mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
513881584d
There are mysterious memory usage growth in Ray clusters that disappear when running with jemalloc. Before we are able to figure out the root cause, it seems using jemalloc by default can be a good walkaround. Because of its efficiency, using jemalloc by default can be beneficial, but we need to run more benchmarks to verify.
81 lines
2.9 KiB
Docker
81 lines
2.9 KiB
Docker
# The base-deps Docker image installs main libraries needed to run Ray
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# The GPU options are NVIDIA CUDA developer images.
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ARG BASE_IMAGE="ubuntu:focal"
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FROM ${BASE_IMAGE}
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# FROM directive resets ARG
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ARG BASE_IMAGE
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# If this arg is not "autoscaler" then no autoscaler requirements will be included
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ARG AUTOSCALER="autoscaler"
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ENV TZ=America/Los_Angeles
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# TODO(ilr) $HOME seems to point to result in "" instead of "/home/ray"
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ENV PATH "/home/ray/anaconda3/bin:$PATH"
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ARG DEBIAN_FRONTEND=noninteractive
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ARG PYTHON_VERSION=3.7.7
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ARG RAY_UID=1000
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ARG RAY_GID=100
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RUN apt-get update -y \
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&& apt-get install -y sudo tzdata \
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&& useradd -ms /bin/bash -d /home/ray ray --uid $RAY_UID --gid $RAY_GID \
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&& usermod -aG sudo ray \
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&& echo 'ray ALL=NOPASSWD: ALL' >> /etc/sudoers \
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&& rm -rf /var/lib/apt/lists/* \
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&& apt-get clean
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USER $RAY_UID
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ENV HOME=/home/ray
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RUN sudo apt-get update -y && sudo apt-get upgrade -y \
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&& sudo apt-get install -y \
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git \
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libjemalloc-dev \
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wget \
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cmake \
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g++ \
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zlib1g-dev \
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$(if [ "$AUTOSCALER" = "autoscaler" ]; then echo \
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tmux \
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screen \
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rsync \
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openssh-client \
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gnupg; fi) \
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&& wget \
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--quiet "https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh" \
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-O /tmp/miniconda.sh \
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&& /bin/bash /tmp/miniconda.sh -b -u -p $HOME/anaconda3 \
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&& $HOME/anaconda3/bin/conda init \
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&& echo 'export PATH=$HOME/anaconda3/bin:$PATH' >> /home/ray/.bashrc \
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&& rm /tmp/miniconda.sh \
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&& $HOME/anaconda3/bin/conda install -y \
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libgcc python=$PYTHON_VERSION \
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&& $HOME/anaconda3/bin/conda clean -y --all \
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&& $HOME/anaconda3/bin/pip install --no-cache-dir \
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flatbuffers \
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cython==0.29.26 \
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# Necessary for Dataset to work properly.
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numpy\>=1.20 \
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psutil \
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# To avoid the following error on Jenkins:
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# AttributeError: 'numpy.ufunc' object has no attribute '__module__'
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&& $HOME/anaconda3/bin/pip uninstall -y dask \
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# We install cmake temporarily to get psutil
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&& sudo apt-get autoremove -y cmake zlib1g-dev \
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# We keep g++ on GPU images, because uninstalling removes CUDA Devel tooling
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$(if [ "$BASE_IMAGE" = "ubuntu:focal" ]; then echo \
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g++; fi) \
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# Either install kubectl or remove wget
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&& (if [ "$AUTOSCALER" = "autoscaler" ]; \
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then wget -O - -q https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add - \
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&& sudo touch /etc/apt/sources.list.d/kubernetes.list \
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&& echo "deb http://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee -a /etc/apt/sources.list.d/kubernetes.list \
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&& sudo apt-get update \
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&& sudo apt-get install kubectl; \
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else sudo apt-get autoremove -y wget; \
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fi;) \
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&& sudo rm -rf /var/lib/apt/lists/* \
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&& sudo apt-get clean
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WORKDIR $HOME
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