Question

当使用caffe运行make runtest时，我得到以下输出，它与Cudnn编译完好没有提供错误，我还包括build_release / tools / caffe device_query -gpu＆lt; 0,1＆gt;的输出。对于运行Cuda驱动程序和运行时版本7.0的NVidia Tesla GPU。有人可以帮忙吗？

[----------] 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

cuDNN库requires a GPU of compute capability 3.0 or higher：

支持使用Kepler，Maxwell或Tegra K1 GPU的Windows，Linux和MacOS系统。

您的Fermi M2090是一款计算能力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

首先使用终端检查输入此命令nvidia-smi。然后转到此link并尝试在表格中找到您的GPU。您可能会发现您的gpu具有比3.0更低的计算能力，而cuDNN不支持。

根据您的输出和TESLA M2090，您可能拥有以下GPU之一：

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

以上GPU的计算能力为2.0。所以我的建议是尝试在没有cuDNN的情况下安装caffe，并且至少在当前机器中不要使用它。

Caffe编译好了cudnn然而runtest失败并出现错误：CUDNN_STATUS_ARCH_MISMATCH

2 个答案: