CUDA 환경 설정 (rstudio)

Published onesixx on

https://tensorflow.rstudio.com/installation/gpu/local_gpu/

UBNUTU 설정

Rstuio Server사용여부 및 Sigle-user multi-user여부에 따라 설정해야 하는 것이 달라진다.

CUDA 라이브러리 설치과정에서
CUDA binaries경로를 PATH 와 LD_LIBRARY_PATH에추가
CUDA_HOME 환경변수를 설정

Shell

LD_LIBRARY_PATH수정

sudo vi /etc/rstudio/rserver.conf

rsession-ld-library-path=/usr/local/cuda/lib64

CUDA_HOME 과 PATH 변수 설정

vi /usr/lib/R/etc/Rprofile.site

Sys.setenv(CUDA_HOME=”/usr/local/cuda”)
Sys.setenv(PATH=paste(Sys.getenv(“PATH”), “/usr/local/cuda/bin”, sep=”:”))

GPU사용률

Shell

….참고….

sudo service –status-all

sudo service rstudio-server start

sudo service dbus start

R
R

I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA

https://m.blog.naver.com/complusblog/221237740617

W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library ‘libcublas.so.10’; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/lib/R/lib::/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/jvm/java-8-openjdk-amd64/jre/lib/amd64/server

sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda

Categories: DeepLearning

onesixx

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