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http://julialang.org/
从这个语言的主页上面看,性能爆表啊。
原因是什么呢?是不是因为这个语言有类型的概念?
High-Performance JIT CompilerJulia’s LLVM-based just-in-time (JIT) compiler combined with the language’s design allow it to approach and often match the performance of C.To get a sense of relative performance of Julia compared to other languages that can or could be used for numerical and scientific computing, we’ve written a small set of micro-benchmarks in a variety of languages:C,Fortran,Julia,Python,Matlab/Octave,R,JavaScript,Java,Lua,Go, andMathematica.We encourage you to skim the code to get a sense for how easy or difficult numerical programming in each language is.The following micro-benchmark results were obtained on a single core (serial execution) on an Intel(R) Xeon(R) CPU E7-8850 2.00GHz CPU with 1TB of 1067MHz DDR3 RAM, running Linux:
FortranJuliaPythonRMatlabOctaveMathe-maticaJavaScriptGoLuaJITJava
gcc 5.1.10.4.03.4.33.2.2R2015b4.0.010.2.0V8 3.28.71.19go1.5gsl-shell 2.3.11.8.0_45
fib0.702.1177.76533.5226.899324.35118.533.361.861.711.21
parse_int5.051.4517.0245.73802.529581.4415.026.061.205.773.35
quicksort1.311.1532.89264.544.921866.0143.232.701.292.032.60
mandel0.810.7915.3253.167.58451.815.130.661.110.671.35
pi_sum1.001.0021.999.561.00299.311.691.011.001.001.00
rand_mat_stat1.451.6617.9314.5614.5230.935.952.302.963.273.92
rand_mat_mul3.481.021.141.571.121.121.3015.07
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