Summary Data - Full Data [25 Mar 2019 u64q n]

name,lang,id,n,size(B),cpu(s),mem(KB),status,load,elapsed(s) [25 Mar 2019 u64q n]
binary-trees,Pyston,1,14,743,1.916,169100,0,74% 93% 73% 71%,0.622
binary-trees,Pyston,1,14,743,1.958,172728,0,68% 88% 71% 67%,0.723
binary-trees,Pyston,1,14,743,1.945,169224,0,69% 67% 94% 70%,0.653
binary-trees,Python dev,7,14,741,3.063,61908,0,89% 88% 91% 95%,0.962
binary-trees,Python dev,7,14,741,3.123,64676,0,91% 91% 88% 88%,0.961
binary-trees,Python dev,7,14,741,3.067,60992,0,92% 93% 92% 88%,1.169
binary-trees,Python 3,1,14,706,3.276,64672,0,90% 86% 90% 87%,0.964
binary-trees,Python 3,1,14,706,3.252,61568,0,90% 88% 86% 94%,0.957
binary-trees,Python 3,1,14,706,3.267,62884,0,88% 88% 85% 94%,0.957
binary-trees,Nuitka,7,14,741,2.464,67564,0,85% 82% 88% 84%,0.76
binary-trees,Nuitka,7,14,741,2.492,64448,0,88% 92% 81% 86%,0.759
binary-trees,Nuitka,7,14,741,2.500,69384,0,87% 82% 84% 91%,0.759
binary-trees,Python 2,1,14,743,3.850,60452,0,79% 87% 86% 80%,1.196
binary-trees,Python 2,1,14,743,3.816,59484,0,81% 91% 82% 80%,1.185
binary-trees,Python 2,1,14,743,3.767,58912,0,91% 82% 83% 88%,1.19
binary-trees,PyPy 3,7,14,741,2.049,126792,0,77% 63% 45% 46%,1.142
binary-trees,PyPy 3,7,14,741,1.965,132356,0,50% 39% 40% 85%,1.076
binary-trees,PyPy 3,7,14,741,2.082,129356,0,70% 53% 65% 50%,1.117
binary-trees,Numba,1,14,702,3.931,73772,0,85% 91% 83% 83%,1.157
binary-trees,Numba,1,14,702,4.003,63976,0,77% 78% 91% 79%,1.238
binary-trees,Numba,1,14,702,3.986,64276,0,78% 78% 79% 90%,1.226
binary-trees,PyPy,1,14,743,1.763,317208,0,50% 49% 70% 61%,0.8
binary-trees,PyPy,1,14,743,1.786,316980,0,54% 70% 55% 57%,0.792
binary-trees,PyPy,1,14,743,1.777,319260,0,52% 71% 66% 51%,0.791
chameneos-redux,Nuitka,2,6000000,1191,221.939,9872,0,48% 46% 49% 48%,118.191
chameneos-redux,Python 3,2,6000000,1191,166.347,8820,0,51% 46% 41% 46%,96.299
chameneos-redux,PyPy,1,6000000,1192,131.715,75156,0,52% 50% 53% 52%,66.682
chameneos-redux,PyPy 3,2,6000000,1191,146.892,66476,0,47% 39% 44% 47%,74.763
chameneos-redux,Python dev,1,6000000,1191,152.659,8856,0,41% 43% 36% 41%,85.129
chameneos-redux,Python 2,1,6000000,1192,152.780,7100,0,44% 45% 42% 39%,83.773
chameneos-redux,MicroPython,2,6000000,1191,105.969,4596,0,47% 35% 59% 52%,49.129
chameneos-redux,MicroPython,2,6000000,1191,103.085,4628,0,62% 32% 61% 42%,46.57
chameneos-redux,MicroPython,2,6000000,1191,105.224,4632,0,44% 39% 56% 55%,47.941
chameneos-redux,Cython,1,6000000,1203,211.406,8512,0,47% 43% 46% 46%,111.165
chameneos-redux,Pyston,1,6000000,1192,106.639,66884,0,31% 34% 26% 36%,58.296
chameneos-redux,Pyston,1,6000000,1192,105.826,70824,0,29% 35% 29% 36%,57.43
chameneos-redux,Pyston,1,6000000,1192,105.627,68732,0,32% 34% 27% 36%,56.976
fannkuch-redux,PyPy 3,1,10,1271,3.225,78352,0,61% 59% 61% 89%,1.233
fannkuch-redux,PyPy 3,1,10,1271,3.290,79388,0,58% 60% 58% 92%,1.308
fannkuch-redux,PyPy 3,1,10,1271,3.277,77572,0,87% 55% 57% 62%,1.411
fannkuch-redux,Python 3,3,10,894,11.829,52828,0,97% 96% 90% 97%,3.461
fannkuch-redux,Python 3,3,10,894,11.920,53056,0,94% 95% 93% 96%,3.676
fannkuch-redux,Python 3,3,10,894,12.112,52808,0,96% 93% 93% 95%,3.663
fannkuch-redux,Python dev,3,10,894,12.390,52732,0,96% 94% 98% 95%,3.259
fannkuch-redux,Python dev,3,10,894,12.481,52352,0,92% 96% 96% 98%,3.276
fannkuch-redux,Python dev,3,10,894,12.510,52376,0,96% 89% 95% 92%,3.404
fannkuch-redux,Nuitka,3,10,894,10.537,56000,0,98% 93% 97% 92%,2.863
fannkuch-redux,Nuitka,3,10,894,10.817,56320,0,97% 97% 97% 99%,2.863
fannkuch-redux,Nuitka,3,10,894,10.554,55940,0,91% 91% 93% 93%,2.975
fannkuch-redux,Pyston,1,10,1009,10.347,158560,0,95% 93% 99% 94%,2.726
fannkuch-redux,Pyston,1,10,1009,10.384,157872,0,92% 89% 95% 91%,2.831
fannkuch-redux,Pyston,1,10,1009,10.416,157584,0,87% 90% 89% 96%,2.891
fannkuch-redux,MicroPython,6,10,552,8.924,4244,0,1% 59% 0% 42%,8.936
fannkuch-redux,MicroPython,6,10,552,8.527,4260,0,0% 0% 0% 100%,8.54
fannkuch-redux,MicroPython,6,10,552,8.553,4220,0,0% 100% 1% 1%,8.561
fannkuch-redux,Graal,6,10,552,3.740,412464,0,6% 94% 18% 2%,3.213
fannkuch-redux,Graal,6,10,552,3.750,412268,0,23% 4% 2% 95%,3.223
fannkuch-redux,Graal,6,10,552,3.755,412392,0,13% 93% 14% 2%,3.228
fannkuch-redux,Python 2,1,10,1009,16.296,43292,0,96% 95% 94% 95%,4.369
fannkuch-redux,Python 2,1,10,1009,16.545,41932,0,97% 98% 96% 96%,4.365
fannkuch-redux,Python 2,1,10,1009,17.084,43620,0,97% 96% 98% 97%,4.645
fannkuch-redux,PyPy,1,10,1009,2.914,80708,0,70% 69% 86% 64%,1.046
fannkuch-redux,PyPy,1,10,1009,2.999,80556,0,88% 70% 69% 63%,1.09
fannkuch-redux,PyPy,1,10,1009,2.935,80980,0,65% 67% 63% 88%,1.078
fasta,Python dev,5,2500000,2016,8.702,72636,0,65% 67% 46% 36%,4.181
fasta,Python dev,5,2500000,2016,8.820,77892,0,67% 71% 34% 45%,4.14
fasta,Python dev,5,2500000,2016,8.783,89288,0,61% 72% 37% 43%,4.262
fasta,Python 2,1,2500000,900,6.855,13316,0,15% 2% 88% 3%,6.867
fasta,Python 2,1,2500000,900,6.546,13516,0,2% 3% 2% 100%,6.552
fasta,Python 2,1,2500000,900,6.641,13444,0,3% 100% 4% 4%,6.649
fasta,Pyston,1,2500000,900,4.624,33028,0,100% 0% 0% 0%,4.625
fasta,Pyston,1,2500000,900,4.610,32988,0,100% 0% 0% 0%,4.611
