ubuntu 14.04 install cuda 7.5

In the past blog, I showed that it’s easy to install cuda. While the truth is that, as my laptop has two graphical cards(a intel and nvidia GT850M), it’s really hard to install nvidia driver and CUDA.

Fail trace:

Using the cuda-new-version.run as other blogs says, the installation is successeed, but ubuntu wouldn’t be able to login after entering the password.

Success trace

then I tried to use the local cuda.deb file download from the website: https://developer.nvidia.com/cuda-downloads .

• follow the steps:

sudo dpkg -i cuda-repo-ubuntu1404-7-5-local_7.5-18_amd64.deb

sudo apt-get update

sudo apt-get install cuda

tips: if you also has two graphical cards, you should use:

sudo service lightdm stop

and then login your account in the tty1 or other ttys except the graphical one.
the use the three step.

• after the installation of cuda.
  reboot

• then set the environment variables:

echo ‘export PATH=/usr/local/cuda-7.5/bin:$PATH’ >> ~/.bashrc

echo ‘export LD_LIBRARY_PATH=/usr/local/cuda-7.5/lib64:$LD_LIBRARY_PATH’ >> ~/.bashrc

source ~/.bashrc

sudo reboot

After reboot. check whether it’s successfully installed:

nvcc -V

if it returns the version of CUDA.
Then congralates.

New tips: It happened to me that ubuntu stops at the screen of logo and it wouldn't let me login.

the problem is caused by the pre-installed open source graphical card driver nouveau, it can be solved by taking them into the blacklist using following steps:

go to the recovery mode and if it shows that the file system is read-only, choose the selection ' root'

mount -o remount, rw /

Then we can modify the files, edit the file /etc/modprobe.d/blacklist and add following lines at the end of it:

blacklist amd76x_edac

blacklist vga16fb

blacklist nouveau

blacklist rivafb

blacklist nvidiafb

blacklistrivatv

all finished~

ubuntu 14.04 install theano

At first, we should set up the python environment.
maybe we can simply use the apt-get method:

sudo apt-get install -y python-dev python-pip python-nose gcc g++ git gfortran

for some district such as china, pypi host may not available, we can use other open source, such as pypi.douban.com/simple

Theano also needs BLAS, LAPACK, ATLAS. just install them

sudo apt-get install -y libopenblas-dev liblapack-dev libatlas-base-dev

then install numpy. During my installation, An error due to numpy 1.10.1+ can cause failure of test of theano.

So we can download earlier edition's (such as 1.9.2) source code of numpy, then install it. As we have installed gfortran. The step can be:

 sudo tar -zxvf numpy-1.9.2.gz.zip

cd numpy-1.9.2

sudo python setup.py build  --fcompiler=gnu95

sudo python setup.py install

After the set-up of numpy. we should test numpy.

python -c 'import numpy; numpy.test()'

it shouldn't have any error return.

then install scipy. As I got none error from scipy, so we can just install scipy by pip

sudo pip install scipy

then test it:

python -c 'import scipy; scipy.test()'

Also no error is accepted

then install   theano.

sudo pip install theano

also test it:

sudo python -c 'import theano; theano.test()'

this test step is really time-consuming, wait and check it has no error.

then theano is successfully set up.

then install Nivida gpu develop drivers.

if error of blas not found errors, sudo apt-get install gfortran libopenblas-dev liblapack-dev

New start

Everything is fresh in UCAS. Go buddy

Accelerate BSEG

BSEG是新总账的明细表。

BKPF是新总账的头表。

BSIS： 总账的未清项

BSAS：总账的已清项

BSIK： 应付明细的未清项（与vendor相关）

BSAK：应付明细的已清项（与vendor相关）

BSID： 应收明细的未清项（与custom相关）

BSAD： 应收明细的已清项（与custom相关）

BSEG取的过数可以通过BUKRS, EBLNR, GJAHR, ZUBEI这四个字段关联以上六个表而取得。

In the ZFINPCA_KEND accelerate, the fetch data from bseg is really time-costing.

We can get data from the source table of BSEG: BSIS, BSAS, BSIK, BSAK, BSID, BSAD.

注意：BSEG内的每行有且仅在这六个表里存在。所以可以用Single来进行select。

对于在这六个表里没有的字段，可以再从BSEG里取得相应的字段的值。

这样估计会加速很多。

下图是BSEG与其他表的关系。

对于BSIM：

In addition: After our further research, we find that using that six tables we may loose some fields. The detail is below:

table                    missing fields                              

BSIS          vbeln          kidno     vbel2      posn2

BSAS         vbeln          kidno     vbel2      posn2

BSID          segment      werks     bewar

BSAD         segment      werks     bewar

BSIK          segment      vbeln     vbel2     posn2     werks     bewar

BSAK          segment      vbeln     vbel2     posn2     werks     bewar

So we lost many data. Then we research again. 

Finally we get that,  if we use the statement 'select single XXX from bseg where bukrs = bukrs  and belnr = belnr

                                                                                                                                                                          gjahr = gjahr  and buzei = buzei'

we can get the fully needed data faster, because 'BUKRS BELNR GJAHR BUZEI' consist all the key fields of the table BSEG, in other words, to a fixed group of ( BUKRS BELNR GJAHR BUZEI ), we can only find one record. So the data we get is correct.

Next is the code of the project:

Source code:

Way to Connect the six table:

                                                                                                                                                                 

 

   Way to use 'Select single from BSEG'

    When we won't loose the fields, we can use the six tables to do the selection. 

    If we loose fields, we can use the 'select single XXX from BSEG'. Tips: the key fields should be given.

  

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