Here's another example that uses the CuPy solve function which does use
cublas. At least from what I can tell in the CuPy source code. This example
works fine too.
# Compare CuPy and NumPy
import cupy as cp
import numpy as np
import time
# Using NumPy
a_cpu = np.array([[4, 3, 2], [-2, 2, 3], [3, -5, 2]])
b_cpu = np.array([25, -10, -4])
ti = time.perf_counter()
x_cpu = np.linalg.solve(a_cpu, b_cpu)
tf = time.perf_counter()
print(f'NumPy result: \t{x_cpu}')
print(f'NumPy time: \t{tf - ti:.4g}')
# Using CuPy
a_gpu = cp.array([[4, 3, 2], [-2, 2, 3], [3, -5, 2]])
b_gpu = cp.array([25, -10, -4])
ti = time.perf_counter()
x_gpu = cp.linalg.solve(a_gpu, b_gpu)
tf = time.perf_counter()
print(f'CuPy result: \t{x_gpu}')
print(f'CuPy time: \t{tf - ti:.4g}')
On Saturday, September 26, 2020 at 12:10:26 PM UTC-4 [email protected]
wrote:
> Hi Gavin,
>
> So it looks as if the cupy.linalg.norm function makes does not call out to
> CUBLAS. See:
>
> https://github.com/cupy/cupy/blob/master/cupy/linalg/norms.py#L54
>
> Regards, Freddie.
>
> On 26 Sep 2020, at 10:54, 'Gavin Wiggins' via PyFR Mailing List <
> [email protected]> wrote:
>
> I created the following example using CuPy which uses Cuda to calculate
> the norm of a matrix. I think this uses cublas. This example works fine.
>
>
> # Compare CuPy and NumPy
>
> import cupy as cp
> import numpy as np
> import time
>
> n = 100_000_000
> ns = 10_000
>
> # Using NumPy
> x_cpu = np.arange(n) - 4
> x_cpu.reshape((ns, ns))
>
> ti = time.perf_counter()
> norm_cpu = np.linalg.norm(x_cpu)
> tf = time.perf_counter()
>
> print(f'NumPy result: \t{norm_cpu}')
> print(f'NumPy time: \t{tf - ti:.4g}')
>
> # Using CuPy
> x_gpu = cp.arange(n) - 4
> x_gpu.reshape((ns, ns))
>
> ti = time.perf_counter()
> norm_gpu = cp.linalg.norm(x_gpu)
> tf = time.perf_counter()
>
> print(f'CuPy result: \t{norm_gpu}')
> print(f'CuPy time: \t{tf - ti:.4g}')
>
>
>
> On Saturday, September 26, 2020 at 10:56:09 AM UTC-4 Gavin Wiggins wrote:
>
>> I have never used Numba (other than the above) so I don't have a readily
>> available example to use.
>>
>>
>>
>>
>>
>> On Saturday, September 26, 2020 at 8:16:55 AM UTC-4 [email protected]
>> wrote:
>>
>>> Hi Gavin,
>>>
>>> Looking at the output below it appears as if Numba is opening up and
>>> loading the CUBLAS shared library, although it does not state if it is
>>> actually calling any of the methods. Would you be able to run a test case
>>> in Numba which calls down to CUBLAS?
>>>
>>> Regards, Freddie.
>>>
>>> On 25 Sep 2020, at 23:25, 'Gavin Wiggins' via PyFR Mailing List <
>>> [email protected]> wrote:
>>>
>>> I used Numba to get some system info (see below). Looks like the cublas
>>> library is working fine.
>>>
>>>
>>>
>>> System info:
>>>
>>> --------------------------------------------------------------------------------
>>> __Time Stamp__
>>> Report started (local time) : 2020-09-26
>>> 00:17:34.207700
>>> UTC start time : 2020-09-26
>>> 04:17:34.207709
>>> Running time (s) : 3.237414
>>>
>>> __Hardware Information__
>>> Machine : x86_64
>>> CPU Name : haswell
>>> CPU Count : 20
>>> Number of accessible CPUs : 20
>>> List of accessible CPUs cores : 0-19
>>> CFS Restrictions (CPUs worth of runtime) : None
>>>
>>> CPU Features : 64bit aes avx avx2 bmi
>>> bmi2 cmov
>>> cx16 cx8 f16c fma
>>> fsgsbase fxsr
>>> invpcid lzcnt mmx movbe
>>> pclmul
>>> popcnt rdrnd sahf sse
>>> sse2 sse3
>>> sse4.1 sse4.2 ssse3
>>> xsave xsaveopt
>>>
>>> Memory Total (MB) : 58373
>>> Memory Available (MB) : 57310
>>>
>>> __OS Information__
>>> Platform Name :
>>> Linux-4.15.0-118-generic-x86_64-with-glibc2.10
>>> Platform Release : 4.15.0-118-generic
>>> OS Name : Linux
>>> OS Version : #119-Ubuntu SMP Tue Sep
>>> 8 12:30:01 UTC 2020
>>> OS Specific Version : ?
