Nvidia DGX Station A100 User Manual

Getting Started with DGX Station A100
DGX Station A100 DU-10189-001 _v5.0.2|11
GPU 0: Graphics Device (UUID: GPU-269d95f8-328a-08a7-5985-ab09e6e2b751)
GPU 1: Graphics Device (UUID: GPU-0f2dff15-7c85-4320-da52-d3d54755d182)
In this example, Docker selected the first two GPUs to run the container, but if the device
option is used, you can specify which GPUs to use:
lab@ro-dvt-058-80gb:~$ docker run --gpus '"device=GPU-dc598de6-dd4d-2f43-549f-
f7b4847865a5,GPU-e32263f2-ae07-f1db-37dc-17d1169b09bf"' --rm -it ubuntu nvidia-smi -L
GPU 0: Graphics Device (UUID: GPU-dc598de6-dd4d-2f43-549f-f7b4847865a5)
GPU 1: Graphics Device (UUID: GPU-e32263f2-ae07-f1db-37dc-17d1169b09bf)
In this example, the two GPUs that were not used earlier are now assigned to run on the
container.
2.3.2. Running on Bare Metal
To run applications by using the four high performance GPUs, the CUDA_VISIBLE_DEVICES
variable must be specified before you run the application.
Note: This method does not use containers.
CUDA orders the GPUs by performance, so GPU 0 will be the highest performing GPU, and the
last GPU will be the slowest GPU.
Important: If the CUDA_DEVICE_ORDER variable is set to PCI_BUS_ID, this ordering will be
overridden.
In the following example, a CUDA application that comes with CUDA samples is run. In
the output, GPU 0 is the fastest in a DGX Station A100, and GPU 4 (DGX Display GPU) is the
slowest:
lab@ro-dvt-058-80gb:~$ sudo apt install cuda-samples-11-2
lab@ro-dvt-058-80gb:~$ cd /usr/local/cuda-11.2/samples/1_Utilities/p2pBandwidthLatencyTest
lab@ro-dvt-058-80gb:/usr/local/cuda-11.2/samples/1_Utilities/p2pBandwidthLatencyTest
$ sudo make
/usr/local/cuda/bin/nvcc -ccbin g++ -I../../common/inc -m64 --threads
0 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37
-gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52
-gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61
-gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75
-gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86
-gencode arch=compute_86,code=compute_86 -o p2pBandwidthLatencyTest.o -c
p2pBandwidthLatencyTest.cu
nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and
'sm_50' architectures are deprecated, and may be removed in a future release (Use -
Wno-deprecated-gpu-targets to suppress warning).
/usr/local/cuda/bin/nvcc -ccbin g++ -m64
-gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37
-gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52
-gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61
-gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75
-gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86
-gencode arch=compute_86,code=compute_86 -o p2pBandwidthLatencyTest
p2pBandwidthLatencyTest.o
nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and
'sm_50' architectures are deprecated, and may be removed in a future release (Use -
Wno-deprecated-gpu-targets to suppress warning).
mkdir -p ../../bin/x86_64/linux/release
cp p2pBandwidthLatencyTest ../../bin/x86_64/linux/release
lab@ro-dvt-058-80gb:/usr/local/cuda-11.2/samples/1_Utilities/p2pBandwidthLatencyTest
$ cd /usr/local/cuda-11.2/samples/bin/x86_64/linux/release

Nvidia DGX Station A100 Specifications

General

Brand	Nvidia
Model	DGX Station A100
Category	Desktop
Language	English