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Add GPU unit test
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weicongw committed Jul 9, 2024
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28 changes: 28 additions & 0 deletions e2e2/test/cases/nvidia/manifests/job-unit-test-single-node.yaml
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kind: Job
apiVersion: batch/v1
metadata:
name: unit-test-job
labels:
app: unit-test-job
spec:
template:
metadata:
labels:
app: unit-test-job
spec:
containers:
- name: unit-test-container
image: public.ecr.aws/o5d5x8n6/weicongw:nvidia
command:
- /bin/bash
- ./gpu_unit_tests/unit_test
imagePullPolicy: Always
resources:
limits:
cpu: "4"
memory: 4Gi
requests:
cpu: "1"
memory: 1Gi
restartPolicy: Never
backoffLimit: 4
100 changes: 100 additions & 0 deletions e2e2/test/images/nvidia/Dockerfile
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# Start with the NVIDIA CUDA base image
FROM nvidia/cuda:12.5.0-devel-ubuntu22.04

ARG EFA_INSTALLER_VERSION=latest
# 1.7.4+ is required, to enforce proper EFA function with OFI_NCCL_DISABLE_GDR_REQUIRED_CHECK=0
ARG AWS_OFI_NCCL_VERSION=1.9.1
ARG NCCL_TESTS_VERSION=master

# Install necessary dependencies
RUN apt-get update -y
RUN apt-get remove -y --allow-change-held-packages \
libmlx5-1 \
ibverbs-utils \
libibverbs-dev \
libibverbs1 \
libnccl2 \
libnccl-dev

RUN rm -rf /opt/hpcx \
&& rm -rf /usr/local/mpi \
&& rm -rf /usr/local/ucx \
&& rm -f /etc/ld.so.conf.d/hpcx.conf \
&& ldconfig

RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
sudo \
git \
gcc \
vim \
kmod \
openssh-client \
openssh-server \
build-essential \
wget curl \
autoconf \
libtool \
gdb \
automake \
python3-distutils \
cmake \
apt-utils \
devscripts \
debhelper \
libsubunit-dev \
check \
pkg-config \
libhwloc-dev \
datacenter-gpu-manager \
cloud-utils \
cuda-demo-suite-12-5

RUN mkdir -p /var/run/sshd
RUN sed -i 's/[ #]\(.*StrictHostKeyChecking \).*/ \1no/g' /etc/ssh/ssh_config && \
echo " UserKnownHostsFile /dev/null" >> /etc/ssh/ssh_config && \
sed -i 's/#\(StrictModes \).*/\1no/g' /etc/ssh/sshd_config
ENV LD_LIBRARY_PATH /opt/amazon/openmpi/lib64:/opt/amazon/openmpi/lib:/opt/amazon/efa/lib64:/opt/aws-ofi-nccl/install/lib:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/lib/:/usr/lib64:/usr/lib/x86_64-linux-gnu/:$LD_LIBRARY_PATH
ENV PATH /usr/local/cuda/bin:/opt/amazon/openmpi/bin:/opt/amazon/efa/bin:/usr/sbin:/usr/bin:/usr/local/bin:$PATH

# Install EFA
RUN cd $HOME \
&& curl -O https://efa-installer.amazonaws.com/aws-efa-installer-${EFA_INSTALLER_VERSION}.tar.gz \
&& tar -xf $HOME/aws-efa-installer-${EFA_INSTALLER_VERSION}.tar.gz \
&& cd aws-efa-installer \
&& ./efa_installer.sh -y -g -d --skip-kmod --skip-limit-conf --no-verify \
&& rm -rf $HOME/aws-efa-installer

# Install NCCL
RUN apt-key del 7fa2af80 \
&& curl -L -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-keyring_1.0-1_all.deb \
&& dpkg -i cuda-keyring_1.0-1_all.deb \
&& sudo apt install libnccl2=2.18.5-1+cuda12.2 libnccl-dev=2.18.5-1+cuda12.2

## Install AWS-OFI-NCCL plugin
RUN export OPAL_PREFIX="" \
&& git clone https://github.com/aws/aws-ofi-nccl.git /opt/aws-ofi-nccl \
&& cd /opt/aws-ofi-nccl \
&& git checkout v${AWS_OFI_NCCL_VERSION}-aws \
&& ./autogen.sh \
&& ./configure --prefix=/opt/aws-ofi-nccl/install \
--with-libfabric=/opt/amazon/efa/ \
--with-cuda=/usr/local/cuda \
--with-mpi=/opt/amazon/openmpi/ \
&& make && make install

# Install NCCL Tests
RUN git clone https://github.com/NVIDIA/nccl-tests.git /opt/nccl-tests \
&& cd /opt/nccl-tests \
&& git checkout ${NCCL_TESTS_VERSION} \
&& make MPI=1 \
MPI_HOME=/opt/amazon/openmpi/ \
CUDA_HOME=/usr/local/cuda


# Set a default command for debugging or modify as per requirements
ENV NCCL_PROTO simple
RUN rm -rf /var/lib/apt/lists/*
ENV LD_PRELOAD /usr/lib/x86_64-linux-gnu/libnccl.so:$LD_PRELOAD

COPY e2e2/test/images/nvidia/gpu_unit_tests ./gpu_unit_tests
RUN chmod +x ./gpu_unit_tests/unit_test
48 changes: 48 additions & 0 deletions e2e2/test/images/nvidia/gpu_unit_tests/README.md
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# What

gpu_unit_tests is the unit tests for gpu enabled platforms. Idea is to create compact
set of tests which will cover most of performance critical aspects for gpu
platforms. Test designed to run on single instance.
# Usage

```
# Run tests
./unit_test
```

**Generate test data for new instance type**

Step 1: Copy the `gpu_unit_tests` folder to the EC2 instance where you want to generate the data.

Step 2: Execute the following command in the `gpu_unit_tests` directory on the EC2 instance:
```
GENERATE_DATA=1 ./unit_test
```
Step 3:
Copy the files from `tests/test_sysinfo.sh.data` (e.g., `tests/test_sysinfo.sh.data/p3.2xlarge`) to your local repository.

Step 4:
Create PR with the new `tests/test_sysinfo.sh.data/xxx`

# Test list

- test_sysinfo.sh :: Validate basic system configuration by comparing it with test config
- test_numa_topo_topo :: check cpu/numa topology
- test_nvidia_gpu_count :: fail if one of GPUs is broken or is not visiable
- test_nvidia_fabric_status :: fail if fabric manager is not active
- test_nvidia_smi_topo :: fail if nvidia-smi topology is differ
- test_nvidia_persistence_status :: validate persistence state
- test_nvidia_gpu_unused :: Check that no other process are using GPUs, fail is a signal system misconfiguration.


- 10_test_basic_cuda.sh :: Execute trivial cuda binaries, fail if cuda subsys is not healthy
Use demo-suite binaries https://docs.nvidia.com/cuda/demo-suite/index.html and DCGM Diagnostics https://docs.nvidia.com/datacenter/dcgm/latest/user-guide/dcgm-diagnostics.html#run-levels-and-tests
If this test suite fail this is a sign that cuda subsystem is not usable at all.
Usually this is side effect of system misconfiguration (driver or fabric manager is not loaded)
- test_01_device_query
- test_02_vector_add
- test_03_bandwidth
- test_04_bus_grind
- test_05_dcgm_diagnostics


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