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root@547a227b1517:~/numba-examples# numba_bench -o results -r gpu
Scanning /root/numba-examples for benchmarks
Writing results to /root/numba-examples/results
/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py:54: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
config = yaml.load(f)
Running Histogram [/root/numba-examples/examples/density_estimation/histogram]
numpy: bins10, float32 - 1000 => 3 reps, 1000 iter per rep, 169.493665 usec per call
numba: bins10, float32 - 1000 => 3 reps, 10000 iter per rep, 15.088746 usec per call
numba_gpu: bins10, float32 - 1000 => 3 reps, 100 iter per rep, 1593.281750 usec per call
numpy: bins10, float32 - 10000 => 3 reps, 1000 iter per rep, 265.618970 usec per call
numba: bins10, float32 - 10000 => 3 reps, 1000 iter per rep, 141.332854 usec per call
numba_gpu: bins10, float32 - 10000 => 3 reps, 100 iter per rep, 1603.700330 usec per call
numpy: bins10, float32 - 100000 => 3 reps, 100 iter per rep, 1179.389010 usec per call
numba: bins10, float32 - 100000 => 3 reps, 100 iter per rep, 1402.002540 usec per call
numba_gpu: bins10, float32 - 100000 => 3 reps, 100 iter per rep, 1681.287160 usec per call
numpy: bins10, float32 - 300000 => 3 reps, 100 iter per rep, 3271.321700 usec per call
numba: bins10, float32 - 300000 => 3 reps, 100 iter per rep, 4213.909610 usec per call
numba_gpu: bins10, float32 - 300000 => 3 reps, 100 iter per rep, 1949.394360 usec per call
numpy: bins10, float32 - 3000000 => 3 reps, 10 iter per rep, 32000.128600 usec per call
numba: bins10, float32 - 3000000 => 3 reps, 10 iter per rep, 42029.814400 usec per call
numba_gpu: bins10, float32 - 3000000 => 3 reps, 100 iter per rep, 4975.962050 usec per call
numpy: bins10, float64 - 1000 => 3 reps, 1000 iter per rep, 160.448296 usec per call
numba: bins10, float64 - 1000 => 3 reps, 10000 iter per rep, 14.967072 usec per call
numba_gpu: bins10, float64 - 1000 => 3 reps, 100 iter per rep, 1591.028610 usec per call
numpy: bins10, float64 - 10000 => 3 reps, 1000 iter per rep, 273.850549 usec per call
numba: bins10, float64 - 10000 => 3 reps, 1000 iter per rep, 137.559821 usec per call
numba_gpu: bins10, float64 - 10000 => 3 reps, 100 iter per rep, 1585.167370 usec per call
numpy: bins10, float64 - 100000 => 3 reps, 100 iter per rep, 1402.316260 usec per call
numba: bins10, float64 - 100000 => 3 reps, 100 iter per rep, 1365.159980 usec per call
numba_gpu: bins10, float64 - 100000 => 3 reps, 100 iter per rep, 1778.616570 usec per call
numpy: bins10, float64 - 300000 => 3 reps, 100 iter per rep, 4086.320090 usec per call
numba: bins10, float64 - 300000 => 3 reps, 100 iter per rep, 4103.344970 usec per call
numba_gpu: bins10, float64 - 300000 => 3 reps, 100 iter per rep, 2086.206040 usec per call
numpy: bins10, float64 - 3000000 => 3 reps, 10 iter per rep, 37877.584500 usec per call
numba: bins10, float64 - 3000000 => 3 reps, 10 iter per rep, 40958.335600 usec per call
numba_gpu: bins10, float64 - 3000000 => 3 reps, 100 iter per rep, 6885.126960 usec per call
numpy: bins1000, float32 - 1000 => 3 reps, 1000 iter per rep, 180.907137 usec per call
numba: bins1000, float32 - 1000 => 3 reps, 10000 iter per rep, 16.114160 usec per call
numba_gpu: bins1000, float32 - 1000 => 3 reps, 100 iter per rep, 1586.353680 usec per call
numpy: bins1000, float32 - 10000 => 3 reps, 1000 iter per rep, 275.862535 usec per call
numba: bins1000, float32 - 10000 => 3 reps, 1000 iter per rep, 142.604908 usec per call
numba_gpu: bins1000, float32 - 10000 => 3 reps, 100 iter per rep, 1589.610960 usec per call
numpy: bins1000, float32 - 100000 => 3 reps, 100 iter per rep, 1223.783610 usec per call
numba: bins1000, float32 - 100000 => 3 reps, 100 iter per rep, 1404.859190 usec per call
numba_gpu: bins1000, float32 - 100000 => 3 reps, 100 iter per rep, 1684.227960 usec per call
numpy: bins1000, float32 - 300000 => 3 reps, 100 iter per rep, 3347.087800 usec per call
numba: bins1000, float32 - 300000Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py", line 184, in _run_and_validate_results
self.validator(input_args, input_kwargs, actual_results)
File "/root/numba-examples/examples/density_estimation/histogram/impl.py", line 73, in validator
np.testing.assert_array_equal(expected_hist, actual_hist)
File "/usr/local/lib/python3.6/dist-packages/numpy/testing/_private/utils.py", line 918, in assert_array_equal
verbose=verbose, header='Arrays are not equal')
File "/usr/local/lib/python3.6/dist-packages/numpy/testing/_private/utils.py", line 841, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
Mismatch: 0.4%
Max absolute difference: 1
Max relative difference: 0.00301205
x: array([ 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
