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* Added NCCL Nsight files Signed-off-by: Ankur Srivastava <[email protected]> * Added NCCL Nsight files Signed-off-by: Ankur Srivastava <[email protected]> * Updateed nccl and readme and fsdp Signed-off-by: Ankur Srivastava <[email protected]> * Updated NCCL Signed-off-by: Ankur Srivastava <[email protected]> * Added almost everything Signed-off-by: Ankur Srivastava <[email protected]> * Removed token Signed-off-by: Ankur Srivastava <[email protected]> --------- Signed-off-by: Ankur Srivastava <[email protected]>
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4.validation_and_observability/5.nsight/2.generate_recipes.sh
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_api_sum --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_api_sync --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_kern_pace --input ${NSIGHT_REPORT_NAME}.nsys-rep --name ncclDevKernel_ReduceScatter_Sum_f32_RING_LL | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_kern_pace --input ${NSIGHT_REPORT_NAME}.nsys-rep --name ncclDevKernel_AllGather_RING_LL | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_kern_sum --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_mem_size_sum --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_mem_time_sum --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe cuda_gpu_time_util_map --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe nccl_sum --input ${NSIGHT_REPORT_NAME}.nsys-rep | ||
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/fsx/nsight-efa/target-linux-x64/nsys recipe nccl_gpu_time_util_map --input ${NSIGHT_REPORT_NAME}.nsys-rep |
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4.validation_and_observability/5.nsight/EKS/Dockerfile.llama2-efa
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apiVersion: "kubeflow.org/v1" | ||
kind: PyTorchJob | ||
metadata: | ||
name: fsdp | ||
spec: | ||
elasticPolicy: | ||
rdzvBackend: etcd | ||
rdzvHost: etcd | ||
rdzvPort: 2379 | ||
minReplicas: 1 | ||
maxReplicas: 96 | ||
maxRestarts: 100 | ||
#metrics: | ||
# - type: Resource | ||
# resource: | ||
# name: cpu | ||
# target: | ||
# type: Utilization | ||
# averageUtilization: 80 | ||
pytorchReplicaSpecs: | ||
Worker: | ||
replicas: 2 | ||
restartPolicy: OnFailure | ||
template: | ||
metadata: | ||
labels: | ||
app: fsdp | ||
nvidia-devtools-sidecar-injector: enabled | ||
spec: | ||
volumes: | ||
- name: shmem | ||
#emptyDir: | ||
# medium: Memory | ||
hostPath: | ||
path: /dev/shm | ||
#nodeSelector: | ||
# node.kubernetes.io/instance-type: "p5.48xlarge" | ||
containers: | ||
- name: pytorch | ||
image: 159553542841.dkr.ecr.us-west-2.amazonaws.com/fsdp:llama2-efa-main-02-13 | ||
imagePullPolicy: Always | ||
resources: | ||
requests: | ||
nvidia.com/gpu: | ||
vpc.amazonaws.com/efa: 4 | ||
limits: | ||
nvidia.com/gpu: | ||
vpc.amazonaws.com/efa: 4 | ||
env: | ||
# for P5 FI_* should be commented out | ||
#- name: LOGLEVEL | ||
# value: "DEBUG" | ||
- name: FI_PROVIDER | ||
value: efa | ||
- name: FI_EFA_USE_DEVICE_RDMA | ||
value: "1" | ||
- name: FI_EFA_FORK_SAFE | ||
value: "1" | ||
- name: FI_LOG_LEVEL | ||
value: "1" | ||
- name: FI_EFA_ENABLE_SHM_TRANSFER | ||
value: "1" | ||
#- name: NCCL_DEBUG | ||
# value: "INFO" | ||
- name: NCCL_ASYNC_ERROR_HANDLING | ||
value: "1" | ||
#- name: NCCL_IGNORE_DISABLED_P2P | ||
# value: "1" | ||
- name: HF_TOKEN | ||
value: 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 | ||
command: | ||
- bash | ||
- -c | ||
- "torchrun --nproc_per_node=8 --nnodes=2 examples/finetuning.py --num_epochs=1 --batch_size_training=3 --enable_fsdp --pure_bf16 --model_name meta-llama/Llama-2-7b-hf --output_dir ." | ||
volumeMounts: | ||
- name: shmem | ||
mountPath: /dev/shm | ||
