BASICA/GW-BASIC | 53.42 | Bas 2.4, Linux |
| QBasic | 148.3 | MS-DOS QBasic 1.1, Windows XP Console |
| Mathematica | 391.6 | Mathematica 10.3.1.0, Raspberry Pi 3, Raspbian |
Posted at November 21, 2017 22:35