y: array([ 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/bin/numba_bench", line 4, in <module>
__import__('pkg_resources').run_script('numba-bench==0.1', 'numba_bench')
File "/usr/local/lib/python3.6/dist-packages/pkg_resources/__init__.py", line 666, in run_script
self.require(requires)[0].run_script(script_name, ns)
File "/usr/local/lib/python3.6/dist-packages/pkg_resources/__init__.py", line 1462, in run_script
exec(code, namespace, namespace)
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/EGG-INFO/scripts/numba_bench", line 7, in <module>
sys.exit(main(sys.argv))
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/main.py", line 62, in main
verify_only=args.verify_only)
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py", line 290, in discover_and_run_benchmarks
results = benchmark.run_benchmark(verify_only=verify_only)
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py", line 229, in run_benchmark
self._run_and_validate_results(input_dict, impl_dict)
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py", line 186, in _run_and_validate_results
self._raise_benchmark_error('Implementation %s failed validation on input %s' % (impl_dict['name'], input_dict['x']))
File "/usr/local/lib/python3.6/dist-packages/numba_bench-0.1-py3.6.egg/numba_bench/benchmark.py", line 59, in _raise_benchmark_error
raise BenchmarkError(self.benchmark_dir, message)
numba_bench.benchmark.BenchmarkError: [/root/numba-examples/examples/density_estimation/histogram]: Implementation numba failed validation on input 300000
Runing on:
root@547a227b1517:~/numba-examples# numba -s
System info:
--------------------------------------------------------------------------------
__Time Stamp__
2020-01-20 18:47:17.782535
__Hardware Information__
Machine : x86_64
CPU Name : ivybridge
Number of accessible CPU cores : 4
Listed accessible CPUs cores : 0-3
CFS restrictions : None
CPU Features :
64bit aes avx cmov cx16 f16c fsgsbase mmx pclmul popcnt rdrnd sahf sse sse2 sse3
sse4.1 sse4.2 ssse3 xsave xsaveopt
__OS Information__
Platform : Linux-5.0.0-38-generic-x86_64-with-Ubuntu-18.04-bionic
Release : 5.0.0-38-generic
System Name : Linux
Version : #41-Ubuntu SMP Tue Dec 3 00:27:35 UTC 2019
OS specific info : Ubuntu18.04bionic
glibc info : glibc 2.25
__Python Information__
Python Compiler : GCC 8.3.0
Python Implementation : CPython
Python Version : 3.6.8
Python Locale : en_US UTF-8
__LLVM information__
LLVM version : 8.0.0
__CUDA Information__
Found 1 CUDA devices
id 0 b'GeForce GTX 760' [SUPPORTED]
compute capability: 3.0
pci device id: 0
pci bus id: 1
Summary:
1/1 devices are supported
CUDA driver version : 10010
CUDA libraries:
Finding cublas from System
named libcublas.so.10.0.130
trying to open library... ok
Finding cusparse from System
named libcusparse.so.10.0.130
trying to open library... ok
Finding cufft from System
named libcufft.so.10.0.145
trying to open library... ok
Finding curand from System
named libcurand.so.10.0.130
trying to open library... ok
Finding nvvm from System
named libnvvm.so.3.3.0
trying to open library... ok
Finding libdevice from System
searching for compute_20... ok
searching for compute_30... ok
searching for compute_35... ok
searching for compute_50... ok
__ROC Information__
ROC available : False
Error initialising ROC due to : No ROC toolchains found.
No HSA Agents found, encountered exception when searching:
Error at driver init:
NUMBA_HSA_DRIVER /opt/rocm/lib/libhsa-runtime64.so is not a valid file path. Note it must be a filepath of the .so/.dll/.dylib or the driver:
__SVML Information__
SVML state, config.USING_SVML : False
SVML library found and loaded : False
llvmlite using SVML patched LLVM : True
SVML operational : False
__Threading Layer Information__
TBB Threading layer available : True
OpenMP Threading layer available : False
+--> Disabled due to : Unknown import problem.
Workqueue Threading layer available : True
__Numba Environment Variable Information__
None set.
__Conda Information__
Conda not present/not working.
Error was [Errno 2] No such file or directory: 'conda': 'conda'
--------------------------------------------------------------------------------
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the dashed (----) lines, or from a given specific section as
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=============================================================
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I have a similar error using numba_bench -o results histogram, but with 100000 instead of 300000:
Implementation numba failed validation on input 100000
Looks like the issue is with density_estimation/histogram example. Other benchmarks ran fine.
