Updated with support of CUDA 9.2

Dockerfile

@@ -7,20 +7,23 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
         nano gnuplot \
         g++-5 gcc-5 \
         libglib2.0-0 libxext6 libsm6 libxrender1 \
-        mercurial subversion && \
+        mercurial subversion \
+        epstool && \
     curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64/7fa2af80.pub | apt-key add - && \
     echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1710/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
     echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list && \
     apt-get purge --autoremove -y curl && \
     rm -rf /var/lib/apt/lists/*
 
 
-ENV CUDA_VERSION 9.2.88
+ENV CUDA_VERSION 9.2.148
 ENV CUDA_PKG_VERSION 9-2=$CUDA_VERSION-1
-ENV NCCL_VERSION 2.2.12
+ENV NCCL_VERSION 2.2.13
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
         cuda-cudart-$CUDA_PKG_VERSION \
+        cuda-cudart-dev-$CUDA_PKG_VERSION \
+        cuda-cupti-$CUDA_PKG_VERSION \
         cuda-libraries-$CUDA_PKG_VERSION \
         cuda-nvtx-$CUDA_PKG_VERSION \
         libnccl2=$NCCL_VERSION-1+cuda9.2 \
@@ -32,39 +35,28 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     ln -s cuda-9.2 /usr/local/cuda && \
     rm -rf /var/lib/apt/lists/*
 
-# nvidia-docker 1.0
-LABEL com.nvidia.volumes.needed="nvidia_driver"
-LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
-
 RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
     echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
 
+#Install CUDA path variables
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
 ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs
 ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
 
 # nvidia-container-runtime
 ENV NVIDIA_VISIBLE_DEVICES all
 ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
-ENV NVIDIA_REQUIRE_CUDA "cuda>=9.1"
+ENV NVIDIA_REQUIRE_CUDA "cuda>=9.2"
 
 #Install CuDNN (using this hack since CuDNN does not support 17.04)
-ENV CUDNN_VERSION 7.1.4.18
+ENV CUDNN_VERSION 7.2.1.38
 LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
             libcudnn7=$CUDNN_VERSION-1+cuda9.2 \
             libcudnn7-dev=$CUDNN_VERSION-1+cuda9.2 && \
     rm -rf /var/lib/apt/lists/*
 
-#Install CUDA path variables
-RUN echo "/usr/local/cuda/lib64" >> /etc/ld.so.conf.d/cuda.conf && \
-    ldconfig
-RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
-    echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
-ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
-
 #Install Anaconda
 RUN echo 'export PATH=/opt/conda/bin:$PATH' > /etc/profile.d/conda.sh && \
     wget --quiet https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O ~/anaconda.sh && \
@@ -76,8 +68,6 @@ RUN /opt/conda/bin/conda install -y ipykernel matplotlib pydot-ng theano pygpu b
 RUN /opt/conda/bin/conda create -n xeus python=3.6 ipykernel xeus-cling -c QuantStack -c conda-forge
 RUN /opt/conda/bin/conda create -n pytorch python=3.6 ipykernel pytorch torchvision cuda90 -c pytorch
 
-#RUN /opt/conda/bin/conda install -c calex sklearn-pandas
-
 ENV PATH /opt/conda/bin:${PATH}
 ENV PATH /usr/local/cuda/bin:${PATH}
 RUN echo 'export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}' >> /cocalc/src/smc_pyutil/smc_pyutil/templates/linux/bashrc && \