Author: Hakan Ardo <[email protected]> Branch: extradoc Changeset: r4578:7ccd112ce9cb Date: 2012-08-15 09:23 +0200 http://bitbucket.org/pypy/extradoc/changeset/7ccd112ce9cb/
Log: preliminary results diff --git a/talk/iwtc11/benchmarks/result.txt b/talk/iwtc11/benchmarks/result.txt --- a/talk/iwtc11/benchmarks/result.txt +++ b/talk/iwtc11/benchmarks/result.txt @@ -1,129 +1,189 @@ pypy -sqrt(float): 1.20290899277 - sqrt(int): 2.41840982437 -sqrt(Fix16): 6.10620713234 -conv3(1e8): 2.5192759037 -conv5(1e8): 2.89429306984 -conv3(1e6): 0.828789949417 -conv5(1e6): 1.01669406891 -conv3(1e5): 0.777491092682 -conv5(1e5): 0.971807956696 -conv3x3(3): 0.653658866882 -conv3x3(1000): 0.748742103577 -dilate3x3(1000): 4.8826611042 -NoBorderImagePadded: 2.31043601036 -NoBorderImagePadded(iter): 0.572638988495 -NoBorderImagePadded(range): 0.494098186493 -NoBorderImage: 2.90333104134 -NoBorderImage(iter): 2.06943392754 -NoBorderImage(range): 1.99161696434 -sobel(NoBorderImagePadded): 0.668392896652 +sqrt(int): 3.9497149229 +- 0.00120169176702 +sqrt(float): 1.18568074703 +- 0.000155574177096 +sqrt(Fix16): 4.33989310265 +- 0.00141233338935 +conv3(array(1e6)): 0.509183955193 +- 0.0118453357313 +conv5(array(1e6)): 0.69121158123 +- 0.00750138546764 +conv3(array(1e5)): 0.4399548769 +- 0.00179808936191 +conv5(array(1e5)): 0.641533112526 +- 0.00283121562299 +conv3x3(Array2D(1000000x3)): 0.32311899662 +- 0.00297940582696 +conv3x3(Array2D(1000x1000)): 0.294556212425 +- 0.00394363604342 +dilate3x3(Array2D(1000x1000)): 5.62028222084 +- 0.0100742850395 +sobel(Array2D(1000x1000)): 0.353349781036 +- 0.000422230713013 +SOR(100, 32768): 3.6967458725 +- 0.00479411350316 +SOR(1000, 256): 2.92602846622 +- 0.00460152567878 +SOR(100, 32768): 5.91232867241 +- 0.0575417343725 +SOR(1000, 256): 4.48931508064 +- 0.0545822457385 +SparseMatMult(1000, 5000, 262144): 45.573383832 +- 0.628020354674 +SparseMatMult(100000, 1000000, 1024): 31.8840100527 +- 0.0835424264131 +MonteCarlo(268435456): 18.0108832598 +- 0.0590538416431 +LU(100, 4096): 17.11741395 +- 0.146651016873 +LU(1000, 2): 8.36587500572 +- 0.0643368943091 -pypy --jit enable_opts=intbounds:rewrite:virtualize:heap:unroll -sqrt(float): 1.19338798523 - sqrt(int): 2.42711806297 -sqrt(Fix16): 6.12403416634 -conv3(1e8): 2.06937193871 -conv5(1e8): 2.26879811287 -conv3(1e6): 0.837247848511 -conv5(1e6): 1.02573990822 -conv3(1e5): 0.779927015305 -conv5(1e5): 0.975258827209 -conv3x3(3): 0.663229942322 -conv3x3(1000): 0.763913154602 -dilate3x3(1000): 4.80735611916 -NoBorderImagePadded: 2.33380198479 -NoBorderImagePadded(iter): 0.504709005356 -NoBorderImagePadded(range): 0.503198862076 -NoBorderImage: 2.93766593933 -NoBorderImage(iter): 2.04195189476 -NoBorderImage(range): 2.02779984474 -sobel(NoBorderImagePadded): 0.670017004013 +pypy --jit enable_opts=intbounds:rewrite:virtualize:string:earlyforce:pure:heap:ffi +sqrt(int): 5.38412702084 +- 0.0100677718267 +sqrt(float): 2.49882881641 +- 0.000611829128708 +sqrt(Fix16): 9.08926799297 +- 0.00638996685205 +conv3(array(1e6)): 2.07706921101 +- 0.0578137268002 +conv5(array(1e6)): 2.29385373592 +- 0.239051363255 +conv3(array(1e5)): 1.9695744276 +- 0.00699373341986 +conv5(array(1e5)): 2.06334021091 +- 0.00461312422073 +conv3x3(Array2D(1000000x3)): 0.913360571861 +- 0.00406856919645 +conv3x3(Array2D(1000x1000)): 0.906745815277 +- 0.011800811341 +dilate3x3(Array2D(1000x1000)): 5.94119987488 +- 0.0177689080267 +sobel(Array2D(1000x1000)): 0.879287624359 +- 0.00351199656947 +SOR(100, 32768): 13.3457442522 +- 0.15597493782 +SOR(1000, 256): 10.6485268593 +- 0.0335292228831 +SOR(100, 32768): 15.2722632885 +- 0.149270948773 +SOR(1000, 256): 12.2542063951 +- 0.0467913588079 +SparseMatMult(1000, 5000, 262144): 51.7010503292 +- 0.0900830635215 +SparseMatMult(100000, 1000000, 1024): 34.0754101276 +- 0.0854521241748 +MonteCarlo(268435456): 27.4164168119 +- 0.00974970184296 +LU(100, 4096): 48.2948143244 +- 0.509639206256 +LU(1000, 2): 24.4584824085 +- 0.0807806236077 -pypy --jit enable_opts=intbounds:rewrite:virtualize:heap -sqrt(float): 1.69957995415 - sqrt(int): 3.13235807419 -sqrt(Fix16): 10.325592041 -conv3(1e8): 2.997631073 -conv5(1e8): 3.13820099831 -conv3(1e6): 1.7843170166 -conv5(1e6): 1.94643998146 -conv3(1e5): 1.75876712799 -conv5(1e5): 1.96709895134 -conv3x3(3): 1.09958791733 -conv3x3(1000): 1.02993702888 -dilate3x3(1000): 5.22873902321 -NoBorderImagePadded: 2.45174002647 -NoBorderImagePadded(iter): 1.60747289658 -NoBorderImagePadded(range): 1.55282211304 -NoBorderImage: 2.91020989418 -NoBorderImage(iter): 1.97922706604 -NoBorderImage(range): 2.14161992073 -sobel(NoBorderImagePadded): 1.47591900826 +pypy-1.5 +sqrt(int): 4.01375324726 +- 0.0011476694851 +sqrt(float): 1.18687217236 +- 0.000301798978394 +sqrt(Fix16): 4.86933817863 +- 0.00205854686543 +conv3(array(1e6)): 0.805051374435 +- 0.0063356172758 +conv5(array(1e6)): 1.06881151199 +- 0.166557589133 +conv3(array(1e5)): 0.767954874039 +- 0.00310620949945 +conv5(array(1e5)): 0.965079665184 +- 0.000806628058215 +conv3x3(Array2D(1000000x3)): 0.335144019127 +- 0.00049856745349 +conv3x3(Array2D(1000x1000)): 0.29465200901 +- 0.000517387744409 +dilate3x3(Array2D(1000x1000)): 4.75037336349 +- 0.0580217877578 +sobel(Array2D(1000x1000)): 0.663321614265 +- 0.122793251782 +SOR(100, 32768): 4.81084053516 +- 0.00994169505717 +SOR(1000, 256): 3.69062592983 +- 0.000879615350989 +SparseMatMult(1000, 5000, 262144): 29.4872629166 +- 0.10046773485 +SparseMatMult(100000, 1000000, 1024): 16.4197937727 +- 0.0719696247072 +MonteCarlo(268435456): 33.0701499462 +- 0.0638672466435 -gcc -sqrt(float): 1.43 -sqrt(int): 1.93 -sqrt(Fix16): 2.04 -conv3(1e8): 2.03 -conv5(1e8): 2.39 -conv3(1e6): 1.66 -conv5(1e6): 2.03 -conv3(1e5): 1.60 -conv5(1e5): 2.02 -conv3x3(3): 1.81 -conv3x3(1000): 1.79 -dilate3x3(1000): 3.26 -sobel_magnitude: 1.37 +pypy-1.5 --jit enable_opts=intbounds:rewrite:virtualize:heap +sqrt(int): 4.90680310726 +- 0.0163989281435 +sqrt(float): 1.76404910088 +- 0.019897073087 +sqrt(Fix16): 9.64484581947 +- 0.114181653484 +conv3(array(1e6)): 2.09028859138 +- 0.0553368910699 +conv5(array(1e6)): 1.98986980915 +- 0.0147589410577 +conv3(array(1e5)): 2.03130574226 +- 0.0153185288294 +conv5(array(1e5)): 1.95361895561 +- 0.00846210060946 +conv3x3(Array2D(1000000x3)): 0.771404409409 +- 0.00438046479707 +conv3x3(Array2D(1000x1000)): 0.724743962288 +- 0.00330094765836 +dilate3x3(Array2D(1000x1000)): 4.96963682175 +- 0.00698590266664 +sobel(Array2D(1000x1000)): 1.63008458614 +- 1.3629432655 +SOR(100, 32768): 13.871041584 +- 0.0322488434431 +SOR(1000, 256): 11.9500208616 +- 0.00961527429654 +SparseMatMult(1000, 5000, 262144): 37.7395636082 +- 0.108390387625 +SparseMatMult(100000, 1000000, 1024): 27.7381374121 +- 0.105548816891 +MonteCarlo(268435456): 30.6472777128 +- 0.0437974003055 -gcc -O2 -sqrt(float): 1.15 -sqrt(int): 1.86 -sqrt(Fix16): 1.89 -conv3(1e8): 1.22 -conv5(1e8): 1.37 -conv3(1e6): 1.00 -conv5(1e6): 1.04 -conv3(1e5): 0.81 -conv5(1e5): 0.97 -conv3x3(3): 0.25 -conv3x3(1000): 0.23 -dilate3x3(1000): 0.27 -sobel_magnitude: 0.25 - -gcc -O3 -march=native -sqrt(float): 1.15 -sqrt(int): 1.82 -sqrt(Fix16): 1.89 -conv3(1e8): 1.12 -conv5(1e8): 1.16 -conv3(1e6): 0.96 -conv5(1e6): 0.97 -conv3(1e5): 0.66 -conv5(1e5): 0.75 -conv3x3(3): 0.23 -conv3x3(1000): 0.21 -dilate3x3(1000): 0.26 -sobel_magnitude: 0.25 +gcc -O3 -march=native -fno-tree-vectorize +sqrt(float): 1.14 +- 0.0 +sqrt(int): 1.85 +- 0.0 +sqrt(Fix16): 1.992 +- 0.004472135955 +conv3(1e6): 1.066 +- 0.00547722557505 +conv5(1e6): 1.104 +- 0.00547722557505 +conv3(1e5): 0.75 +- 0.0 +conv5(1e5): 1.03 +- 0.0 +conv3x3(3): 0.22 +- 3.10316769156e-17 +conv3x3(1000): 0.2 +- 0.0 +dilate3x3(1000): 0.2 +- 0.0 +SOR(100,32768): 2.506 +- 0.00547722557505 +SOR(1000,256): 2.072 +- 0.004472135955 +SparseMatMult(1000,5000,262144): 2.54 +- 0.0 +SparseMatMult(100000,1000000,1024): 2.398 +- 0.004472135955 +MonteCarlo(268435456): 2.52 +- 0.0 +LU(100,4096): 1.882 +- 0.004472135955 +LU(1000,2): 2.036 +- 0.00547722557505 python2.7 -sqrt(float): 34.9008591175 - sqrt(int): 19.6919620037 -sqrt(Fix16): 966.111785889 -conv3(1e8): 69.0758299828 -conv5(1e8): 101.503945827 -conv3(1e6): 62.212736845 -conv5(1e6): 93.5375850201 -conv3(1e5): 61.4343979359 -conv5(1e5): 93.6144771576 -conv3x3(3): 198.12590003 -conv3x3(1000): 193.030704975 -dilate3x3(1000): 192.323596954 -NoBorderImagePadded: 512.473811865 -NoBorderImagePadded(iter): 503.393321991 -NoBorderImagePadded(range): 493.907886028 -NoBorderImage: 501.37309289 -NoBorderImage(iter): 495.473101139 -NoBorderImage(range): 493.572232008 -sobel(NoBorderImagePadded): 433.678281069 +sqrt(int): 15.5302910805 +sqrt(float): 19.8081839085 +sqrt(Fix16): 690.281599045 +conv3(array(1e6)): 58.9430649281 +conv5(array(1e6)): 88.9902608395 +conv3(array(1e5)): 60.0520131588 +conv5(array(1e5)): 88.7499320507 +conv3x3(Array2D(1000000x3)): 182.564875841 +conv3x3(Array2D(1000x1000)): 179.802839994 +dilate3x3(Array2D(1000x1000)): 177.197051048 +sobel(Array2D(1000x1000)): 132.991428852 +SOR(100, 32768): 1854.50835085 +SOR(1000, 256): 1506.28460383 +SOR(100, 32768): 1279.75841594 +SOR(1000, 256): 1038.63221002 +SparseMatMult(1000, 5000, 262144): 456.105548859 +SparseMatMult(100000, 1000000, 1024): 272.003329039 +MonteCarlo(268435456): 800.114681005 +LU(100, 4096): 2704.15891314 +LU(1000, 2): 1317.06345105 + +python2.6 psyco-wrapper.py + +luajit-2.0.0-beta10 +sqrt(int): 1.185000 +- 0.005270 +sqrt(float): 1.185000 +- 0.005270 +sqrt(Fix16): 106.936000 +- 0.350213 +convolution(conv3): 0.476000 +- 0.005164 +convolution(conv5): 0.478000 +- 0.012293 +convolution(conv3): 0.172000 +- 0.006325 +convolution(conv5): 0.286000 +- 0.005164 +convolution(conv3x3): 0.207000 +- 0.004830 +convolution(conv3x3): 0.167000 +- 0.006749 +convolution(dilate3x3): 0.165000 +- 0.005270 +convolution(sobel_magnitude): 0.398000 +- 0.006325 +SOR(100, 32768): 2.186000 +- 0.005164 +SOR(1000, 256): 1.797000 +- 0.006749 +SparseMatMult(1000,5000,262144): 6.642000 +- 0.049621 +SparseMatMult(100000,1000000,1024): 3.846000 +- 0.023664 +MonteCarlo(268435456): 4.082000 +- 0.004216 +LU(100, 4096): 2.371000 +- 0.019120 +LU(1000, 2): 2.141000 +- 0.037550 +FFT(1024, 32768): 3.900000 +- 0.010541 +FFT(1048576, 2): 2.815000 +- 0.142848 + +luajit-2.0.0-beta10 -O-loop +sqrt(int): 1.462000 +- 0.004216 +sqrt(float): 1.462000 +- 0.004216 +sqrt(Fix16): 102.775000 +- 0.332106 +convolution(conv3): 0.950000 +- 0.006667 +convolution(conv5): 1.219000 +- 0.077093 +convolution(conv3): 0.894000 +- 0.005164 +convolution(conv5): 1.150000 +- 0.004714 +convolution(conv3x3): 0.734000 +- 0.005164 +convolution(conv3x3): 0.691000 +- 0.007379 +convolution(dilate3x3): 0.710000 +- 0.012472 +convolution(sobel_magnitude): 0.833000 +- 0.009487 +SOR(100, 32768): 2.727000 +- 0.004830 +SOR(1000, 256): 2.264000 +- 0.005164 +SparseMatMult(1000,5000,262144): 13.485000 +- 0.235384 +SparseMatMult(100000,1000000,1024): 10.869000 +- 0.014491 +MonteCarlo(268435456): 5.943000 +- 0.006749 +LU(100, 4096): 11.064000 +- 0.019551 +LU(1000, 2): 5.109000 +- 0.005676 +FFT(1024, 32768): 5.999000 +- 0.007379 +FFT(1048576, 2): 2.997000 +- 0.137602 + +luajit-master +sqrt(int): 1.185000 +- 0.005270 +sqrt(float): 1.185000 +- 0.005270 +sqrt(Fix16): 1.739000 +- 0.003162 +convolution(conv3): 0.477000 +- 0.008233 +convolution(conv5): 0.474000 +- 0.005164 +convolution(conv3): 0.165000 +- 0.005270 +convolution(conv5): 0.286000 +- 0.005164 +convolution(conv3x3): 0.207000 +- 0.004830 +convolution(conv3x3): 0.167000 +- 0.006749 +convolution(dilate3x3): 0.163000 +- 0.006749 +convolution(sobel_magnitude): 0.403000 +- 0.009487 +SOR(100, 32768): 2.187000 +- 0.006749 +SOR(1000, 256): 1.802000 +- 0.006325 +SparseMatMult(1000,5000,262144): 6.683000 +- 0.029833 +SparseMatMult(100000,1000000,1024): 3.870000 +- 0.037712 +MonteCarlo(268435456): 4.035000 +- 0.005270 +LU(100, 4096): 2.351000 +- 0.008756 +LU(1000, 2): 2.107000 +- 0.018288 +FFT(1024, 32768): 3.926000 +- 0.010750 +FFT(1048576, 2): 2.865000 +- 0.064334 diff --git a/talk/iwtc11/benchmarks/runall.sh b/talk/iwtc11/benchmarks/runall.sh --- a/talk/iwtc11/benchmarks/runall.sh +++ b/talk/iwtc11/benchmarks/runall.sh @@ -12,4 +12,5 @@ ./benchmark.sh python2.6 psyco-wrapper.py ./benchmark.sh luajit-2.0.0-beta10 ./benchmark.sh luajit-2.0.0-beta10 -O-loop -./benchmakr.sh luajit +./benchmark.sh luajit-master +./benchmark.sh luajit _______________________________________________ pypy-commit mailing list [email protected] http://mail.python.org/mailman/listinfo/pypy-commit