root@cb9511473ccc:/eks/deployment/distributed-training/pytorch/pytorchjob/fsdp# cat Dockerfile.llama2-efa | ||
FROM nvidia/cuda:12.2.2-devel-ubuntu22.04 | ||
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ARG EFA_INSTALLER_VERSION=1.29.1 | ||
ARG AWS_OFI_NCCL_VERSION=v1.7.3-aws | ||
ARG NCCL_TESTS_VERSION=master | ||
ARG NCCL_VERSION=2.18.5 | ||
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RUN apt-get update -y | ||
RUN apt-get remove -y --allow-change-held-packages \ | ||
libmlx5-1 ibverbs-utils libibverbs-dev libibverbs1 libnccl2 libnccl-dev | ||
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RUN rm -rf /opt/hpcx \ | ||
&& rm -rf /usr/local/mpi \ | ||
&& rm -f /etc/ld.so.conf.d/hpcx.conf \ | ||
&& ldconfig | ||
ENV OPAL_PREFIX= | ||
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RUN DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \ | ||
git \ | ||
gcc \ | ||
vim \ | ||
kmod \ | ||
openssh-client \ | ||
openssh-server \ | ||
build-essential \ | ||
curl \ | ||
autoconf \ | ||
libtool \ | ||
gdb \ | ||
automake \ | ||
python3-distutils \ | ||
cmake \ | ||
apt-utils \ | ||
devscripts \ | ||
debhelper \ | ||
libsubunit-dev \ | ||
check \ | ||
pkg-config | ||
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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 /usr/local/cuda/extras/CUPTI/lib64:/opt/amazon/openmpi/lib:/opt/nccl/build/lib:/opt/amazon/efa/lib:/opt/aws-ofi-nccl/install/lib:/usr/local/lib:$LD_LIBRARY_PATH | ||
ENV PATH /opt/amazon/openmpi/bin/:/opt/amazon/efa/bin:/usr/bin:/usr/local/bin:$PATH | ||
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RUN curl https://bootstrap.pypa.io/get-pip.py -o /tmp/get-pip.py \ | ||
&& python3 /tmp/get-pip.py \ | ||
&& pip3 install awscli pynvml | ||
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################################################# | ||
## Install NVIDIA GDRCopy | ||
#RUN git clone https://github.com/NVIDIA/gdrcopy.git /opt/gdrcopy \ | ||
# && cd /opt/gdrcopy \ | ||
# && make lib_install install \ | ||
# && cd /opt/gdrcopy/tests \ | ||
# && make \ | ||
# && mv copylat copybw sanity apiperf /usr/bin/ | ||
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################################################# | ||
## Install EFA installer | ||
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 $HOME/aws-efa-installer | ||
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################################################### | ||
## Install NCCL | ||
RUN git clone https://github.com/NVIDIA/nccl -b v${NCCL_VERSION}-1 /opt/nccl \ | ||
&& cd /opt/nccl \ | ||
&& make -j $(nproc) src.build CUDA_HOME=/usr/local/cuda \ | ||
NVCC_GENCODE="-gencode=arch=compute_80,code=sm_80 -gencode=arch=compute_86,code=sm_86 -gencode=arch=compute_90,code=sm_90" | ||
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################################################### | ||
## Install AWS-OFI-NCCL plugin | ||
RUN apt-get install libtool autoconf cmake nasm unzip pigz parallel nfs-common build-essential hwloc libhwloc-dev libjemalloc2 libnuma-dev numactl libjemalloc-dev preload htop iftop liblapack-dev libgfortran5 ipcalc wget curl devscripts debhelper check libsubunit-dev fakeroot pkg-config dkms -y | ||
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 ${AWS_OFI_NCCL_VERSION} \ | ||
&& ./autogen.sh \ | ||
&& ./configure --prefix=/opt/aws-ofi-nccl/install \ | ||
--with-libfabric=/opt/amazon/efa/ \ | ||
--with-cuda=/usr/local/cuda \ | ||
--with-nccl=/opt/nccl/build \ | ||
--with-mpi=/opt/amazon/openmpi/ \ | ||
&& make -j $(nproc) && make install | ||
################################################### | ||
## Install fsdp | ||
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RUN mkdir -p /workspace/ | ||
