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a/graphs/arch-x86-64/branch-master/cpu-i7-6700K/machine-i7-6700K/num_cpu-null/os-ubuntu-20.10/python-3.8/ram-16GB/codegen.TTI.time_forward.json b/graphs/arch-x86-64/branch-master/cpu-i7-6700K/machine-i7-6700K/num_cpu-null/os-ubuntu-20.10/python-3.8/ram-16GB/codegen.TTI.time_forward.json index 81f80b96..3c921185 100644 --- a/graphs/arch-x86-64/branch-master/cpu-i7-6700K/machine-i7-6700K/num_cpu-null/os-ubuntu-20.10/python-3.8/ram-16GB/codegen.TTI.time_forward.json +++ b/graphs/arch-x86-64/branch-master/cpu-i7-6700K/machine-i7-6700K/num_cpu-null/os-ubuntu-20.10/python-3.8/ram-16GB/codegen.TTI.time_forward.json @@ -1 +1 @@ -[[11970, 6.105075881999937], [12036, 6.036832682904787], [12039, 6.016281103948131], [12156, 6.061072713579051], [12159, 6.512085993075743], [12162, 6.772758020088077], [12166, 6.576192567474209], [12207, 6.4946837189999655], [12211, 7.1461984049965395], [12215, 7.1594730464858], [12218, 7.428106535488041], [12224, 7.3196506169915665], [12228, 6.639583139505703], 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"IntelXeon8168", "machine": "F8s_v2", "num_cpu": "8", "os": "ubuntu-18.04", "ram": "16GB", "python": "3.6", "branch": "master"}, {"arch": "x86-64", "cpu": "i7-6700K", "machine": "i7-6700K", "os": "ubuntu-20.10", "ram": "16GB", "python": "3.8", "branch": "master", "num_cpu": null}, {"arch": "x86-64", "cpu": "i7-6700K", "machine": "i7-6700K", "os": "ubuntu-20.10", "ram": "16GB", "python": "3.10", "branch": "master", "num_cpu": null}], "benchmarks": {"acoustic.IsotropicAcoustic.time_forward": {"code": "class IsotropicAcoustic:\n def time_forward(self, shape, space_order):\n self.solver.forward(x0_blk0_size=IsotropicAcoustic.x0_blk0_size,\n y0_blk0_size=IsotropicAcoustic.y0_blk0_size,\n time_M=50)\n\n def setup(self, shape, space_order):\n self.solver = acoustic_setup(shape=shape, space_order=space_order,\n opt=('advanced', {'openmp': True}))", "min_run_count": 2, "name": "acoustic.IsotropicAcoustic.time_forward", "number": 0, "param_names": ["shape", "space_order"], "params": [["(492, 492, 492)"], ["12"]], "repeat": 3, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "f8ca35d4df15942c3d0503d30af68493596ed84c3960fc10c4d50b767e79196f", "warmup_time": -1}, "arguments.Processing.time_processing": {"code": "class Processing:\n def time_processing(self):\n self.op.arguments(time_M=98)\n\n def setup(self):\n grid = Grid(shape=(5, 5, 5))\n \n funcs = [Function(name='f%d' % n, grid=grid) for n in range(30)]\n tfuncs = [TimeFunction(name='u%d' % n, grid=grid) for n in range(30)]\n stfuncs = [SparseTimeFunction(name='su%d' % n, grid=grid, npoint=1, nt=100)\n for n in range(30)]\n v = TimeFunction(name='v', grid=grid, space_order=2)\n \n eq = Eq(v.forward, v.laplace + sum(funcs) + sum(tfuncs) + sum(stfuncs),\n subdomain=grid.interior)\n \n self.op = Operator(eq, opt='noop')\n \n # Allocate data, populate cached properties, etc.