compilation - seguridad - tecnicas de pruebas de software

Caffe compiló bien con cudnn; sin embargo, la prueba de ejecución falla con el error: CUDNN_STATUS_ARCH_MISMATCH

Question

Cuando ejecuto make runtest usando caffe obtengo el siguiente resultado, todo se compila bien con Cudnn, no se proporcionan errores, también he incluido el resultado de build_release / tools / caffe device_query -gpu <0,1> para ambas GPU NVidia Tesla que ejecutan Cuda driver y runtime versión 7.0. ¿Alguien podría ayudar?

[----------] 1 test from SolverTest/0, where TypeParam = caffe::CPUDevice<float>
[ RUN ] SolverTest/0.TestInitTrainTestNets
F0907 18:53:28.279698 309 cudnn_softmax_layer.cpp:19] Check failed: status == CUDNN_STATUS_SUCCESS (6 vs. 0) CUDNN_STATUS_ARCH_MISMATCH
*** Check failure stack trace: ***
@ 0x2b8a426cfdaa (unknown)
@ 0x2b8a426cfce4 (unknown)
@ 0x2b8a426cf6e6 (unknown)
@ 0x2b8a426d2687 (unknown)
@ 0x2b8a4404b3c5 caffe::CuDNNSoftmaxLayer<>::LayerSetUp()
@ 0x2b8a440bf8a7 caffe::SoftmaxWithLossLayer<>::LayerSetUp()
@ 0x2b8a440eb9dd caffe::Net<>::Init()
@ 0x2b8a440eca25 caffe::Net<>::Net()
@ 0x2b8a4410335a caffe::Solver<>::InitTrainNet()
@ 0x2b8a44104354 caffe::Solver<>::Init()
@ 0x2b8a44104659 caffe::Solver<>::Solver()
@ 0x787e9c caffe::SolverTest<>::InitSolverFromProtoString()
@ 0x785170 caffe::SolverTest_TestInitTrainTestNets_Test<>::TestBody()
@ 0x7e9943 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x7e0627 testing::Test::Run()
@ 0x7e06ce testing::TestInfo::Run()
@ 0x7e07d5 testing::TestCase::Run()
@ 0x7e3b18 testing::internal::UnitTestImpl::RunAllTests()
@ 0x7e3da7 testing::UnitTest::Run()
@ 0x45552a main
@ 0x2b8a44d70ec5 (unknown)
@ 0x45bd69 (unknown)
@ (nil) (unknown)
make: *** [runtest] Aborted (core dumped)
% ./build_release/tools/caffe device_query -gpu 0
I0907 18:55:04.830653 729 caffe.cpp:111] Querying GPUs 0
I0907 18:55:05.037142 729 common.cpp:168] Device id: 0
I0907 18:55:05.037195 729 common.cpp:169] Major revision number: 2
I0907 18:55:05.037201 729 common.cpp:170] Minor revision number: 0
I0907 18:55:05.037207 729 common.cpp:171] Name: Tesla M2090
I0907 18:55:05.037214 729 common.cpp:172] Total global memory: 5636554752
I0907 18:55:05.037220 729 common.cpp:173] Total shared memory per block: 49152
I0907 18:55:05.037225 729 common.cpp:174] Total registers per block: 32768
I0907 18:55:05.037231 729 common.cpp:175] Warp size: 32
I0907 18:55:05.037236 729 common.cpp:176] Maximum memory pitch: 2147483647
I0907 18:55:05.037241 729 common.cpp:177] Maximum threads per block: 1024
I0907 18:55:05.037246 729 common.cpp:178] Maximum dimension of block: 1024, 1024, 64
I0907 18:55:05.037253 729 common.cpp:181] Maximum dimension of grid: 65535, 65535, 65535
I0907 18:55:05.037258 729 common.cpp:184] Clock rate: 1301000
I0907 18:55:05.037263 729 common.cpp:185] Total constant memory: 65536
I0907 18:55:05.037268 729 common.cpp:186] Texture alignment: 512
I0907 18:55:05.037272 729 common.cpp:187] Concurrent copy and execution: Yes
I0907 18:55:05.037278 729 common.cpp:189] Number of multiprocessors: 16
I0907 18:55:05.037283 729 common.cpp:190] Kernel execution timeout: No
% ./build_release/tools/caffe device_query -gpu 1
I0907 18:55:15.162884 784 caffe.cpp:111] Querying GPUs 1
I0907 18:55:20.532964 784 common.cpp:168] Device id: 1
I0907 18:55:20.533093 784 common.cpp:169] Major revision number: 2
I0907 18:55:20.533129 784 common.cpp:170] Minor revision number: 0
I0907 18:55:20.533161 784 common.cpp:171] Name: Tesla M2090
I0907 18:55:20.533193 784 common.cpp:172] Total global memory: 5636554752
I0907 18:55:20.533227 784 common.cpp:173] Total shared memory per block: 49152
I0907 18:55:20.533252 784 common.cpp:174] Total registers per block: 32768
I0907 18:55:20.533277 784 common.cpp:175] Warp size: 32
I0907 18:55:20.533298 784 common.cpp:176] Maximum memory pitch: 2147483647
I0907 18:55:20.533323 784 common.cpp:177] Maximum threads per block: 1024
I0907 18:55:20.533345 784 common.cpp:178] Maximum dimension of block: 1024, 1024, 64
I0907 18:55:20.533371 784 common.cpp:181] Maximum dimension of grid: 65535, 65535, 65535
I0907 18:55:20.533404 784 common.cpp:184] Clock rate: 1301000
I0907 18:55:20.533428 784 common.cpp:185] Total constant memory: 65536
I0907 18:55:20.533452 784 common.cpp:186] Texture alignment: 512
I0907 18:55:20.533476 784 common.cpp:187] Concurrent copy and execution: Yes
I0907 18:55:20.533500 784 common.cpp:189] Number of multiprocessors: 16
I0907 18:55:20.533524 784 common.cpp:190] Kernel execution timeout: No

Answer 1

La biblioteca cuDNN requiere una GPU de capacidad de cálculo 3.0 o superior :

Compatible con sistemas Windows, Linux y MacOS con Kepler, Maxwell o Tegra K1 GPU.

Su Fermi M2090 es una capacidad de cómputo de 2.0 GPU:

I0907 18:55:05.037195 729 common.cpp:169] Major revision number: 2
I0907 18:55:05.037201 729 common.cpp:170] Minor revision number: 0
I0907 18:55:05.037207 729 common.cpp:171] Name: Tesla M2090

Answer 2

Primero compruebe que escribe este comando nvidia-smi usando el terminal. Luego vaya a este enlace y trate de encontrar su GPU en la tabla. Probablemente descubrirá que su gpu tiene una capacidad de cálculo inferior a 3.0 que no es compatible con cuDNN.

Según su salida y TESLA M2090, probablemente tenga una de las siguientes GPU:

GeForce GTX 590, GeForce GTX 580, GeForce GTX 570, GeForce GTX 480, GeForce GTX 470, GeForce GTX 465, GeForce GTX 480M

Y la capacidad de cómputo de las GPU anteriores es 2.0. Entonces mi sugerencia es intentar instalar caffe sin cuDNN, y no usarlo al menos en la máquina actual.