xgboost/tests/ci_build/Dockerfile.gpu
Matthew Jones 92b7577c62 [REVIEW] Enable Multi-Node Multi-GPU functionality (#4095)
* Initial commit to support multi-node multi-gpu xgboost using dask

* Fixed NCCL initialization by not ignoring the opg parameter.

- it now crashes on NCCL initialization, but at least we're attempting it properly

* At the root node, perform a rabit::Allreduce to get initial sum_gradient across workers

* Synchronizing in a couple of more places.

- now the workers don't go down, but just hang
- no more "wild" values of gradients
- probably needs syncing in more places

* Added another missing max-allreduce operation inside BuildHistLeftRight

* Removed unnecessary collective operations.

* Simplified rabit::Allreduce() sync of gradient sums.

* Removed unnecessary rabit syncs around ncclAllReduce.

- this improves performance _significantly_ (7x faster for overall training,
  20x faster for xgboost proper)

* pulling in latest xgboost

* removing changes to updater_quantile_hist.cc

* changing use_nccl_opg initialization, removing unnecessary if statements

* added definition for opaque ncclUniqueId struct to properly encapsulate GetUniqueId

* placing struct defintion in guard to avoid duplicate code errors

* addressing linting errors

* removing

* removing additional arguments to AllReduer initialization

* removing distributed flag

* making comm init symmetric

* removing distributed flag

* changing ncclCommInit to support multiple modalities

* fix indenting

* updating ncclCommInitRank block with necessary group calls

* fix indenting

* adding print statement, and updating accessor in vector

* improving print statement to end-line

* generalizing nccl_rank construction using rabit

* assume device_ordinals is the same for every node

* test, assume device_ordinals is identical for all nodes

* test, assume device_ordinals is unique for all nodes

* changing names of offset variable to be more descriptive, editing indenting

* wrapping ncclUniqueId GetUniqueId() and aesthetic changes

* adding synchronization, and tests for distributed

* adding  to tests

* fixing broken #endif

* fixing initialization of gpu histograms, correcting errors in tests

* adding to contributors list

* adding distributed tests to jenkins

* fixing bad path in distributed test

* debugging

* adding kubernetes for distributed tests

* adding proper import for OrderedDict

* adding urllib3==1.22 to address ordered_dict import error

* added sleep to allow workers to save their models for comparison

* adding name to GPU contributors under docs
2019-03-02 10:03:22 +13:00

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2.1 KiB
Docker

ARG CUDA_VERSION
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
# Environment
ENV DEBIAN_FRONTEND noninteractive
# Install all basic requirements
RUN \
yum -y update && \
yum install -y tar unzip wget xz git && \
wget http://people.centos.org/tru/devtools-2/devtools-2.repo -O /etc/yum.repos.d/devtools-2.repo && \
yum install -y devtoolset-2-gcc devtoolset-2-binutils devtoolset-2-gcc-c++ && \
# Python
wget https://repo.continuum.io/miniconda/Miniconda2-4.3.27-Linux-x86_64.sh && \
bash Miniconda2-4.3.27-Linux-x86_64.sh -b -p /opt/python && \
# CMake
wget -nv -nc https://cmake.org/files/v3.5/cmake-3.5.2-Linux-x86_64.sh --no-check-certificate && \
bash cmake-3.5.2-Linux-x86_64.sh --skip-license --prefix=/usr
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
if [ "${CUDA_SHORT}" != "10.0" ]; then \
wget https://developer.download.nvidia.com/compute/redist/nccl/v2.2/nccl_2.2.13-1%2Bcuda${CUDA_SHORT}_x86_64.txz && \
tar xf "nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64.txz" && \
cp nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64/include/nccl.h /usr/include && \
cp nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64/lib/* /usr/lib && \
rm -f nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64.txz && \
rm -r nccl_2.2.13-1+cuda${CUDA_SHORT}_x86_64; fi
ENV PATH=/opt/python/bin:$PATH
ENV CC=/opt/rh/devtoolset-2/root/usr/bin/gcc
ENV CXX=/opt/rh/devtoolset-2/root/usr/bin/c++
ENV CPP=/opt/rh/devtoolset-2/root/usr/bin/cpp
# Install Python packages
RUN \
pip install numpy pytest scipy scikit-learn wheel kubernetes urllib3==1.22
ENV GOSU_VERSION 1.10
# Install lightweight sudo (not bound to TTY)
RUN set -ex; \
wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
chmod +x /usr/local/bin/gosu && \
gosu nobody true
# Default entry-point to use if running locally
# It will preserve attributes of created files
COPY entrypoint.sh /scripts/
WORKDIR /workspace
ENTRYPOINT ["/scripts/entrypoint.sh"]