Running Histogram [/Documents/GitHub/numba-examples/examples/density_estimation/histogram]
numpy: bins10, float32 - 1000 => 3 reps, 10000 iter per rep, 88.135271 usec per call
numba: bins10, float32 - 1000 => 3 reps, 100000 iter per rep, 4.443364 usec per call
numpy: bins10, float32 - 10000 => 3 reps, 1000 iter per rep, 144.338375 usec per call
numba: bins10, float32 - 10000 => 3 reps, 10000 iter per rep, 29.171375 usec per call
numpy: bins10, float32 - 100000 => 3 reps, 1000 iter per rep, 687.286959 usec per call
numba: bins10, float32 - 100000 => 3 reps, 1000 iter per rep, 279.511208 usec per call
numpy: bins10, float32 - 300000 => 3 reps, 100 iter per rep, 1895.402500 usec per call
numba: bins10, float32 - 300000 => 3 reps, 1000 iter per rep, 843.883041 usec per call
numpy: bins10, float32 - 3000000 => 3 reps, 10 iter per rep, 18824.854100 usec per call
numba: bins10, float32 - 3000000 => 3 reps, 100 iter per rep, 8644.399160 usec per call
numpy: bins10, float64 - 1000 => 3 reps, 10000 iter per rep, 85.318975 usec per call
numba: bins10, float64 - 1000 => 3 reps, 100000 iter per rep, 4.416603 usec per call
numpy: bins10, float64 - 10000 => 3 reps, 1000 iter per rep, 148.214792 usec per call
numba: bins10, float64 - 10000 => 3 reps, 10000 iter per rep, 29.376937 usec per call
numpy: bins10, float64 - 100000 => 3 reps, 1000 iter per rep, 768.946458 usec per call
numba: bins10, float64 - 100000 => 3 reps, 1000 iter per rep, 283.016125 usec per call
numpy: bins10, float64 - 300000 => 3 reps, 100 iter per rep, 2161.592920 usec per call
numba: bins10, float64 - 300000 => 3 reps, 1000 iter per rep, 853.712167 usec per call
numpy: bins10, float64 - 3000000 => 3 reps, 10 iter per rep, 21563.341600 usec per call
numba: bins10, float64 - 3000000 => 3 reps, 100 iter per rep, 8740.612910 usec per call
numpy: bins1000, float32 - 1000 => 3 reps, 10000 iter per rep, 92.946225 usec per call
numba: bins1000, float32 - 1000 => 3 reps, 100000 iter per rep, 4.994264 usec per call
numpy: bins1000, float32 - 10000 => 3 reps, 1000 iter per rep, 139.874917 usec per call
numba: bins1000, float32 - 10000 => 3 reps, 10000 iter per rep, 28.367758 usec per call
numpy: bins1000, float32 - 100000 => 3 reps, 1000 iter per rep, 634.296291 usec per call
numba: bins1000, float32 - 100000Traceback (most recent call last):
File "/Documents/GitHub/numba-examples/numba_bench/benchmark.py", line 184, in _run_and_validate_results
self.validator(input_args, input_kwargs, actual_results)
File "/Documents/GitHub/numba-examples/examples/density_estimation/histogram/impl.py", line 73, in validator
np.testing.assert_array_equal(expected_hist, actual_hist)
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 934, in assert_array_equal
assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
File "/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Arrays are not equal
Mismatched elements: 2 / 1000 (0.2%)
Max absolute difference: 1
Max relative difference: 0.00595238
x: array([ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,...
y: array([ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,...
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.9/bin/numba_bench", line 7, in <module>
exec(compile(f.read(), __file__, 'exec'))
File "/Documents/GitHub/numba-examples/bin/numba_bench", line 7, in <module>
sys.exit(main(sys.argv))
File "/Documents/GitHub/numba-examples/numba_bench/main.py", line 61, in main
discover_and_run_benchmarks(root, output, match_substrings, skip_existing=args.skip_existing, resources=resources,
File "/Documents/GitHub/numba-examples/numba_bench/benchmark.py", line 290, in discover_and_run_benchmarks
results = benchmark.run_benchmark(verify_only=verify_only)
File "/Documents/GitHub/numba-examples/numba_bench/benchmark.py", line 229, in run_benchmark
self._run_and_validate_results(input_dict, impl_dict)
File "/Documents/GitHub/numba-examples/numba_bench/benchmark.py", line 186, in _run_and_validate_results
self._raise_benchmark_error('Implementation %s failed validation on input %s' % (impl_dict['name'], input_dict['x']))
File "/Documents/GitHub/numba-examples/numba_bench/benchmark.py", line 59, in _raise_benchmark_error
raise BenchmarkError(self.benchmark_dir, message)
numba_bench.benchmark.BenchmarkError: [/Documents/GitHub/numba-examples/examples/density_estimation/histogram]: Implementation numba failed validation on input 100000
