{"action":"created","comment":{"url":"https://api.github.com/repos/serge-sans-paille/pythran-stories/pulls/comments/58601643","id":58601643,"diff_hunk":"@@ -0,0 +1,185 @@\n+Compiler Flags\n+##############\n+\n+:date: 2016-04-05\n+:category: benchmark\n+:lang: en\n+:authors: Lightjohn\n+:summary: Let's re-run an existing benchmark with pythran \n+\n+The benchmark\n+=================\n+\n+First there was a paper [0]_, \n+in the paper there was a github [1]_, \n+in the github [1]_ some benchmarks. \n+In my case I wanted to re-run the julia code because the language is changing quickly and so may do better. \n+But the day before I discovered `Pythran` so why not test both ?\n+\n+And so let's re-run two benchmarks: C++, Julia and add a new one, Pythran.\n+\n+Compiling and running C++ code was easy:\n+\n+\tg++ -Ofast RBC_CPP.cpp -o testcpp\n+\n+\n+then\n+\n+\ttestcpp \n+\tOutput = 0.562731, Capital = 0.178198, Consumption = 0.384533\n+\tIteration = 1, Sup Diff = 0.0527416\n+\tIteration = 10, Sup Diff = 0.0313469\n+\tIteration = 20, Sup Diff = 0.0187035\n+\tIteration = 30, Sup Diff = 0.0111655\n+\tIteration = 40, Sup Diff = 0.00666854\n+\tIteration = 50, Sup Diff = 0.00398429\n+\tIteration = 60, Sup Diff = 0.00238131\n+\tIteration = 70, Sup Diff = 0.00142366\n+\tIteration = 80, Sup Diff = 0.00085134\n+\tIteration = 90, Sup Diff = 0.000509205\n+\tIteration = 100, Sup Diff = 0.000304623\n+\tIteration = 110, Sup Diff = 0.000182265\n+\tIteration = 120, Sup Diff = 0.00010907\n+\tIteration = 130, Sup Diff = 6.52764e-05\n+\tIteration = 140, Sup Diff = 3.90711e-05\n+\tIteration = 150, Sup Diff = 2.33881e-05\n+\tIteration = 160, Sup Diff = 1.40086e-05\n+\tIteration = 170, Sup Diff = 8.39132e-06\n+\tIteration = 180, Sup Diff = 5.02647e-06\n+\tIteration = 190, Sup Diff = 3.0109e-06\n+\tIteration = 200, Sup Diff = 1.80355e-06\n+\tIteration = 210, Sup Diff = 1.08034e-06\n+\tIteration = 220, Sup Diff = 6.47132e-07\n+\tIteration = 230, Sup Diff = 3.87636e-07\n+\tIteration = 240, Sup Diff = 2.32197e-07\n+\tIteration = 250, Sup Diff = 1.39087e-07\n+\tIteration = 257, Sup Diff = 9.71604e-08\n+\t \n+\tMy check = 0.146549\n+\t \n+\tElapsed time is   = 2.40271\n+\n+\n+Then Julia Code:\n+\n+we run `julia`:\n+\n+\n+\tinclude(\"RBC_Julia.jl\")\n+\tjulia> @time main()\n+\tOutput = 0.5627314338711378 Capital = 0.178198287392527 Consumption = 0.3845331464786108\n+\tIteration = 1 Sup Diff = 0.05274159340733661\n+\tIteration = 10 Sup Diff = 0.031346949265852075\n+\tIteration = 20 Sup Diff = 0.01870345989335709\n+\tIteration = 30 Sup Diff = 0.01116551203397087\n+\tIteration = 40 Sup Diff = 0.006668541708132691\n+\tIteration = 50 Sup Diff = 0.003984292748717033\n+\tIteration = 60 Sup Diff = 0.0023813118039327508\n+\tIteration = 70 Sup Diff = 0.0014236586450983024\n+\tIteration = 80 Sup Diff = 0.0008513397747206275\n+\tIteration = 90 Sup Diff = 0.0005092051752288995\n+\tIteration = 100 Sup Diff = 0.0003046232442147634\n+\tIteration = 110 Sup Diff = 0.00018226485632300005\n+\tIteration = 120 Sup Diff = 0.00010906950872635601\n+\tIteration = 130 Sup Diff = 6.527643736320421e-5\n+\tIteration = 140 Sup Diff = 3.907108211997912e-5\n+\tIteration = 150 Sup Diff = 2.3388077119990136e-5\n+\tIteration = 160 Sup Diff = 1.4008644637408807e-5\n+\tIteration = 170 Sup Diff = 8.391317203093607e-6\n+\tIteration = 180 Sup Diff = 5.0264745379280384e-6\n+\tIteration = 190 Sup Diff = 3.010899863764571e-6\n+\tIteration = 200 Sup Diff = 1.8035522481030242e-6\n+\tIteration = 210 Sup Diff = 1.0803409160597965e-6\n+\tIteration = 220 Sup Diff = 6.471316946754513e-7\n+\tIteration = 230 Sup Diff = 3.876361940324813e-7\n+\tIteration = 240 Sup Diff = 2.3219657929729465e-7\n+\tIteration = 250 Sup Diff = 1.3908720952748865e-7\n+\tIteration = 257 Sup Diff = 9.716035642703957e-8\n+\t \n+\tMy check = 0.1465491436962635\n+\t3.001183 seconds (3.84 k allocations: 703.276 MB, 0.68% gc time)\n+\n+Not bad !\n+\n+Now some pythran code, we use the numba version: so we remove numba import and \n+add the pythran decorator:\n+\n+\n+\tfrom numba import autojit\n+\t\n+\t@autojit\n+\tdef innerloop(bbeta, nGridCapital, gridCapitalNextPeriod, mOutput, nProductivity, vGridCapital, expectedValueFunction, mValueFunction, mValueFunctionNew, mPolicyFunction):\n+\n+to\n+\n+\t#pythran export innerloop(float, int, int, float[][], int, float[], float[][], float[][], float[][], float[][])\n+\t  \n+\tdef innerloop(bbeta, nGridCapital, gridCapitalNextPeriod, mOutput, nProductivity, vGridCapital, expectedValueFunction, mValueFunction, mValueFunctionNew, mPolicyFunction):\n+\n+\n+Easy ? not quite... while pythranisation of the code, something went wrong, but\n+no idea why ! 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as you asked, here a quick article about my small journey.\r\nI had no idea on how to write so juste tell me what is wrong.\r\n\r\nOn my side it seems that usual github markdown does not work well compare to normal markdown.\r\n\r\nWhat do you think 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