Cuda 在Jetson-TK1板上构建caffe时出错

我正在我的Jetson-TK1板上建造咖啡馆。该板运行32位Ubuntu Linux。我的Makefile.config如下所示

## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!

# cuDNN acceleration switch (uncomment to build with cuDNN).
#USE_CUDNN := 1

# CPU-only switch (uncomment to build without GPU support).
#CPU_ONLY := 1

# To customize your choice of compiler, uncomment and set the following.
# N.B. the default for Linux is g++ and the default for OSX is clang++
#CUSTOM_CXX := g++

# CUDA directory contains bin/ and lib/ directories that we need.
CUDA_DIR := /usr/local/cuda-6.5
# On Ubuntu 14.04, if cuda tools are installed via
# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
# CUDA_DIR := /usr

# CUDA architecture setting: going with all of them.
# For CUDA < 6.0, comment the *_50 lines for compatibility.
CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
        -gencode arch=compute_20,code=sm_21 \
        -gencode arch=compute_30,code=sm_30 \
        -gencode arch=compute_35,code=sm_35 \
        -gencode arch=compute_50,code=sm_50 \
        -gencode arch=compute_50,code=compute_50

# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS := atlas
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# Leave commented to accept the defaults for your choice of BLAS
# (which should work)!
BLAS_INCLUDE := /usr/include
BLAS_LIB := /usr/lib

# Homebrew puts openblas in a directory that is not on the standard search path
# BLAS_INCLUDE := $(shell brew --prefix openblas)/include
# BLAS_LIB := $(shell brew --prefix openblas)/lib

# This is required only if you will compile the matlab interface.
# MATLAB directory should contain the mex binary in /bin.
# MATLAB_DIR := /usr/local
# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# NOTE: this is required only if you will compile the python interface.
# We need to be able to find Python.h and numpy/arrayobject.h.

PYTHON_INCLUDE := /usr/include/python2.7 \
        /usr/lib/python2.7/dist-packages/numpy/core/include
# Anaconda Python distribution is quite popular. Include path:
# Verify anaconda location, sometimes it's in root.
# ANACONDA_HOME := $(HOME)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
        # $(ANACONDA_HOME)/include/python2.7 \
        # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \

# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /usr/lib
# PYTHON_LIB := $(ANACONDA_HOME)/lib

# Homebrew installs numpy in a non standard path (keg only)
# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)
# WITH_PYTHON_LAYER := 1

# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/local/hdf5/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/local/hdf5/lib


# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
# INCLUDE_DIRS += $(shell brew --prefix)/include
# LIBRARY_DIRS += $(shell brew --prefix)/lib


# Uncomment to use `pkg-config` to specify OpenCV library paths.
# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1

BUILD_DIR := build
DISTRIBUTE_DIR := distribute

# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
DEBUG := 1

# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0

# enable pretty build (comment to see full commands)
Q ?= @

我使用CUDA-6.5

这个版本可能有什么问题

编辑1: @Klaus Prinoth提到的是有用的。现在我可以建造了。我还可以测试CPU和gpu的

build/tools/caffe time--model=models/bvlc_-alexnet/deploy.prototxt--gpu=0

。但是当我做

make-j8运行测试时，我得到的消息是
Check Failed
。我不确定出了什么问题。信息是

[----------] 5 tests from DBTest/1, where TypeParam = caffe::TypeLMDB
[ RUN      ] DBTest/1.TestNext
[       OK ] DBTest/1.TestNext (63 ms)
[ RUN      ] DBTest/1.TestSeekToFirst
[       OK ] DBTest/1.TestSeekToFirst (119 ms)
[ RUN      ] DBTest/1.TestKeyValue
[       OK ] DBTest/1.TestKeyValue (118 ms)
[ RUN      ] DBTest/1.TestWrite
F0807 23:14:56.323696 19992 db.hpp:109] Check failed: mdb_status == 0 (-30792 vs. 0) MDB_MAP_FULL: Environment mapsize limit reached
*** Check failure stack trace: ***
    @ 0x4330f060  (unknown)
    @ 0x4330ef5c  (unknown)
    @ 0x4330eb78  (unknown)
    @ 0x43310f98  (unknown)
    @ 0x43cc2386  caffe::db::LMDBTransaction::Put()
    @   0x155a36  caffe::DBTest_TestWrite_Test<>::TestBody()
    @   0x248d00  testing::internal::HandleExceptionsInMethodIfSupported<>()
    @   0x242124  testing::Test::Run()
    @   0x2421b6  testing::TestInfo::Run()
    @   0x24228a  testing::TestCase::Run()
    @   0x242438  testing::internal::UnitTestImpl::RunAllTests()
    @   0x248a88  testing::internal::HandleExceptionsInMethodIfSupported<>()
    @   0x241c26  testing::UnitTest::Run()
    @    0x81314  main
    @ 0x43f5f632  (unknown)
make: *** [runtest] Aborted
ubuntu@tegra-ubuntu:/opt/caffe$