fasta,Pyston,1,2500000,900,4.632,32960,0,0% 26% 0% 74%,4.634
fasta,Graal,2,2500000,889,16.986,477020,0,67% 42% 33% 8%,12.289
fasta,Graal,2,2500000,889,16.535,492424,0,32% 6% 17% 93%,11.666
fasta,Graal,2,2500000,889,17.156,477712,0,51% 20% 30% 49%,11.943
fasta,Python 3,5,2500000,2016,9.469,89800,0,68% 59% 51% 68%,4.503
fasta,Python 3,5,2500000,2016,9.559,89232,0,54% 75% 75% 48%,4.496
fasta,Python 3,5,2500000,2016,10.165,90448,0,70% 79% 66% 51%,4.9
fasta,PyPy 3,4,2500000,1698,1.979,67728,0,4% 98% 5% 6%,2.002
fasta,PyPy 3,4,2500000,1698,1.926,67488,0,37% 3% 65% 3%,1.947
fasta,PyPy 3,4,2500000,1698,1.922,67984,0,4% 99% 3% 5%,1.945
fasta,PyPy,1,2500000,900,2.692,80960,0,10% 99% 5% 6%,2.716
fasta,PyPy,1,2500000,900,2.493,80708,0,99% 4% 4% 4%,2.521
fasta,PyPy,1,2500000,900,2.563,80976,0,99% 3% 2% 2%,2.59
fasta,Jython,1,2500000,900,25.948,299620,0,21% 45% 29% 24%,21.926
fasta,Jython,1,2500000,900,24.755,305304,0,41% 22% 27% 28%,20.912
fasta,Jython,1,2500000,900,25.402,316384,0,31% 32% 36% 20%,21.244
fasta,Nuitka,5,2500000,2016,9.579,90376,0,53% 77% 77% 39%,4.107
fasta,Nuitka,5,2500000,2016,9.482,93252,0,60% 67% 80% 39%,4.045
fasta,Nuitka,5,2500000,2016,9.268,82608,0,57% 73% 70% 35%,4.141
fasta,MicroPython,1,2500000,904,22.706,4516,0,0% 0% 22% 78%,22.743
fasta,MicroPython,1,2500000,904,21.980,4452,0,0% 100% 0% 0%,21.998
fasta,MicroPython,1,2500000,904,21.939,4660,0,11% 0% 89% 0%,21.955
fasta-redux,PyPy 3,7,2500000,1115,0.266,1048,0,3% 93% 3% 3%,0.284
fasta-redux,PyPy 3,7,2500000,1115,0.249,1084,0,100% 4% 4% 7%,0.251
fasta-redux,PyPy 3,7,2500000,1115,0.248,1140,0,4% 100% 4% 0%,0.25
fasta-redux,Python dev,1,2500000,1115,0.290,1864,0,0% 3% 6% 100%,0.293
fasta-redux,Python dev,1,2500000,1115,0.273,1816,0,0% 100% 4% 0%,0.275
fasta-redux,Python dev,1,2500000,1115,0.271,1928,0,4% 100% 0% 0%,0.272
fasta-redux,PyPy,1,2500000,1115,0.233,1324,0,92% 0% 4% 0%,0.25
fasta-redux,PyPy,1,2500000,1115,0.217,1316,0,0% 13% 100% 5%,0.219
fasta-redux,PyPy,1,2500000,1115,0.219,1240,0,4% 0% 4% 96%,0.222
fasta-redux,Cython,1,2500000,1169,0.168,0,0,0% 0% 100% 6%,0.169
fasta-redux,Cython,1,2500000,1169,0.150,0,0,0% 94% 0% 0%,0.151
fasta-redux,Cython,1,2500000,1169,0.150,0,0,0% 0% 100% 0%,0.151
fasta-redux,Nuitka,7,2500000,1115,0.286,732,0,4% 7% 0% 100%,0.288
fasta-redux,Nuitka,7,2500000,1115,0.275,708,0,97% 3% 17% 3%,0.29
fasta-redux,Nuitka,7,2500000,1115,0.261,1844,0,11% 100% 0% 0%,0.263
fasta-redux,Python 3,1,2500000,1115,0.356,908,0,31% 23% 100% 9%,0.359
fasta-redux,Python 3,1,2500000,1115,0.285,888,0,4% 100% 0% 4%,0.286
fasta-redux,Python 3,1,2500000,1115,0.286,1776,0,10% 3% 100% 3%,0.288
fib50,Graal,1,1000000,136,16.478,468912,0,13% 93% 14% 23%,12.403
fib50,Graal,1,1000000,136,15.244,474316,0,19% 26% 31% 91%,11.078
fib50,Graal,1,1000000,136,15.489,469868,0,73% 29% 29% 25%,11.06
fib50,Cython,1,1000000,159,0.791,8908,0,5% 3% 100% 7%,0.793
fib50,Cython,1,1000000,159,0.779,8896,0,5% 4% 100% 13%,0.781
fib50,Cython,1,1000000,159,0.764,8744,0,100% 3% 4% 3%,0.767
fib50,Numba,1,1000000,152,1.328,73672,0,0% 0% 99% 1%,1.328
fib50,Numba,1,1000000,152,1.343,73220,0,1% 1% 99% 0%,1.343
fib50,Numba,1,1000000,152,1.338,73180,0,0% 1% 0% 100%,1.338
fib50,MicroPython,1,1000000,136,6.274,4100,0,2% 0% 0% 100%,6.283
fib50,MicroPython,1,1000000,136,4.646,4100,0,100% 0% 0% 0%,4.65
fib50,MicroPython,1,1000000,136,4.642,4100,0,0% 1% 0% 100%,4.648
fib50,Nuitka,1,1000000,136,4.554,10120,0,6% 2% 2% 100%,4.561
fib50,Nuitka,1,1000000,136,4.619,10000,0,7% 2% 100% 2%,4.626
fib50,Nuitka,1,1000000,136,4.671,10148,0,7% 2% 100% 2%,4.677
fib50,PyPy 3,1,1000000,136,0.844,71468,0,2% 99% 0% 3%,0.863
fib50,PyPy 3,1,1000000,136,0.842,71512,0,60% 1% 42% 5%,0.845
fib50,PyPy 3,1,1000000,136,0.837,71112,0,2% 2% 5% 100%,0.84
fib50,Python 3,1,1000000,136,3.342,8880,0,11% 5% 5% 99%,3.348
fib50,Python 3,1,1000000,136,3.437,8964,0,12% 8% 11% 100%,3.444
fib50,Python 3,1,1000000,136,3.743,8908,0,37% 26% 33% 100%,3.752
fib50,Python dev,1,1000000,136,3.230,8904,0,2% 2% 1% 100%,3.24
fib50,Python dev,1,1000000,136,3.228,8788,0,2% 1% 2% 100%,3.236
fib50,Python dev,1,1000000,136,3.235,8960,0,2% 2% 2% 100%,3.243
fibonacci,Jython,3,1000000,181,4.768,272324,0,73% 84% 58% 36%,1.899
fibonacci,Jython,3,1000000,181,4.415,246336,0,79% 62% 61% 47%,1.775
fibonacci,Jython,3,1000000,181,4.567,255888,0,73% 69% 61% 51%,1.803
fibonacci,Python 3,3,1000000,182,0.672,9420,0,4% 9% 100% 10%,0.675
fibonacci,Python 3,3,1000000,182,0.670,9284,0,9% 1% 100% 5%,0.673
fibonacci,Python 3,3,1000000,182,0.670,9364,0,5% 100% 6% 2%,0.672
fibonacci,PyPy,3,1000000,181,0.255,1312,0,4% 4% 0% 100%,0.257
fibonacci,PyPy,3,1000000,181,0.258,1272,0,100% 4% 7% 0%,0.261
fibonacci,PyPy,3,1000000,181,0.254,1332,0,100% 0% 4% 0%,0.256
fibonacci,Nuitka,3,1000000,182,0.679,10380,0,9% 1% 3% 100%,0.681
fibonacci,Nuitka,3,1000000,182,0.677,10420,0,5% 1% 1% 100%,0.679
fibonacci,Nuitka,3,1000000,182,0.678,10392,0,9% 9% 0% 100%,0.68
fibonacci,MicroPython,3,1000000,182,81.743,3180,0,0% 0% 100% 0%,81.79
fibonacci,MicroPython,3,1000000,182,81.745,3084,0,0% 0% 0% 100%,81.823
fibonacci,MicroPython,3,1000000,182,81.744,3184,0,4% 0% 96% 0%,81.79
