Check failed: status == CUBLAS_STATUS_SUCCESS (13 vs. 0) CUBLAS_STATUS_EXECUTION_FAILED

你的名字 2022-05-28 12:30 314阅读 0赞

[ RUN      ] PowerLayerTest/3.TestPowerOneGradient
    F0319 15:50:19.414253 22426 math_functions.cu:92] Check failed: status == CUBLAS_STATUS_SUCCESS (13 vs. 0)  CUBLAS_STATUS_EXECUTION_FAILED
    *** Check failure stack trace: ***
        @     0x7f574fe7e78d  google::LogMessage::Fail()
        @     0x7f574fe80d43  google::LogMessage::SendToLog()
        @     0x7f574fe7e31b  google::LogMessage::Flush()
        @     0x7f574fe7fc8e  google::LogMessageFatal::~LogMessageFatal()
        @     0x7f574e348e4e  caffe::caffe_gpu_scal<>()
        @     0x7f574e336906  caffe::PowerLayer<>::Forward_gpu()
        @           0x455772  caffe::Layer<>::Forward()
        @           0x496300  caffe::GradientChecker<>::CheckGradientSingle()
        @           0x50ea94  caffe::GradientChecker<>::CheckGradientEltwise()
        @           0x6b69b5  caffe::PowerLayerTest<>::TestBackward()
        @           0x7ac6b3  testing::internal::HandleExceptionsInMethodIfSupported<>()
        @           0x7a5cca  testing::Test::Run()
        @           0x7a5e18  testing::TestInfo::Run()
        @           0x7a5ef5  testing::TestCase::Run()
        @           0x7a71cf  testing::internal::UnitTestImpl::RunAllTests()
        @           0x7a74f3  testing::UnitTest::Run()
        @           0x44bfa9  main
        @     0x7f574d5a8830  __libc_start_main
        @           0x451c39  _start
    Makefile:478: recipe for target 'runtest' failed
    make: *** [runtest] 已放弃 (core dumped)

首先明确，这是make runtest的错误，所以一定不能是代码问题。一定是我的配置问题。虽然是segnet作者改得caffe，但是应该没有问题。不过我还是打算用官方的caffe跑一下试试。

我之前那篇教程，安装教程http://www.cnblogs.com/SweetBeens/p/8525131.html，提到如果ubuntu16.04装9,可能会有问题，那么问题来了。**官网给出的doc提到了这个问题**：

The GPU program failed to execute. This is often caused by a launch failure of the kernel on the GPU, which can be caused by multiple reasons.

To correct: check that the hardware, an appropriate version of the driver, and the cuBLAS library are correctly installed.

**github上有个比较火的讨论贴：**

https://github.com/BVLC/caffe/issues/2417

**大家的解决方法是装cuda8.0,还有说不用cudnn。**

但由于我不到黄河心不死，不想用cuda8

那么有如下思路：

1,跑官网caffe，看看是不是因为segnet\_caffe版本太低或者什么的

2.改下gcc版本

3.更换driver和cuda版本

等我试试。而且为什么别人的有一些可用16.04+9.1，奇怪了。

**拟解决过程**

1.我跑了官网的caffe，出现如下错误：

[  FAILED  ] EmbedLayerTest/3.TestForward, where TypeParam = caffe::GPUDevice<double> (1 ms)
    [ RUN      ] EmbedLayerTest/3.TestGradient
    [       OK ] EmbedLayerTest/3.TestGradient (101 ms)
    [ RUN      ] EmbedLayerTest/3.TestSetUp
    [       OK ] EmbedLayerTest/3.TestSetUp (0 ms)
    [ RUN      ] EmbedLayerTest/3.TestForwardWithBias
    F0319 17:26:25.959848 30839 math_functions.cu:42] Check failed: status == CUBLAS_STATUS_SUCCESS (13 vs. 0)  CUBLAS_STATUS_EXECUTION_FAILED
    *** Check failure stack trace: ***
        @     0x7f787028d78d  google::LogMessage::Fail()
        @     0x7f787028fd43  google::LogMessage::SendToLog()
        @     0x7f787028d31b  google::LogMessage::Flush()
        @     0x7f787028ec8e  google::LogMessageFatal::~LogMessageFatal()
        @     0x7f786e105672  caffe::caffe_gpu_gemm<>()
        @     0x7f786e13d75a  caffe::EmbedLayer<>::Forward_gpu()
        @           0x476522  caffe::Layer<>::Forward()
        @           0x4f5ef6  caffe::EmbedLayerTest_TestForwardWithBias_Test<>::TestBody()
        @           0x90b393  testing::internal::HandleExceptionsInMethodIfSupported<>()
        @           0x9049aa  testing::Test::Run()
        @           0x904af8  testing::TestInfo::Run()
        @           0x904bd5  testing::TestCase::Run()
        @           0x905eaf  testing::internal::UnitTestImpl::RunAllTests()
        @           0x9061d3  testing::UnitTest::Run()
        @           0x469fed  main
        @     0x7f786d2ec830  __libc_start_main
        @           0x471a69  _start
    Makefile:532: recipe for target 'runtest' failed
    make: *** [runtest] 已放弃 (core dumped)

# 解决方式 #

**下面两位回复说下载patch能够解决问题。：**

“”问题解决，谢谢！顺便提供下链接，当时找了好一会才找到：https://developer.nvidia.com/cuda-90-download-archive?target\_os=Linux&target\_arch=x86\_64&target\_distro=Ubuntu&target\_version=1604&target\_type=runfilelocal 这是cuda-9.0系列的，下载patchesPatch 2 (Released Mar 5, 2018)“”

可以参考下。

**作者本人直接使用anaconda了，并且使用的是最新的显卡驱动，所以装什么版本都没有问题。**

这个实际上使用anaconda基本上就不需要考虑版本问题，前置依赖了，是一种国际广泛使用的深度学习软件。推荐大家使用，如果latex一样，学会了就在也不想用回word了。

Check failed: status == CUBLAS_STATUS_SUCCESS (13 vs. 0) CUBLAS_STATUS_EXECUTION_FAILED

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