\n self.op.arguments(time_M=98)", "min_run_count": 2, "name": "arguments.Processing.time_processing", "number": 0, "param_names": [], "params": [], "repeat": 10, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "5c7e2bf7664e8e05e93bf30259bae2cfeb172ba770526c14b2c8558dccf3bde1", "warmup_time": -1}, "codegen.TTI.time_adjoint": {"code": "class TTI:\n def time_adjoint(self):\n self.solver.op_adj()\n\n def setup(self):\n self.solver = tti_setup(space_order=TTI.space_order)", "min_run_count": 2, "name": "codegen.TTI.time_adjoint", "number": 0, "param_names": [], "params": [], "repeat": 1, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "792c265ef3a829b1d897ea464b5694e2b3529736fd92aedcb7713714b6aad671", "warmup_time": -1}, "codegen.TTI.time_forward": {"code": "class TTI:\n def time_forward(self):\n self.solver.op_fwd()\n\n def setup(self):\n self.solver = tti_setup(space_order=TTI.space_order)", "min_run_count": 2, "name": "codegen.TTI.time_forward", "number": 0, "param_names": [], "params": [], "repeat": 1, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "2edfcba3adca42090ac1dc38625050a7c78bad56fe1b3a4e24b71957ffc758a5", "warmup_time": -1}, "simple_operators.time_basic": {"code": "def time_basic():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid)\n\n op = Operator(Eq(f.forward, f + 1))\n\n op.apply(time_M=100)", "min_run_count": 2, "name": "simple_operators.time_basic", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "19da0630eea256a3d1f0809a124e82601ddb1967a7c8719ea5886f0ab6d6708f", "warmup_time": -1}, "simple_operators.time_gaussian_smoother": {"code": "def time_gaussian_smoother():\n grid = Grid(shape=(400, 400, 400))\n\n f = Function(name='f', grid=grid, space_order=12)\n\n gaussian_smooth(f, sigma=0.5)", "min_run_count": 2, "name": "simple_operators.time_gaussian_smoother", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7abb634ac37c967e173f4450f9dc1090a382e2bc61d798a300ce63502b4c9866", "warmup_time": -1}, "simple_operators.time_laplacian": {"code": "def time_laplacian():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid, space_order=2)\n\n op = Operator(Eq(f.forward, 1e-8*(f.laplace + 1)))\n\n op.apply(time_M=100)", "min_run_count": 2, "name": "simple_operators.time_laplacian", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "c4d5e7a640a02bc53f2cb9d04a424c0bdc8f5b45d1e171c987c80c8e5c9066f9", "warmup_time": -1}, "simple_operators.time_norm": {"code": "def time_norm():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid, space_order=2)\n\n norm(f)", "min_run_count": 2, "name": "simple_operators.time_norm", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "09ab2f25734f0c8be412feb02f7c5e174c068bee3b0b7fcaddc93351240eae29", "warmup_time": -1}}, "machines": {"F8s_v2": {"arch": "x86-64", "cpu": "IntelXeon8168", "machine": "F8s_v2", "num_cpu": "8", "os": "ubuntu-18.04", "ram": "16GB", "version": 1}, "i7-6700K": {"arch": "x86-64", "cpu": "i7-6700K", "machine": "i7-6700K", "os": "ubuntu-20.10", "ram": "16GB", "version": 1}}, "tags": {"3.0.1": 2094, "dft-paper": 4705, "v2.0.1": 1231, "v3.0.0": 1939, "v3.0.2": 2174, "v3.0.3": 2730, "v3.1.0": 3067, "v3.2-beta": 3933, "v3.2.0": 4428, "v3.3": 5570, "v3.4": 6447, "v3.5": 8295, "v4.0": 8931, "v4.1": 9595, "v4.2": 10406, "v4.2.1": 10627, "v4.2.2": 10904, "v4.2.3": 11411, "v4.3": 12224, "v4.3-beta": 12218, "v4.4": 12767, "v4.5": 13300, "v4.6": 13568, "v4.6.1": 13950, "v4.6.2": 14035, "v4.7.0": 14850, "v4.7.1": 14853, "v4.8.0": 15497, "v4.8.1": 15726, "v4.8.10": 17996, "v4.8.11": 18100, "v4.8.2": 16428, "v4.8.4": 17538, "v4.8.5": 17540, "v4.8.6": 17555, "v4.8.7": 17815, "v4.8.8": 17900, "v4.8.9": 17972, "v4.8.3": 16762}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file +{"project": "devito", "project_url": "http://devitoproject.org/", "show_commit_url": "http://github.com/devitocodes/devito/commit/", "hash_length": 8, "revision_to_hash": {"1231": "7d152b0de10cccf3ef97fafba29cb6ade5dc3cdf", "1939": "e8da8ef68ec7c7f723832602e9c41fca47bc2e45", "2094": "dc75e38303b369e3dfd409302b048cbf948cab85", "2174": "d044efc2cbf589804d9944ea24c88f85502b3a47", "2730": "c98ac370cbdc0e7a18ae471f9864657ec306c86a", "3067": "be3a4516b3fc8d83880243228c31a253f704f7d9", "3933": "2792096105203bc5af1631a7882465355ba1ad2f", "4428": "12126fcc059cf84e5e9c137082603e9ac85dd60e", "4705": "932c067df4b25ad748c617e3a09fc0c7d57469df", "5570": 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"17802": 1717514968000, "17805": 1717682379000, "17810": 1717783145000, "17887": 1719409850000, "17906": 1719558786000, "17913": 1719862902000, "17916": 1719876324000, "17936": 1720444026000, "17949": 1720458463000, "17956": 1720553029000, "17959": 1720607382000, "17973": 1720627582000, "17983": 1720726639000, "18018": 1720805770000, "18023": 1721117974000, "18035": 1721151874000, "18047": 1721233411000, "18051": 1721253478000, "18054": 1721268497000, "18058": 1721633552000, "18065": 1721651999000, "18066": 1721652304000, "18070": 1721663380000, "18073": 1721834871000, "18077": 1721845104000, "18081": 1721916637000, "18086": 1721995105000, "18090": 1722007067000, "18096": 1722258931000, "18181": 1722498260000}, "params": {"arch": ["x86-64"], "cpu": ["IntelXeon8168", "i7-6700K"], "machine": ["F8s_v2", "i7-6700K"], "num_cpu": ["8", null], "os": ["ubuntu-18.04", "ubuntu-20.10"], "ram": ["16GB"], "python": ["3.10", "3.6", "3.8"], "branch": ["master"]}, "graph_param_list": [{"arch": "x86-64", "cpu": "IntelXeon8168", "machine": "F8s_v2", "num_cpu": "8", "os": "ubuntu-18.04", "ram": "16GB", "python": "3.6", "branch": "master"}, {"arch": "x86-64", "cpu": "i7-6700K", "machine": "i7-6700K", "os": "ubuntu-20.10", "ram": "16GB", "python": "3.8", "branch": "master", "num_cpu": null}, {"arch": "x86-64", "cpu": "i7-6700K", "machine": "i7-6700K", "os": "ubuntu-20.10", "ram": "16GB", "python": "3.10", "branch": "master", "num_cpu": null}], "benchmarks": {"acoustic.IsotropicAcoustic.time_forward": {"code": "class IsotropicAcoustic:\n def time_forward(self, shape, space_order):\n self.solver.forward(x0_blk0_size=IsotropicAcoustic.x0_blk0_size,\n y0_blk0_size=IsotropicAcoustic.y0_blk0_size,\n time_M=50)\n\n def setup(self, shape, space_order):\n self.solver = acoustic_setup(shape=shape, space_order=space_order,\n opt=('advanced', {'openmp': True}))", "min_run_count": 2, "name": "acoustic.IsotropicAcoustic.time_forward", "number": 0, "param_names": ["shape", "space_order"], "params": [["(492, 492, 492)"], ["12"]], "repeat": 3, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "f8ca35d4df15942c3d0503d30af68493596ed84c3960fc10c4d50b767e79196f", "warmup_time": -1}, "arguments.Processing.time_processing": {"code": "class Processing:\n def time_processing(self):\n self.op.arguments(time_M=98)\n\n def setup(self):\n grid = Grid(shape=(5, 