[------------]5个来自DBTest/1的测试，其中TypeParam=caffe:：TypeLMDB
[运行]DBTest/1.TestNext
[OK]DBTest/1.TestNext（63毫秒）
[运行]DBTest/1.TestSeekToFirst
[OK]DBTest/1.TestSeekToFirst（119毫秒）
[RUN]DBTest/1.TestKeyValue
[OK]DBTest/1.TestKeyValue（118毫秒）
[RUN]DBTest/1.TestWrite
F0807 23:14:56.323696 19992 db.hpp:109]检查失败：mdb_状态==0（-30792 vs.0）mdb_映射已满：已达到环境映射大小限制
***检查故障堆栈跟踪：***
@0x4330f060（未知）
@0x4330ef5c（未知）
@0x4330eb78（未知）
@0x43310f98（未知）
@0x43cc2386 caffe:：db:：LMDBTransaction:：Put（）
@0x155a36 caffe:：DBTest\u TestWrite\u Test:：TestBody（）
@0x248d00测试：：内部：：HandleExceptionsInMethodIfSupported（）
@0x242124测试：：测试：：运行（）
@0x2421b6测试：：TestInfo：：运行（）
@0x24228a测试：：测试用例：：运行（）
@0x242438测试：：内部：：UnitTestImpl：：RunAllTests（）
@0x248a88测试：：内部：：HandleExceptionsInMethodIfSupported（）
@0x241c26测试：：单元测试：：运行（）
@0x81314主
@0x43f5f632（未知）
make:**[runtest]已中止
ubuntu@tegra-ubuntu:/opt/caffe$

这个消息是什么意思？
我按照以下步骤解决了问题。这些是本文中提到的步骤

（1） 需要确保安装了所有依赖项。是的

    sudo apt-get install \
    libprotobuf-dev protobuf-compiler gfortran \
    libboost-dev cmake libleveldb-dev libsnappy-dev \
    libboost-thread-dev libboost-system-dev \
    libatlas-base-dev libhdf5-serial-dev libgflags-dev \
    libgoogle-glog-dev liblmdb-dev gcc-4.7 g++-4.7

因为我不使用Python，所以跳过了Python接口所需的步骤

（2） 获取caffe来源

sudo apt-get install git
git clone https://github.com/BVLC/caffe.git
cd caffe
cp Makefile.config.example Makefile.config

（3） 在
make-j 8 runtest
之前，需要将src/caffe/util/db.cpp中的109951162776更改为536870912，否则将导致runtest中的
MDB\u MAP\u完全错误。
我的Makefile.config显示在原始帖子中。
那你准备好了吗

make -j 8 all
make -j 8 test
make -j 8 runtest

CPU和GPU处理的性能差异可以通过

对于GPU：“
运行build/tools/caffe time--model=models/bvlc_-alexnet/deploy.prototxt--GPU=0
”

对于CPU：“
运行build/tools/caffe time--model=models/bvlc_-alexnet/deploy.prototxt
”
感谢@Klaus Prinoth给我这个链接。
你从哪里下载的这个咖啡馆？从这个链接。还有GitHubTry，这是一个caffe，来自github上的一个家伙，他修复了一些错误。谢谢。好链接。将尝试更新。大致相同，但下载包时有一些不同，因此如果另一个包不起作用，您可以尝试一下。
make -j 8 all
make -j 8 test
make -j 8 runtest