fibonacci,Python 2,3,1000000,181,0.669,7284,0,99% 2% 3% 6%,0.671
fibonacci,Python 2,3,1000000,181,0.666,7384,0,12% 2% 6% 100%,0.669
fibonacci,Python 2,3,1000000,181,0.666,7240,0,1% 100% 3% 0%,0.667
fibonacci,Pyston,3,1000000,181,0.059,0,0,0% 0% 0% 100%,0.06
fibonacci,Pyston,3,1000000,181,0.059,0,0,14% 0% 0% 100%,0.06
fibonacci,Pyston,3,1000000,181,0.059,0,0,0% 0% 0% 100%,0.06
fibonacci,Python dev,3,1000000,182,0.675,9212,0,1% 5% 0% 99%,0.678
fibonacci,Python dev,3,1000000,182,0.667,9144,0,3% 100% 3% 0%,0.669
fibonacci,Python dev,3,1000000,182,0.668,9308,0,99% 0% 2% 1%,0.67
fibonacci,Grumpy,2,1000000,110,38.805,550940,0,71% 69% 67% 68%,15.903
fibonacci,Grumpy,2,1000000,110,39.459,519192,0,65% 71% 63% 66%,15.778
fibonacci,Grumpy,2,1000000,110,38.552,498660,0,65% 71% 65% 64%,15.392
fibonacci,PyPy 3,3,1000000,182,0.293,1012,0,28% 29% 32% 94%,0.329
fibonacci,PyPy 3,3,1000000,182,0.271,1136,0,7% 11% 7% 100%,0.273
fibonacci,PyPy 3,3,1000000,182,0.263,1112,0,4% 0% 4% 100%,0.265
fibonacci,Graal,2,1000000,110,32.905,398904,0,99% 5% 5% 5%,32.867
fibonacci,Graal,2,1000000,110,32.719,398936,0,99% 3% 4% 3%,32.697
fibonacci,Graal,2,1000000,110,32.768,400740,0,5% 56% 5% 47%,32.718
fibonacci,Numba,1,1000000,160,1.198,75208,0,99% 0% 0% 0%,1.199
fibonacci,Numba,1,1000000,160,1.199,75420,0,99% 1% 1% 0%,1.199
fibonacci,Numba,1,1000000,160,1.200,74964,0,0% 1% 0% 100%,1.2
fibonacci,IronPython,3,1000000,181,5.861,53032,0,100% 0% 0% 0%,5.862
fibonacci,IronPython,3,1000000,181,5.864,55276,0,0% 100% 0% 0%,5.865
fibonacci,IronPython,3,1000000,181,5.863,50872,0,0% 0% 100% 0%,5.863
fibonacci,Cython,3,1000000,184,0.675,9268,0,10% 14% 7% 100%,0.681
fibonacci,Cython,3,1000000,184,0.694,9172,0,80% 59% 28% 37%,0.7
fibonacci,Cython,3,1000000,184,0.681,9068,0,81% 24% 22% 40%,0.699
iobench,Numba,1,1,384,4.821,79516,0,0% 0% 100% 0%,4.821
iobench,Numba,1,1,384,5.012,79572,0,0% 96% 0% 4%,5.013
iobench,Numba,1,1,384,4.880,80276,0,0% 0% 100% 0%,4.881
iobench,Python 3,1,1,367,5.582,8556,0,34% 34% 24% 93%,5.756
iobench,Python 3,1,1,367,5.324,8440,0,16% 12% 100% 12%,5.337
iobench,Python 3,1,1,367,5.487,8472,0,25% 23% 100% 18%,5.502
iobench,PyPy 3,1,1,367,18.886,75960,0,81% 5% 23% 5%,18.956
iobench,PyPy 3,1,1,367,18.949,75516,0,85% 4% 19% 6%,19.028
iobench,PyPy 3,1,1,367,19.015,75616,0,83% 6% 23% 6%,19.1
iobench,Graal,1,1,367,151.153,566424,0,67% 30% 13% 14%,136.752
iobench,Python dev,1,1,367,4.853,8528,0,2% 1% 1% 100%,4.862
iobench,Python dev,1,1,367,4.857,8468,0,2% 1% 100% 0%,4.861
iobench,Python dev,1,1,367,4.806,8440,0,1% 100% 0% 1%,4.81
iobench,Nuitka,1,1,367,4.957,9780,0,6% 1% 2% 100%,4.963
iobench,Nuitka,1,1,367,5.095,9796,0,7% 1% 100% 1%,5.102
iobench,Nuitka,1,1,367,5.137,9580,0,6% 2% 100% 2%,5.144
iobench,PyPy,1,1,370,24.107,86500,0,94% 4% 10% 5%,24.196
iobench,PyPy,1,1,370,24.227,86832,0,17% 88% 4% 5%,24.294
iobench,PyPy,1,1,370,24.058,86328,0,75% 5% 24% 9%,24.142
iobench,Cython,1,1,366,0.021,0,0,0% 0% 67% 0%,0.023
iobench,Cython,1,1,366,0.021,0,0,100% 0% 0% 0%,0.023
iobench,Cython,1,1,366,0.021,0,0,100% 0% 0% 0%,0.023
iobench,Python 2,1,1,370,36.665,6844,0,3% 100% 3% 2%,36.692
iobench,Python 2,1,1,370,36.460,6892,0,19% 12% 74% 3%,36.506
iobench,Python 2,1,1,370,37.394,6992,0,2% 100% 2% 3%,37.421
iobench,Pyston,1,1,370,20.144,26780,0,0% 4% 100% 8%,20.145
iobench,Pyston,1,1,370,20.117,26684,0,0% 61% 0% 39%,20.119
iobench,Pyston,1,1,370,20.339,26752,0,100% 0% 0% 0%,20.34
jsonbench,PyPy 3,1,1,322,1.514,74372,0,99% 4% 4% 5%,1.537
jsonbench,PyPy 3,1,1,322,1.523,74700,0,99% 1% 6% 3%,1.546
jsonbench,PyPy 3,1,1,322,1.531,74040,0,99% 7% 6% 4%,1.553
jsonbench,Nuitka,1,1,322,3.689,12992,0,7% 2% 100% 3%,3.696
jsonbench,Nuitka,1,1,322,3.679,12916,0,7% 2% 100% 2%,3.686
jsonbench,Nuitka,1,1,322,3.539,12416,0,7% 81% 2% 21%,3.546
jsonbench,Python dev,1,1,322,3.555,12468,0,4% 3% 100% 2%,3.56
jsonbench,Python dev,1,1,322,3.507,11188,0,1% 100% 1% 1%,3.512
jsonbench,Python dev,1,1,322,3.554,12220,0,3% 100% 1% 1%,3.559
jsonbench,PyPy,1,1,322,1.314,82212,0,2% 2% 4% 98%,1.335
jsonbench,PyPy,1,1,322,1.297,82736,0,8% 3% 5% 98%,1.318
jsonbench,PyPy,1,1,322,1.310,82192,0,98% 4% 6% 3%,1.334
jsonbench,Cython,1,1,323,3.764,11656,0,18% 98% 17% 14%,3.781
jsonbench,Cython,1,1,323,3.759,12032,0,87% 12% 28% 10%,3.786
jsonbench,Cython,1,1,323,3.533,12416,0,4% 100% 5% 3%,3.541
jsonbench,Python 2,1,1,322,4.469,16652,0,3% 2% 100% 3%,4.481
jsonbench,Python 2,1,1,322,4.480,16572,0,66% 2% 37% 3%,4.488
jsonbench,Python 2,1,1,322,4.562,17080,0,3% 100% 3% 3%,4.569
jsonbench,Pyston,1,1,322,26.686,41540,0,11% 0% 89% 0%,26.687
jsonbench,Pyston,1,1,322,26.459,42332,0,0% 79% 0% 22%,26.462
jsonbench,Pyston,1,1,322,26.462,41828,0,100% 0% 0% 0%,26.463
jsonbench,Python 3,1,1,322,3.561,11404,0,100% 5% 4% 4%,3.735
jsonbench,Python 3,1,1,322,3.625,11144,0,100% 5% 5% 9%,3.812
jsonbench,Python 3,1,1,322,3.615,12268,0,100% 5% 4% 5%,3.798
jsonbench,Jython,1,1,322,27.283,396084,0,44% 51% 69% 31%,14.102
jsonbench,Jython,1,1,322,22.942,336268,0,43% 29% 38% 58%,13.632
jsonbench,Jython,1,1,322,23.563,404840,0,41% 38% 41% 51%,13.911
k-nucleotide,Pyston,1,10000,593,0.122,0,0,0% 0% 0% 92%,0.124
k-nucleotide,Pyston,1,10000,593,0.097,0,0,22% 9% 80% 10%,0.1
k-nucleotide,Pyston,1,10000,593,0.096,0,0,100% 0% 0% 0%,0.097
k-nucleotide,Cython,1,10000,618,0.091,0,0,0% 0% 100% 0%,0.093
k-nucleotide,Cython,1,10000,618,0.105,0,0,22% 10% 100% 18%,0.106
k-nucleotide,Cython,1,10000,618,0.118,0,0,15% 58% 8% 100%,0.119
k-nucleotide,Nuitka,1,10000,594,0.107,0,0,8% 0% 100% 0%,0.109
k-nucleotide,Nuitka,1,10000,594,0.108,0,0,18% 100% 17% 17%,0.109
k-nucleotide,Nuitka,1,10000,594,0.105,0,0,9% 0% 0% 100%,0.106
k-nucleotide,Python 2,1,10000,593,0.078,0,0,0% 0% 0% 100%,0.08
k-nucleotide,Python 2,1,10000,593,0.078,0,0,0% 0% 0% 100%,0.08
k-nucleotide,Python 2,1,10000,593,0.079,0,0,100% 0% 0% 11%,0.081
k-nucleotide,Python dev,1,10000,594,0.119,0,0,23% 77% 0% 8%,0.121
k-nucleotide,Python dev,1,10000,594,0.113,0,0,0% 8% 100% 0%,0.114
k-nucleotide,Python dev,1,10000,594,0.111,0,0,0% 100% 8% 8%,0.112
k-nucleotide,PyPy,1,10000,593,0.108,0,0,91% 7% 8% 8%,0.124
k-nucleotide,PyPy,1,10000,593,0.107,0,0,100% 0% 0% 0%,0.109
k-nucleotide,PyPy,1,10000,593,0.109,0,0,0% 100% 0% 0%,0.111
k-nucleotide,Graal,1,10000,594,3.846,437944,0,54% 23% 57% 59%,2.096
k-nucleotide,Graal,1,10000,594,3.957,430424,0,12% 47% 52% 89%,2.089
k-nucleotide,Graal,1,10000,594,3.951,432112,0,64% 4% 42% 87%,2.094
k-nucleotide,Jython,1,10000,593,3.848,188480,0,81% 45% 63% 59%,1.611
k-nucleotide,Jython,1,10000,593,4.268,198752,0,67% 70% 65% 68%,1.8
k-nucleotide,Jython,1,10000,593,3.954,197900,0,66% 50% 61% 77%,1.664
k-nucleotide,Python 3,1,10000,594,0.127,0,0,8% 21% 83% 8%,0.129
k-nucleotide,Python 3,1,10000,594,0.115,0,0,8% 100% 0% 8%,0.116
k-nucleotide,Python 3,1,10000,594,0.119,0,0,100% 8% 14% 8%,0.126
k-nucleotide,PyPy 3,1,10000,594,0.154,0,0,0% 100% 0% 0%,0.157
k-nucleotide,PyPy 3,1,10000,594,0.140,0,0,7% 100% 0% 13%,0.142
k-nucleotide,PyPy 3,1,10000,594,0.140,0,0,100% 7% 0% 0%,0.142
k-nucleotide,IronPython,1,10000,593,1.195,71668,0,34% 11% 3% 39%,1.587
k-nucleotide,IronPython,1,10000,593,1.134,78304,0,3% 3% 52% 23%,1.551
k-nucleotide,IronPython,1,10000,593,1.146,80896,0,56% 4% 16% 3%,1.567
k-nucleotide,Shedskin,1,10000,593,0.064,0,0,0% 0% 0% 100%,0.049
k-nucleotide,Shedskin,1,10000,593,0.064,0,0,0% 40% 67% 20%,0.049
k-nucleotide,Shedskin,1,10000,593,0.064,0,0,0% 20% 0% 100%,0.049
mandelbrot,Python 3,6,16000,3832,74.084,181936,0,98% 98% 98% 99%,19.521
mandelbrot,Python 3,6,16000,3832,77.391,182904,0,98% 96% 98% 99%,20.82
mandelbrot,Python 3,6,16000,3832,79.284,182676,0,99% 96% 95% 98%,21.875
mandelbrot,Nuitka,6,16000,3832,78.418,61872,0,98% 97% 97% 99%,20.309
mandelbrot,Nuitka,6,16000,3832,80.787,11331612,0,99% 98% 98% 99%,20.798
mandelbrot,Nuitka,6,16000,3832,83.118,11365740,0,99% 99% 99% 99%,21.279
mandelbrot,Python dev,6,16000,3832,74.023,181748,0,98% 98% 98% 97%,19.184
mandelbrot,Python dev,6,16000,3832,76.708,181892,0,99% 98% 96% 96%,20.053
mandelbrot,Python dev,6,16000,3832,79.948,182416,0,98% 99% 98% 98%,20.594
mandelbrot,Python 2,6,16000,3832,75.628,176524,0,95% 100% 97% 96%,20.232
mandelbrot,Python 2,6,16000,3832,76.103,176744,0,99% 97% 97% 98%,20.043
mandelbrot,Python 2,6,16000,3832,76.504,176760,0,98% 98% 99% 98%,20.135
mandelbrot,Numba,6,16000,3865,80.001,100552,0,99% 97% 97% 99%,20.422
mandelbrot,Numba,6,16000,3865,80.208,100328,0,99% 97% 99% 98%,20.423
mandelbrot,Numba,6,16000,3865,80.031,100324,0,99% 98% 97% 98%,20.416
mandelbrot,Pyston,6,16000,3832,68.133,138712,0,94% 95% 97% 93%,18.047
mandelbrot,Pyston,6,16000,3832,68.369,129704,0,97% 95% 98% 97%,17.824
mandelbrot,Pyston,6,16000,3832,68.453,129816,0,98% 97% 97% 95%,17.751
meteor-contest,PyPy,2,2098,1485,0.936,85108,0,3% 11% 3% 97%,0.957
meteor-contest,PyPy,2,2098,1485,0.903,85132,0,1% 3% 100% 1%,0.907
meteor-contest,PyPy,2,2098,1485,0.967,84788,0,18% 100% 20% 15%,0.975
meteor-contest,Cython,3,2098,1334,3.710,11156,0,8% 100% 8% 9%,3.721
meteor-contest,Cython,3,2098,1334,3.703,11100,0,100% 7% 9% 6%,3.716
meteor-contest,Cython,3,2098,1334,3.723,11156,0,100% 8% 9% 8%,3.734
meteor-contest,Pyston,2,2098,1485,1.742,29972,0,3% 98% 0% 0%,1.744
meteor-contest,Pyston,2,2098,1485,1.743,28016,0,100% 0% 1% 0%,1.744
meteor-contest,Pyston,2,2098,1485,1.740,30156,0,0% 0% 99% 0%,1.741
meteor-contest,Python 2,2,2098,1485,2.643,7092,0,77% 2% 25% 1%,2.648
meteor-contest,Python 2,2,2098,1485,2.614,7132,0,1% 0% 1% 100%,2.617
meteor-contest,Python 2,2,2098,1485,2.644,7156,0,3% 100% 1% 2%,2.647
meteor-contest,Nuitka,2,2098,1443,2.680,10176,0,31% 4% 70% 1%,2.684
meteor-contest,Nuitka,2,2098,1443,2.671,10072,0,3% 1% 100% 4%,2.675
meteor-contest,Nuitka,2,2098,1443,2.691,10292,0,11% 100% 4% 3%,2.695
meteor-contest,Jython,2,2098,1485,12.661,311796,0,42% 41% 36% 48%,7.547
meteor-contest,Jython,2,2098,1485,13.334,319360,0,51% 40% 36% 46%,7.695
meteor-contest,Jython,2,2098,1485,12.506,307576,0,25% 40% 49% 55%,7.414
meteor-contest,Graal,2,2098,1443,20.762,853136,0,55% 69% 60% 61%,10.008
meteor-contest,Graal,2,2098,1443,17.734,680656,0,75% 19% 57% 66%,8.628
meteor-contest,Graal,2,2098,1443,19.244,672212,0,61% 69% 58% 49%,9.149
meteor-contest,Python dev,2,2098,1443,3.211,8988,0,1% 1% 0% 100%,3.217