5, 5))\n \n funcs = [Function(name='f%d' % n, grid=grid) for n in range(30)]\n tfuncs = [TimeFunction(name='u%d' % n, grid=grid) for n in range(30)]\n stfuncs = [SparseTimeFunction(name='su%d' % n, grid=grid, npoint=1, nt=100)\n for n in range(30)]\n v = TimeFunction(name='v', grid=grid, space_order=2)\n \n eq = Eq(v.forward, v.laplace + sum(funcs) + sum(tfuncs) + sum(stfuncs),\n subdomain=grid.interior)\n \n self.op = Operator(eq, opt='noop')\n \n # Allocate data, populate cached properties, etc.\n self.op.arguments(time_M=98)", "min_run_count": 2, "name": "arguments.Processing.time_processing", "number": 0, "param_names": [], "params": [], "repeat": 10, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "5c7e2bf7664e8e05e93bf30259bae2cfeb172ba770526c14b2c8558dccf3bde1", "warmup_time": -1}, "codegen.TTI.time_adjoint": {"code": "class TTI:\n def time_adjoint(self):\n self.solver.op_adj()\n\n def setup(self):\n self.solver = tti_setup(space_order=TTI.space_order)", "min_run_count": 2, "name": "codegen.TTI.time_adjoint", "number": 0, "param_names": [], "params": [], "repeat": 1, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "792c265ef3a829b1d897ea464b5694e2b3529736fd92aedcb7713714b6aad671", "warmup_time": -1}, "codegen.TTI.time_forward": {"code": "class TTI:\n def time_forward(self):\n self.solver.op_fwd()\n\n def setup(self):\n self.solver = tti_setup(space_order=TTI.space_order)", "min_run_count": 2, "name": "codegen.TTI.time_forward", "number": 0, "param_names": [], "params": [], "repeat": 1, "rounds": 2, "sample_time": 0.01, "timeout": 600.0, "type": "time", "unit": "seconds", "version": "2edfcba3adca42090ac1dc38625050a7c78bad56fe1b3a4e24b71957ffc758a5", "warmup_time": -1}, "simple_operators.time_basic": {"code": "def time_basic():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid)\n\n op = Operator(Eq(f.forward, f + 1))\n\n op.apply(time_M=100)", "min_run_count": 2, "name": "simple_operators.time_basic", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "19da0630eea256a3d1f0809a124e82601ddb1967a7c8719ea5886f0ab6d6708f", "warmup_time": -1}, "simple_operators.time_gaussian_smoother": {"code": "def time_gaussian_smoother():\n grid = Grid(shape=(400, 400, 400))\n\n f = Function(name='f', grid=grid, space_order=12)\n\n gaussian_smooth(f, sigma=0.5)", "min_run_count": 2, "name": "simple_operators.time_gaussian_smoother", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "7abb634ac37c967e173f4450f9dc1090a382e2bc61d798a300ce63502b4c9866", "warmup_time": -1}, "simple_operators.time_laplacian": {"code": "def time_laplacian():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid, space_order=2)\n\n op = Operator(Eq(f.forward, 1e-8*(f.laplace + 1)))\n\n op.apply(time_M=100)", "min_run_count": 2, "name": "simple_operators.time_laplacian", "number": 0, "param_names": [], "params": [], "repeat": 3, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "c4d5e7a640a02bc53f2cb9d04a424c0bdc8f5b45d1e171c987c80c8e5c9066f9", "warmup_time": -1}, "simple_operators.time_norm": {"code": "def time_norm():\n grid = Grid(shape=(400, 400, 400))\n\n f = TimeFunction(name='f', grid=grid, space_order=2)\n\n norm(f)", "min_run_count": 2, "name": 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