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WORKDIR /workspace | ||
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#RUN git clone -b flop_counter https://github.com/facebookresearch/llama-recipes.git | ||
#RUN git clone -b flop_counter_gc https://github.com/facebookresearch/llama-recipes.git | ||
RUN git clone https://github.com/facebookresearch/llama-recipes.git | ||
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WORKDIR /workspace/llama-recipes | ||
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RUN pip3 install -U pip setuptools | ||
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RUN pip3 install fsspec==2023.1.0 | ||
RUN pip3 install huggingface_hub==0.17.0 | ||
RUN pip3 install -r requirements.txt | ||
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RUN pip3 install -e . | ||
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RUN pip3 install tabulate | ||
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RUN pip3 install protobuf | ||
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RUN pip3 install python-etcd | ||
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#RUN pip3 uninstall -y torch | ||
#RUN pip3 install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121 | ||
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ENV PYTHONPATH="${PYTHONPATH}:/workspace/llama-recipes/src" |
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4.validation_and_observability/5.nsight/EKS/custom_values.yaml
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# If we dont specify the Nsight image, 2024.2 version is used by default. | ||
# Will use 2024.4 version which is planned to be released by 5/24/2024 | ||
devtoolBinariesImage: | ||
image: ${REGISTRY}.dkr.ecr.${REGION}.amazonaws.com/nsight-systems-cli:2024.4.1-ubuntu22.04 | ||
imagePullPolicy: Always | ||
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# Assuming EKS cluster has a FSx for Lustre filesystem mounted on it. Nsight reports will be saved in /fsx_shared | ||
profile: | ||
volumes: | ||
[ | ||
{ | ||
"name": "nsys-output-volume", | ||
"persistentVolumeClaim": { "claimName": "fsx-pvc" } | ||
} | ||
] | ||
volumeMounts: | ||
[ | ||
{ | ||
"name": "nsys-output-volume", | ||
"mountPath": "/fsx_shared" | ||
} | ||
] | ||
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# CLI options: https://docs.nvidia.com/nsight-systems/UserGuide/index.html#cli-command-switches | ||
# delay and duration values in secs | ||
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# Use %{} to include environment variables in the Nsight report filename | ||
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# The arguments for the Nsight Systems. The placeholders will be replaced with the actual values. | ||
devtoolArgs: "profile --force-overwrite true --trace nvtx,cuda --delay 150 --duration 60 \ | ||
-o /fsx_shared/fsdp/auto_{PROCESS_NAME}_%{POD_FULLNAME}_%{CONTAINER_NAME}_{TIMESTAMP}_{UID}.nsys-rep" | ||
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injectionMatch: "^/usr/bin/python3 /usr/local/bin/torchrun.*$" | ||
#injectionMatch: "^.*torchrun.*$" | ||
|
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apiVersion: "kubeflow.org/v1" | ||
kind: PyTorchJob | ||
metadata: | ||
name: fsdp | ||
spec: | ||
elasticPolicy: | ||
rdzvBackend: etcd | ||
rdzvHost: etcd | ||
rdzvPort: 2379 | ||
minReplicas: 1 | ||
maxReplicas: 96 | ||
maxRestarts: 100 | ||
#metrics: | ||
# - type: Resource | ||
# resource: | ||
# name: cpu | ||
# target: | ||
# type: Utilization | ||
# averageUtilization: 80 | ||
pytorchReplicaSpecs: | ||
Worker: | ||
replicas: 2 | ||
restartPolicy: OnFailure | ||
template: | ||
metadata: | ||
labels: | ||
app: fsdp | ||
nvidia-devtools-sidecar-injector: enabled | ||
spec: | ||
volumes: | ||