meteor-contest,Python dev,2,2098,1443,3.192,9024,0,1% 100% 4% 1%,3.196
meteor-contest,Python dev,2,2098,1443,3.196,9024,0,11% 95% 3% 1%,3.201
meteor-contest,Python 3,2,2098,1443,3.313,8820,0,6% 4% 4% 99%,3.318
meteor-contest,Python 3,2,2098,1443,3.318,8816,0,7% 6% 3% 100%,3.323
meteor-contest,Python 3,2,2098,1443,3.396,8852,0,44% 5% 64% 4%,3.458
meteor-contest,PyPy 3,2,2098,1443,0.929,74836,0,3% 5% 7% 98%,0.949
meteor-contest,PyPy 3,2,2098,1443,0.949,75136,0,100% 9% 9% 6%,0.957
meteor-contest,PyPy 3,2,2098,1443,0.928,75136,0,5% 7% 8% 100%,0.932
n-body,Graal,1,5000000,1315,7.696,398824,0,41% 9% 58% 5%,7.41
n-body,Graal,1,5000000,1315,7.578,398772,0,58% 6% 42% 8%,7.314
n-body,Graal,1,5000000,1315,7.721,398824,0,78% 7% 26% 2%,7.458
n-body,MicroPython,1,5000000,1315,104.713,4684,0,0% 0% 100% 0%,104.793
n-body,MicroPython,1,5000000,1315,104.454,4684,0,0% 12% 0% 88%,104.6
n-body,MicroPython,1,5000000,1315,104.542,4544,0,0% 0% 0% 100%,104.686
n-body,Jython,1,5000000,1337,74.195,299088,0,20% 25% 33% 28%,70.257
n-body,Jython,1,5000000,1337,71.234,297436,0,28% 28% 24% 26%,67.645
n-body,Jython,1,5000000,1337,72.577,297252,0,34% 21% 30% 21%,68.565
n-body,Python dev,1,5000000,1315,44.933,8820,0,2% 6% 95% 1%,44.96
n-body,Python dev,1,5000000,1315,44.081,8812,0,8% 65% 1% 29%,44.127
n-body,Python dev,1,5000000,1315,44.218,8824,0,10% 2% 92% 0%,44.246
n-body,IronPython,1,5000000,1337,54.998,65208,0,69% 7% 11% 12%,55.189
n-body,IronPython,1,5000000,1337,55.210,63040,0,0% 66% 0% 34%,54.672
n-body,IronPython,1,5000000,1337,56.371,63324,0,30% 0% 68% 0%,56.69
n-body,PyPy,1,5000000,1337,6.548,76200,0,100% 4% 7% 5%,6.594
n-body,PyPy,1,5000000,1337,6.561,76468,0,91% 4% 15% 6%,6.606
n-body,PyPy,1,5000000,1337,6.589,76408,0,100% 5% 5% 6%,6.629
n-body,PyPy 3,1,5000000,1315,6.687,66948,0,100% 3% 4% 2%,6.722
n-body,PyPy 3,1,5000000,1315,6.593,67008,0,2% 19% 3% 83%,6.621
n-body,PyPy 3,1,5000000,1315,6.524,67008,0,3% 4% 3% 100%,6.555
n-body,Python 3,1,5000000,1315,45.054,8756,0,13% 7% 7% 100%,45.104
n-body,Python 3,1,5000000,1315,44.167,8856,0,7% 4% 3% 100%,44.201
n-body,Python 3,1,5000000,1315,44.287,8796,0,7% 100% 3% 4%,44.325
n-body,Numba,1,5000000,1333,59.744,96736,0,0% 0% 100% 0%,60.013
n-body,Numba,1,5000000,1333,59.620,97376,0,0% 26% 0% 74%,59.623
n-body,Numba,1,5000000,1333,58.432,97492,0,0% 100% 0% 0%,58.437
n-body,Nuitka,1,5000000,1315,42.722,9612,0,8% 100% 7% 8%,42.808
n-body,Nuitka,1,5000000,1315,42.876,9720,0,7% 37% 7% 71%,42.993
n-body,Nuitka,1,5000000,1315,41.405,9708,0,13% 45% 51% 9%,41.487
n-body,Pyston,1,5000000,1337,29.442,26596,0,0% 53% 0% 47%,29.445
n-body,Pyston,1,5000000,1337,31.054,26724,0,2% 0% 98% 0%,31.055
n-body,Pyston,1,5000000,1337,29.488,26648,0,0% 0% 100% 0%,29.489
n-body,Cython,1,5000000,1392,11.803,8640,0,98% 3% 6% 3%,11.829
n-body,Cython,1,5000000,1392,11.865,8572,0,5% 82% 4% 23%,11.886
n-body,Cython,1,5000000,1392,11.997,8544,0,50% 8% 9% 55%,12.04
n-body,Python 2,1,5000000,1337,48.926,6740,0,1% 0% 0% 100%,48.952
n-body,Python 2,1,5000000,1337,50.940,6616,0,2% 17% 80% 6%,50.991
n-body,Python 2,1,5000000,1337,53.173,6692,0,30% 28% 64% 20%,53.332
pidigits,Python 3,4,10000,379,0.026,0,0,0% 67% 50% 25%,0.027
pidigits,Python 3,4,10000,379,0.026,0,0,0% 100% 0% 0%,0.027
pidigits,Python 3,4,10000,379,0.026,0,0,0% 0% 100% 0%,0.027
pidigits,Python 2,4,10000,380,0.017,0,0,50% 0% 100% 0%,0.019
pidigits,Python 2,4,10000,380,0.013,0,0,0% 0% 0% 100%,0.014
pidigits,Python 2,4,10000,380,0.013,0,0,0% 0% 100% 0%,0.014
pidigits,Pyston,1,10000,322,0.906,26560,0,0% 4% 95% 0%,0.908
pidigits,Pyston,1,10000,322,0.902,26528,0,1% 100% 0% 0%,0.903
pidigits,Pyston,1,10000,322,0.908,26480,0,100% 0% 0% 1%,0.909
pidigits,PyPy 3,1,10000,322,3.195,77724,0,16% 21% 17% 100%,3.224
pidigits,PyPy 3,1,10000,322,3.246,77248,0,100% 24% 26% 23%,3.3
pidigits,PyPy 3,1,10000,322,3.213,77428,0,30% 31% 81% 18%,3.248
pidigits,Jython,1,10000,322,9.415,324056,0,47% 39% 41% 40%,5.633
pidigits,Jython,1,10000,322,8.861,294580,0,29% 51% 30% 54%,5.441
pidigits,Jython,1,10000,322,8.844,290952,0,34% 45% 51% 35%,5.402
pidigits,Python dev,4,10000,379,0.026,0,0,75% 0% 0% 0%,0.03
pidigits,Python dev,4,10000,379,0.025,0,0,0% 0% 100% 0%,0.026
pidigits,Python dev,4,10000,379,0.025,0,0,0% 100% 0% 0%,0.026
pidigits,Nuitka,4,10000,379,0.046,0,0,60% 40% 17% 0%,0.052
pidigits,Nuitka,4,10000,379,0.040,0,0,100% 0% 0% 0%,0.042
pidigits,Nuitka,4,10000,379,0.034,0,0,100% 0% 0% 0%,0.035
pidigits,Cython,4,10000,349,0.026,0,0,0% 0% 33% 67%,0.027
pidigits,Cython,4,10000,349,0.026,0,0,0% 0% 100% 0%,0.027
pidigits,Cython,4,10000,349,0.026,0,0,0% 100% 0% 0%,0.027
pidigits,MicroPython,1,10000,322,12.328,4172,0,100% 0% 0% 0%,12.344
pidigits,MicroPython,1,10000,322,12.367,4144,0,38% 1% 63% 0%,12.384
pidigits,MicroPython,1,10000,322,12.335,4144,0,0% 0% 100% 0%,12.351
pidigits,PyPy,1,10000,322,3.182,87440,0,93% 16% 25% 17%,3.221
pidigits,PyPy,1,10000,322,3.073,87328,0,33% 74% 12% 14%,3.108
pidigits,PyPy,1,10000,322,3.395,87640,0,67% 61% 32% 30%,3.45
pidigits,IronPython,1,10000,322,13.148,79276,0,1% 29% 5% 68%,12.686
pidigits,IronPython,1,10000,322,13.115,77680,0,58% 2% 41% 2%,12.682