>>> Libc Version : glibc 2.27
>>>
>>> __Python Information__
>>> Python Compiler : GCC 7.3.0
>>> Python Implementation : CPython
>>> Python Version : 3.8.5
>>> Python Locale : en_US.UTF-8
>>>
>>> __LLVM Information__
>>> LLVM Version : 10.0.1
>>>
>>> __CUDA Information__
>>> CUDA Device Initialized : True
>>> CUDA Driver Version : 9010
>>> CUDA Detect Output:
>>> Found 1 CUDA devices
>>> id 0 b'Tesla K40m' [SUPPORTED]
>>> compute capability: 3.5
>>> pci device id: 5
>>> pci bus id: 0
>>> Summary:
>>> 1/1 devices are supported
>>>
>>> CUDA Librairies Test Output:
>>> Finding cublas from System
>>> named libcublas.so.9.2.88
>>> trying to open library... ok
>>> Finding cusparse from System
>>> named libcusparse.so.9.2.88
>>> trying to open library... ok
>>> Finding cufft from System
>>> named libcufft.so.9.2.88
>>> trying to open library... ok
>>> Finding curand from System
>>> named libcurand.so.9.2.88
>>> trying to open library... ok
>>> Finding nvvm from System
>>> named libnvvm.so.3.2.0
>>> trying to open library... ok
>>> Finding cudart from System
>>> named libcudart.so.9.2.88
>>> 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
>>> ROC Toolchains : None
>>> HSA Agents Count : 0
>>> HSA Agents:
>>> None
>>> HSA Discrete GPUs Count : 0
>>> HSA Discrete GPUs : None
>>>
>>> __SVML Information__
>>> SVML State, config.USING_SVML : False
>>> SVML Library Loaded : False
>>> llvmlite Using SVML Patched LLVM : True
>>> SVML Operational : False
>>>
>>> __Threading Layer Information__
>>> TBB Threading Layer Available : True
>>> +-->TBB imported successfully.
>>> OpenMP Threading Layer Available : True
>>> +-->Vendor: GNU
>>> Workqueue Threading Layer Available : True
>>> +-->Workqueue imported successfully.
>>>
>>> __Numba Environment Variable Information__
>>> None found.
>>>
>>>
>>>
>>> On Friday, September 25, 2020 at 11:35:04 PM UTC-4 Gavin Wiggins wrote:
>>>
>>>> I ran some of the PyCuda examples at
>>>> https://github.com/inducer/pycuda/tree/master/examples without any
>>>> problems.
>>>>
>>>>
>>>>
>>>>
>>>> On Friday, September 25, 2020 at 9:58:31 PM UTC-4 [email protected]
>>>> wrote:
>>>>
>>>>> Hi Gavin,
>>>>>
>>>>> On 25/09/2020 20:11, 'Gavin Wiggins' via PyFR Mailing List wrote:
>>>>> > I'm trying to run the Couette flow example using the CUDA backend
>>>>> via
>>>>> > the following command:
>>>>> >
>>>>> > $ pyfr run -b cuda -p couette_flow_2d.pyfrm couette_flow_2d.ini
>>>>> >
>>>>> > But I get the following error:
>>>>> >
>>>>> > File
>>>>> >
>>>>> "/home/cades/miniconda3/lib/python3.8/site-packages/pyfr/backends/cuda/cublas.py",
>>>>>
>>>>>
>>>>> > line 78, in _errcheck
>>>>> >
>>>>> > raise self._statuses[status]
>>>>> >
>>>>> > pyfr.backends.cuda.cublas.CUBLASNotInitialized
>>>>> >
>>>>> > Any suggestions on how to fix this?
>>>>>
>>>>> This error appeared once before on the mailing list some years ago:
>>>>>
>>>>> https://groups.google.com/forum/#!topic/pyfrmailinglist/RWWXHC_ACHE
>>>>>
>>>>> although the issue appears to have been configuration related (perhaps
>>>>> a
>>>>> 32-/64-bit problem?).
>>>>>
>>>>> Are you able to run any other CUBLAS applications on the system?
>>>>>
>>>>> Regards, Freddie.
>>>>>
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