- name: shmem | ||
#emptyDir: | ||
# medium: Memory | ||
hostPath: | ||
path: /dev/shm | ||
#nodeSelector: | ||
# node.kubernetes.io/instance-type: "p5.48xlarge" | ||
containers: | ||
- name: pytorch | ||
image: 159553542841.dkr.ecr.us-west-2.amazonaws.com/fsdp:llama2-efa-main-02-13 | ||
imagePullPolicy: Always | ||
resources: | ||
requests: | ||
nvidia.com/gpu: | ||
vpc.amazonaws.com/efa: 4 | ||
limits: | ||
nvidia.com/gpu: | ||
vpc.amazonaws.com/efa: 4 | ||
env: | ||
# for P5 FI_* should be commented out | ||
#- name: LOGLEVEL | ||
# value: "DEBUG" | ||
- name: FI_PROVIDER | ||
value: efa | ||
- name: FI_EFA_USE_DEVICE_RDMA | ||
value: "1" | ||
- name: FI_EFA_FORK_SAFE | ||
value: "1" | ||
- name: FI_LOG_LEVEL | ||
value: "1" | ||
- name: FI_EFA_ENABLE_SHM_TRANSFER | ||
value: "1" | ||
#- name: NCCL_DEBUG | ||
# value: "INFO" | ||
- name: NCCL_ASYNC_ERROR_HANDLING | ||
value: "1" | ||
#- name: NCCL_IGNORE_DISABLED_P2P | ||
# value: "1" | ||
- name: HF_TOKEN | ||
value: <HF_token> | ||
command: | ||
- bash | ||
- -c | ||
- "torchrun --nproc_per_node=8 --nnodes=2 examples/finetuning.py --num_epochs=1 --batch_size_training=3 --enable_fsdp --pure_bf16 --model_name meta-llama/Llama-2-7b-hf --output_dir ." | ||
volumeMounts: | ||
- name: shmem | ||
mountPath: /dev/shm |
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4.validation_and_observability/5.nsight/EKS/fsdp_eks_report_screenshot.png
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#!/bin/bash -x | ||
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helm install -f custom_values.yaml \ | ||
devtools-sidecar-injector https://helm.ngc.nvidia.com/nvidia/devtools/charts/devtools-sidecar-injector-1.0.0.tgz |
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#!/bin/bash -x | ||
kubectl label namespaces ${example-ns} nvidia-devtools-sidecar-injector=enabled --overwrite=true |
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#!/bin/bash -x | ||
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# kubectl cp -n <namespace> <pod-name>:<path> <destination-on-local-system> | ||
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FILE=auto_python3_default_fsdp-worker-1_pytorch_1715996702335_5a061871.nsys-rep | ||
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kubectl cp fsx-share-test:fsx_shared/fsdp/$FILE /eks/deployment/distributed-training/pytorch/pytorchjob/fsdp/$FILE | ||
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aws s3 cp $FILE s3://${S3_BUCKET} | ||
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4.validation_and_observability/5.nsight/EKS/uniinstall-injector
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#!/bin/bash -x | ||
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helm uninstall devtools-sidecar-injector | ||
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kubectl delete namespace nvidia-devtools-sidecar-injector | ||
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kubectl delete mutatingwebhookconfigurations sidecar-injector-webhook | ||
kubectl delete mutatingwebhookconfiguration nvidia-devtools-sidecar-injector-webhook | ||
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kubectl delete cm -n example-ns nvidia-devtools-sidecar-injector | ||
kubectl delete cm -n example-ns nvidia-devtools-sidecar-injector-custom | ||
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kubectl delete cm nvidia-devtools-sidecar-injector | ||
kubectl delete cm nvidia-devtools-sidecar-injector-custom | ||
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#kubectl get all --all-namespaces -l nvidia-devtools-sidecar-injector=enabled -o custom-columns=:.metadata.name,NS:.metadata.namespace,KIND:.kind --no-headers | while read name namespace > |
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