pidigits,IronPython,1,10000,322,13.139,78604,0,0% 57% 3% 42%,12.687
pystone,Pyston,1,50000,2301,0.165,0,0,0% 0% 100% 0%,0.166
pystone,Pyston,1,50000,2301,0.168,0,0,0% 0% 6% 100%,0.169
pystone,Pyston,1,50000,2301,0.166,0,0,100% 0% 0% 0%,0.167
pystone,Nuitka,1,50000,2303,0.199,0,0,0% 100% 10% 5%,0.2
pystone,Nuitka,1,50000,2303,0.193,0,0,0% 0% 0% 95%,0.194
pystone,Nuitka,1,50000,2303,0.193,0,0,100% 0% 5% 5%,0.195
pystone,Jython,1,50000,2301,6.573,311316,0,79% 68% 54% 76%,2.393
pystone,Jython,1,50000,2301,6.202,281144,0,97% 53% 71% 60%,2.209
pystone,Jython,1,50000,2301,6.387,287728,0,82% 72% 66% 61%,2.287
pystone,MicroPython,1,50000,2303,0.368,1256,0,0% 100% 0% 0%,0.37
pystone,MicroPython,1,50000,2303,0.373,1172,0,0% 100% 3% 3%,0.374
pystone,MicroPython,1,50000,2303,0.376,1136,0,3% 100% 0% 0%,0.378
pystone,IronPython,1,50000,2301,1.177,64960,0,32% 26% 3% 24%,1.426
pystone,IronPython,1,50000,2301,1.205,65140,0,3% 51% 3% 26%,1.46
pystone,IronPython,1,50000,2301,1.173,63512,0,2% 35% 4% 41%,1.427
pystone,Python dev,1,50000,2303,0.273,1856,0,0% 4% 100% 0%,0.274
pystone,Python dev,1,50000,2303,0.266,1876,0,0% 0% 100% 0%,0.267
pystone,Python dev,1,50000,2303,0.265,1816,0,0% 4% 100% 4%,0.267
pystone,Graal,1,50000,2303,2.437,402248,0,31% 41% 63% 53%,1.543
pystone,Graal,1,50000,2303,2.466,400604,0,31% 59% 79% 21%,1.591
pystone,Graal,1,50000,2303,2.559,406296,0,50% 51% 38% 69%,1.676
pystone,Cython,1,50000,2402,0.086,0,0,0% 0% 100% 11%,0.087
pystone,Cython,1,50000,2402,0.090,0,0,100% 11% 11% 0%,0.092
pystone,Cython,1,50000,2402,0.087,0,0,0% 100% 0% 0%,0.088
pystone,PyPy 3,1,50000,2303,0.120,0,0,0% 7% 85% 7%,0.137
pystone,PyPy 3,1,50000,2303,0.119,0,0,8% 100% 8% 0%,0.122
pystone,PyPy 3,1,50000,2303,0.118,0,0,0% 0% 0% 100%,0.119
pystone,Python 2,1,50000,2301,0.234,860,0,4% 0% 100% 0%,0.236
pystone,Python 2,1,50000,2301,0.230,844,0,96% 4% 0% 4%,0.232
pystone,Python 2,1,50000,2301,0.234,852,0,0% 96% 4% 0%,0.235
pystone,PyPy,1,50000,2301,0.146,0,0,50% 63% 87% 27%,0.162
pystone,PyPy,1,50000,2301,0.144,0,0,100% 53% 57% 13%,0.147
pystone,PyPy,1,50000,2301,0.140,0,0,100% 60% 57% 8%,0.142
pystone,Python 3,1,50000,2303,0.278,1896,0,7% 3% 100% 0%,0.28
pystone,Python 3,1,50000,2303,0.268,1816,0,7% 96% 0% 4%,0.27
pystone,Python 3,1,50000,2303,0.264,1808,0,7% 100% 4% 0%,0.265
regex-dna,Pyston,5,10000,501,0.078,0,0,11% 13% 0% 89%,0.08
regex-dna,Pyston,5,10000,501,0.075,0,0,0% 0% 0% 100%,0.076
regex-dna,Pyston,5,10000,501,0.077,0,0,13% 0% 0% 100%,0.078
regex-dna,PyPy 3,5,10000,524,0.213,1108,0,91% 4% 0% 4%,0.23
regex-dna,PyPy 3,5,10000,524,0.228,1136,0,0% 100% 5% 9%,0.23
regex-dna,PyPy 3,5,10000,524,0.226,1016,0,5% 100% 16% 5%,0.229
regex-dna,PyPy,5,10000,501,0.133,0,0,0% 93% 7% 0%,0.135
regex-dna,PyPy,5,10000,501,0.140,0,0,14% 7% 0% 100%,0.142
regex-dna,PyPy,5,10000,501,0.133,0,0,7% 0% 0% 100%,0.134
regex-dna,Nuitka,5,10000,524,0.053,0,0,0% 0% 100% 0%,0.054
regex-dna,Nuitka,5,10000,524,0.053,0,0,0% 17% 100% 0%,0.054
regex-dna,Nuitka,5,10000,524,0.053,0,0,33% 100% 0% 0%,0.054
regex-dna,Jython,5,10000,501,3.351,176284,0,46% 92% 52% 57%,1.42
regex-dna,Jython,5,10000,501,3.395,173756,0,50% 56% 52% 96%,1.408
regex-dna,Jython,5,10000,501,3.702,190872,0,69% 52% 72% 64%,1.567
regex-dna,Python 3,5,10000,524,0.049,0,0,17% 83% 0% 0%,0.051
regex-dna,Python 3,5,10000,524,0.047,0,0,0% 100% 0% 0%,0.048
regex-dna,Python 3,5,10000,524,0.047,0,0,0% 100% 0% 0%,0.048
regex-dna,Python dev,5,10000,524,0.064,0,0,17% 86% 25% 0%,0.067
regex-dna,Python dev,5,10000,524,0.045,0,0,20% 0% 0% 100%,0.047
regex-dna,Python dev,5,10000,524,0.045,0,0,0% 0% 100% 0%,0.047
regex-dna,Cython,5,10000,524,0.048,0,0,100% 0% 0% 0%,0.049
regex-dna,Cython,5,10000,524,0.048,0,0,100% 20% 20% 0%,0.05
regex-dna,Cython,5,10000,524,0.047,0,0,0% 100% 0% 0%,0.049
regex-dna,Python 2,5,10000,501,0.033,0,0,0% 0% 25% 100%,0.035
regex-dna,Python 2,5,10000,501,0.031,0,0,0% 100% 0% 0%,0.033
regex-dna,Python 2,5,10000,501,0.032,0,0,0% 0% 100% 0%,0.033
regex-dna,IronPython,5,10000,501,0.698,46832,0,3% 29% 44% 32%,0.701
regex-dna,IronPython,5,10000,501,0.727,44844,0,8% 3% 100% 5%,0.728
regex-dna,IronPython,5,10000,501,0.732,45660,0,5% 100% 3% 6%,0.734
reverse-complement,Python 2,3,1000,431,0.013,0,0,%,0
reverse-complement,Python 2,3,1000,431,0.010,0,0,0% 0% 100% 0%,0.011
reverse-complement,Python 2,3,1000,431,0.010,0,0,0% 100% 0% 0%,0.011
reverse-complement,PyPy 3,5,1000,458,0.084,0,0,9% 10% 75% 0%,0.103
reverse-complement,PyPy 3,5,1000,458,0.083,0,0,0% 100% 0% 0%,0.084
reverse-complement,PyPy 3,5,1000,458,0.083,0,0,10% 0% 89% 0%,0.085
reverse-complement,Cython,4,1000,449,0.021,0,0,0% 0% 0% 100%,0.022
reverse-complement,Cython,4,1000,449,0.023,0,0,100% 50% 0% 50%,0.024
reverse-complement,Cython,4,1000,449,0.021,0,0,33% 0% 100% 0%,0.023
reverse-complement,Nuitka,6,1000,878,0.029,0,0,0% 100% 0% 0%,0.03
reverse-complement,Nuitka,6,1000,878,0.029,0,0,0% 0% 100% 0%,0.031
reverse-complement,Nuitka,6,1000,878,0.029,0,0,67% 0% 0% 0%,0.03
reverse-complement,Jython,4,1000,432,2.819,172892,0,83% 63% 50% 40%,1.234
reverse-complement,Jython,4,1000,432,2.727,134856,0,45% 51% 49% 83%,1.208
reverse-complement,Jython,4,1000,432,2.797,169836,0,46% 52% 39% 94%,1.243
reverse-complement,Python 3,4,1000,449,0.021,0,0,0% 0% 100% 0%,0.023
reverse-complement,Python 3,4,1000,449,0.021,0,0,0% 0% 100% 0%,0.022
reverse-complement,Python 3,4,1000,449,0.021,0,0,0% 0% 100% 33%,0.023
reverse-complement,Python dev,5,1000,458,0.021,0,0,0% 0% 0% 100%,0.023
reverse-complement,Python dev,5,1000,458,0.020,0,0,0% 0% 100% 0%,0.021
reverse-complement,Python dev,5,1000,458,0.020,0,0,33% 100% 0% 0%,0.022
reverse-complement,Pyston,5,1000,455,0.049,0,0,100% 0% 0% 17%,0.051
reverse-complement,Pyston,5,1000,455,0.049,0,0,100% 0% 0% 0%,0.05
reverse-complement,Pyston,5,1000,455,0.049,0,0,0% 0% 17% 100%,0.05
reverse-complement,Graal,6,1000,878,0.429,968,0,13% 92% 13% 3%,0.385
reverse-complement,Graal,6,1000,878,0.404,1024,0,0% 0% 100% 16%,0.372
reverse-complement,Graal,6,1000,878,0.407,908,0,3% 8% 100% 14%,0.376
reverse-complement,PyPy,5,1000,455,0.077,0,0,0% 0% 0% 100%,0.078
reverse-complement,PyPy,5,1000,455,0.079,0,0,13% 11% 100% 0%,0.08
reverse-complement,PyPy,5,1000,455,0.087,0,0,13% 40% 0% 100%,0.089
richards,PyPy 3,1,10,2434,0.264,1104,0,0% 93% 0% 4%,0.281
richards,PyPy 3,1,10,2434,0.266,1136,0,4% 4% 96% 0%,0.268
richards,PyPy 3,1,10,2434,0.271,1108,0,7% 4% 100% 7%,0.273
richards,Pyston,1,10,2423,0.317,2204,0,0% 16% 88% 3%,0.318
richards,Pyston,1,10,2423,0.317,2208,0,0% 97% 0% 0%,0.318
richards,Pyston,1,10,2423,0.317,2136,0,0% 0% 0% 97%,0.318
richards,Grumpy,1,10,2423,5.760,8248,0,29% 27% 31% 30%,5.358
richards,Grumpy,1,10,2423,5.753,8632,0,26% 35% 28% 30%,5.353
richards,Grumpy,1,10,2423,5.708,8276,0,28% 32% 26% 30%,5.306
richards,Cython,1,10,2467,0.739,8556,0,4% 1% 100% 3%,0.741
richards,Cython,1,10,2467,0.758,8568,0,1% 3% 99% 3%,0.76
richards,Cython,1,10,2467,0.730,8540,0,4% 100% 3% 3%,0.732
richards,Python 2,1,10,2423,1.138,7156,0,99% 3% 1% 3%,1.141
richards,Python 2,1,10,2423,1.121,7084,0,1% 2% 100% 0%,1.123
richards,Python 2,1,10,2423,1.113,7100,0,100% 0% 0% 3%,1.115
richards,PyPy,1,10,2423,0.258,1304,0,72% 8% 38% 21%,0.261
richards,PyPy,1,10,2423,0.241,1340,0,4% 100% 8% 9%,0.243
richards,PyPy,1,10,2423,0.243,1308,0,0% 96% 0% 0%,0.245
richards,IronPython,1,10,2423,6.652,63268,0,1% 83% 5% 8%,6.939
richards,IronPython,1,10,2423,6.489,63884,0,12% 1% 82% 6%,6.419
richards,IronPython,1,10,2423,6.496,63612,0,1% 1% 93% 7%,6.413
richards,MicroPython,1,10,2434,3.031,4068,0,1% 1% 100% 1%,3.034
richards,MicroPython,1,10,2434,3.044,4156,0,70% 2% 30% 0%,3.046
richards,MicroPython,1,10,2434,3.031,4056,0,1% 100% 0% 0%,3.033
richards,Nuitka,1,10,2434,0.701,9752,0,25% 1% 76% 1%,0.703
richards,Nuitka,1,10,2434,0.714,9536,0,0% 4% 1% 100%,0.716
richards,Nuitka,1,10,2434,0.689,9580,0,96% 0% 6% 1%,0.691
richards,Jython,1,10,2423,7.184,292192,0,60% 52% 65% 56%,3.101
richards,Jython,1,10,2423,6.953,284928,0,65% 56% 40% 61%,3.139
richards,Jython,1,10,2423,6.883,298504,0,58% 47% 81% 36%,3.105
richards,Python 3,1,10,2434,1.203,9028,0,11% 5% 99% 1%,1.206
richards,Python 3,1,10,2434,1.140,8968,0,4% 1% 99% 2%,1.143
richards,Python 3,1,10,2434,1.116,9068,0,6% 100% 2% 0%,1.118
richards,Graal,1,10,2434,11.076,469744,0,78% 68% 31% 48%,5.149
richards,Graal,1,10,2434,10.918,480468,0,75% 74% 27% 50%,5.073
richards,Graal,1,10,2434,12.769,501348,0,61% 76% 69% 46%,6.136
richards,Python dev,1,10,2434,1.095,9088,0,98% 1% 2% 3%,1.097
richards,Python dev,1,10,2434,1.111,9072,0,0% 100% 2% 0%,1.113
richards,Python dev,1,10,2434,1.084,9084,0,99% 1% 1% 1%,1.086
spectral-norm,PyPy 3,8,550,594,0.198,1132,0,0% 5% 90% 5%,0.216
spectral-norm,PyPy 3,8,550,594,0.199,0,0,0% 0% 100% 0%,0.2
spectral-norm,PyPy 3,8,550,594,0.199,0,0,0% 100% 0% 0%,0.2
spectral-norm,PyPy,8,550,594,0.197,0,0,5% 95% 5% 0%,0.199
spectral-norm,PyPy,8,550,594,0.198,0,0,5% 0% 5% 95%,0.2
spectral-norm,PyPy,8,550,594,0.193,0,0,11% 18% 0% 100%,0.195
spectral-norm,Python 3,2,550,394,0.127,0,0,100% 0% 0% 8%,0.135
spectral-norm,Python 3,2,550,394,0.118,0,0,8% 100% 8% 0%,0.12
spectral-norm,Python 3,2,550,394,0.119,0,0,14% 100% 15% 0%,0.121
spectral-norm,IronPython,8,550,594,3.976,57520,0,0% 63% 8% 24%,4.161
spectral-norm,IronPython,8,550,594,3.986,61472,0,92% 0% 1% 1%,4.177
spectral-norm,IronPython,8,550,594,4.003,57200,0,0% 92% 1% 1%,4.188
spectral-norm,Jython,8,550,594,8.366,297264,0,51% 45% 38% 38%,4.87
spectral-norm,Jython,8,550,594,8.075,294356,0,43% 34% 60% 31%,4.772
spectral-norm,Jython,8,550,594,8.405,294976,0,31% 64% 46% 29%,4.959
spectral-norm,Python 2,2,550,394,0.085,0,0,7% 29% 67% 7%,0.138
spectral-norm,Python 2,2,550,394,0.079,0,0,0% 0% 11% 100%,0.081
spectral-norm,Python 2,2,550,394,0.079,0,0,0% 13% 0% 89%,0.081
spectral-norm,Pyston,2,550,394,0.421,57532,0,0% 10% 83% 12%,0.423
spectral-norm,Pyston,2,550,394,0.420,55652,0,2% 0% 0% 100%,0.421
spectral-norm,Pyston,2,550,394,0.421,56036,0,0% 0% 0% 100%,0.421
spectral-norm,Python dev,2,550,394,0.117,0,0,8% 100% 0% 0%,0.119
spectral-norm,Python dev,2,550,394,0.117,0,0,100% 8% 0% 0%,0.118
spectral-norm,Python dev,2,550,394,0.120,0,0,8% 8% 100% 8%,0.121
spectral-norm,Nuitka,2,550,394,0.124,0,0,0% 0% 100% 0%,0.126
spectral-norm,Nuitka,2,550,394,0.125,0,0,100% 0% 0% 0%,0.126
spectral-norm,Nuitka,2,550,394,0.127,0,0,0% 0% 0% 100%,0.128
spectral-norm,Numba,1,550,663,0.923,84664,0,0% 3% 49% 48%,0.924
spectral-norm,Numba,1,550,663,0.906,84284,0,0% 0% 0% 100%,0.906
spectral-norm,Numba,1,550,663,0.927,83916,0,1% 0% 0% 99%,0.928
spectral-norm,Graal,8,550,594,1.668,395540,0,62% 44% 9% 24%,1.304
spectral-norm,Graal,8,550,594,1.695,394344,0,61% 37% 26% 12%,1.341
spectral-norm,Graal,8,550,594,1.663,394260,0,17% 50% 38% 32%,1.293
spectral-norm,MicroPython,6,550,498,7.015,4364,0,0% 1% 0% 100%,7.027
spectral-norm,MicroPython,6,550,498,7.001,4216,0,100% 0% 0% 0%,7.008
spectral-norm,MicroPython,6,550,498,7.000,4396,0,0% 100% 1% 0%,7.008
templates,Python dev,1,1000,322,1.038,19452,0,3% 97% 1% 1%,1.057
templates,Python dev,1,1000,322,1.053,19272,0,2% 1% 100% 1%,1.056
templates,Python dev,1,1000,322,1.031,19480,0,100% 0% 1% 0%,1.034
templates,Python 3,1,1000,322,1.093,19848,0,6% 1% 99% 1%,1.123
templates,Python 3,1,1000,322,1.062,19664,0,10% 100% 3% 3%,1.065
templates,Python 3,1,1000,322,1.067,19692,0,83% 26% 3% 6%,1.112
templates,Numba,1,1000,335,1.478,77492,0,88% 11% 1% 2%,1.498
templates,Numba,1,1000,335,1.456,77500,0,1% 5% 0% 95%,1.457
templates,Numba,1,1000,335,1.462,77320,0,1% 0% 0% 99%,1.462
templates,Cython,1,1000,328,1.058,19880,0,4% 2% 100% 3%,1.062
templates,Cython,1,1000,328,1.061,19988,0,2% 1% 99% 1%,1.065
templates,Cython,1,1000,328,1.071,19832,0,3% 100% 3% 5%,1.076
templates,Python 2,1,1000,307,1.073,15884,0,1% 99% 1% 0%,1.089
templates,Python 2,1,1000,307,1.068,15876,0,0% 2% 2% 99%,1.072
templates,Python 2,1,1000,307,1.090,15876,0,4% 4% 2% 100%,1.093
templates,Pyston,1,1000,307,1.856,58356,0,2% 5% 91% 3%,1.866
templates,Pyston,1,1000,307,1.854,58092,0,0% 1% 0% 100%,1.856
templates,Pyston,1,1000,307,1.846,58360,0,0% 100% 1% 1%,1.847
templates,PyPy,1,1000,307,2.817,98276,0,99% 2% 1% 2%,2.851
templates,PyPy,1,1000,307,2.838,98068,0,98% 3% 4% 2%,2.87
templates,PyPy,1,1000,307,2.831,96380,0,100% 2% 2% 4%,2.863
templates,Nuitka,1,1000,322,1.132,20380,0,0% 3% 0% 99%,1.177
templates,Nuitka,1,1000,322,1.131,20528,0,1% 3% 1% 100%,1.136
templates,Nuitka,1,1000,322,1.128,20356,0,4% 2% 100% 4%,1.131
templates,PyPy 3,1,1000,322,4.047,109212,0,100% 3% 3% 2%,4.086
templates,PyPy 3,1,1000,322,4.516,109540,0,67% 2% 35% 2%,4.553
templates,PyPy 3,1,1000,322,4.077,109404,0,1% 100% 2% 3%,4.112
thread-ring,Python 2,1,5000000,407,0.553,7068,0,98% 5% 0% 2%,0.555
thread-ring,Python 2,1,5000000,407,0.546,7052,0,0% 0% 100% 2%,0.548
thread-ring,Python 2,1,5000000,407,0.545,7060,0,100% 4% 0% 0%,0.546
thread-ring,PyPy 3,3,5000000,407,0.158,0,0,6% 100% 6% 0%,0.159
thread-ring,PyPy 3,3,5000000,407,0.155,0,0,0% 11% 100% 0%,0.157
thread-ring,PyPy 3,3,5000000,407,0.159,0,0,6% 0% 0% 100%,0.161
thread-ring,Cython,1,5000000,419,0.283,1892,0,7% 100% 7% 7%,0.285
thread-ring,Cython,1,5000000,419,0.281,1844,0,100% 3% 7% 4%,0.283
thread-ring,Cython,1,5000000,419,0.288,1828,0,100% 10% 7% 0%,0.29
thread-ring,Python 3,2,5000000,448,27.164,13224,0,31% 33% 26% 33%,21.462
thread-ring,Python 3,2,5000000,448,27.272,13308,0,34% 35% 27% 32%,21.748
thread-ring,Python 3,2,5000000,448,27.241,13344,0,31% 36% 27% 34%,21.635
thread-ring,Pyston,1,5000000,407,0.803,28536,0,6% 94% 1% 0%,0.805
thread-ring,Pyston,1,5000000,407,0.785,28624,0,0% 100% 0% 1%,0.786
thread-ring,Pyston,1,5000000,407,0.787,28572,0,0% 99% 0% 0%,0.788
thread-ring,IronPython,1,5000000,407,1.946,59312,0,3% 79% 13% 1%,2.036
thread-ring,IronPython,1,5000000,407,1.888,58920,0,2% 21% 62% 8%,2.047
thread-ring,IronPython,1,5000000,407,1.869,63780,0,60% 27% 2% 3%,2.032
thread-ring,Graal,3,5000000,407,1.930,405884,0,39% 63% 43% 3%,1.363
thread-ring,Graal,3,5000000,407,1.971,405904,0,88% 19% 11% 32%,1.376
thread-ring,Graal,3,5000000,407,1.940,405888,0,42% 53% 43% 12%,1.369
thread-ring,Nuitka,2,5000000,448,26.516,14136,0,32% 32% 36% 29%,19.506
thread-ring,Nuitka,2,5000000,448,26.087,14136,0,33% 21% 41% 28%,18.977
thread-ring,Nuitka,2,5000000,448,26.020,14024,0,30% 32% 31% 33%,18.998
thread-ring,Jython,1,5000000,407,4.413,222952,0,63% 72% 60% 48%,1.827
thread-ring,Jython,1,5000000,407,4.636,266428,0,55% 61% 74% 57%,1.882
thread-ring,Jython,1,5000000,407,4.523,270388,0,65% 66% 45% 66%,1.872
thread-ring,PyPy,1,5000000,407,0.144,0,0,6% 6% 88% 6%,0.163
thread-ring,PyPy,1,5000000,407,0.142,0,0,0% 100% 7% 7%,0.144
thread-ring,PyPy,1,5000000,407,0.141,0,0,0% 0% 0% 100%,0.142
thread-ring,Python dev,2,5000000,448,26.290,13240,0,27% 23% 27% 41%,20.196
thread-ring,Python dev,2,5000000,448,26.556,13164,0,25% 28% 35% 38%,20.321
thread-ring,Python dev,2,5000000,448,26.157,13012,0,24% 31% 30% 34%,19.916
thread-ring,MicroPython,2,5000000,448,23.327,6348,0,26% 28% 39% 23%,17.391
thread-ring,MicroPython,2,5000000,448,23.357,6344,0,24% 23% 38% 30%,17.471
thread-ring,MicroPython,2,5000000,448,23.717,6256,0,34% 18% 32% 29%,17.77
thread-ring,Grumpy,1,5000000,407,2.256,8248,0,30% 30% 26% 31%,2.119
thread-ring,Grumpy,1,5000000,407,2.228,8456,0,34% 22% 31% 28%,2.095
thread-ring,Grumpy,1,5000000,407,2.234,7752,0,26% 32% 27% 36%,2.099

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