Abstract

This support matrix is for NVIDIA optimized frameworks. The matrix provides a single view into the supported software and specific versions that come packaged with the frameworks based on the container image.

1. 19.xx Framework Containers Support Matrix

Important: Content that is included in <<>> brackets indicates new content from the previously published version.
Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 19.01 release of an image was released in January, 2019.

19.xx container images

Table 1. Software stack packaged with the 19.xx container images
  Container Image 19.06 19.05 19.04 19.03 19.02 19.01
Supported Platform Host OS DGX OS Server
  • 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.1.0+, 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.1.0+, 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.1.0+, 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.1.0+, 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
NVIDIA Driver

Release 19.06 is based on <<CUDA 10.1.168>>, which requires NVIDIA driver release 418.xx.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410.

The CUDA driver's compatibility package only supports particular drivers (see footnote for more information). 1

Release 19.05 is based on CUDA 10.1 Update 1, which requires NVIDIA driver release 418.xx.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410.

The CUDA driver's compatibility package only supports particular drivers (see footnote for more information). 2

Release 19.04 is based on CUDA 10.1, which requires NVIDIA driver release 418.xx.x+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410.

The CUDA driver's compatibility package only supports particular drivers (see footnote for more information). 3

Release 19.03 is based on CUDA 10.1, which requires NVIDIA driver release 418.xx+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+ or 410.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Release 19.02 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Release 19.01 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Supported Hardware GPU Model
Base Image Container OS Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04
CUDA <<10.1.168>> 10.1 Update 1 10.1.105 10.1.105 10.0.130 10.0.130
cuBLAS <<10.2.0.168>> 10.1 Update 1 10.1.0.105 10.1.105 10.0.130 10.0.130
cuDNN 7.6.0 7.6.0 7.5.0 7.5.0 7.4.2 7.4.2
NCCL <<2.4.7>> 2.4.6 2.4.6 2.4.3 2.3.7 2.3.7
NVIDIA Optimized Frameworks Kaldi 5.5 including 5.5 including 5.5 including 5.5 including    
Docker image size: 5.11 GB Docker image size: 5.11 GB Docker image size: 5.01 GB Docker image size: 5.09 GB    
NVCaffe 0.17.3 including 0.17.3 including 0.17.3 including 0.17.3 including 0.17.2 including 0.17.2 including
Docker image size: 4.33 GB Docker image size: 4.33 GB Docker image size: 4.29 GB Docker image size: 4.42 GB Docker image size: 3.56 GB Docker image size: 3.51 GB
DIGITS 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including
  • TensorFlow Docker image size: 7.86 GB
  • Caffe Docker image size: 4.45 GB
  • TensorFlow Docker image size: 7.00 GB
  • Caffe Docker image size: 4.45 GB
  • TensorFlow Docker image size: 7.04 GB
  • Caffe Docker image size: 4.41 GB
  • TensorFlow Docker image size: 6.92 GB
  • Caffe Docker image size: 4.49 GB
  • TensorFlow Docker image size: 6.43 GB
  • Caffe Docker image size: 3.70 GB
  • TensorFlow Docker image size: 5.96 GB
  • Caffe Docker image size: 3.66 GB
MXNet <<1.4.1>> including 1.4.0 commit 87c7addcd from February 12, 2019 including 1.4.0 commit 87c7addcd from February 12, 2019 including 1.4.0 including 1.4.0.rc0 including 1.4.0.rc0 including
Docker image size: 4.99 GB Docker image size: 4.95 GB Docker image size: 4.9 GB Docker image size: 4.73 GB Docker image size: 3.83 GB Docker image size: 3.82 GB
PyTorch <<1.1.0commit 0885dd28 from May 28, 2019>> including 1.0.1commit 828a6a3b from March 31, 2019 including 1.0.1commit 9eb0f43 from March 28, 2019 including 1.1.0a0+81e025d including 1.1.0a0+c42431b including 1.0.0 including
Docker image size: 7.7 GB Docker image size: 7.55 GB Docker image size: 7.45 GB Docker image size: 7.71 GB Docker image size: 6.61 GB Docker image size: 7.70 GB
TensorFlow 1.13.1 including 1.13.1 including 1.13.1 including 1.13.1 including 1.13.0-rc0 including 1.12.0 including
Docker image size: 6.88 GB Docker image size: 6.76 GB Docker image size: 6.8 GB Docker image size: 6.72 GB Docker image size: 6.06 GB Docker image size: 5.57 GB
TensorRT TensorRT 5.1.5 including: TensorRT 5.1.5 including: TensorRT 5.1.2 RC including: TensorRT 5.1.2 RC including: TensorRT 5.0.2 including: TensorRT 5.0.2 including:
Docker image size: 3.83 GB Docker image size: 3.83 GB Docker image size: 3.79 GB Docker image size: 3.91 GB Docker image size: 3.01 GB Docker image size: 3.00 GB
TensorRT Inference Server <<1.3.0>> including 1.2.0 including 1.1.0 including 1.0.0 including 0.11.0 Beta including 0.10.0 Beta including
Docker image size: 7.15 GB Docker image size: 7.02 GB Docker image size: 5.22 GB Docker image size: 5.33 GB Docker image size: 4.42 GB Docker image size: 4.17 GB
TensorFlow For Jetson   TensorFlow 1.13.1 for Jetson AGX Xavier TensorFlow 1.13.1 for Jetson AGX Xavier TensorFlow 1.13.1 for Jetson AGX Xavier TensorFlow 1.13.0-rc0 for Jetson AGX Xavier TensorFlow 1.12.0 for Jetson AGX Xavier
TensorFlow For TensorRT (TF-TRT) <<TensorFlow 1.13.1 with TensorRT 5.1.5 using the 19.06 container>> TensorFlow 1.13.1 with TensorRT 5.1.5 using the 19.05 container TensorFlow 1.13.1 with TensorRT 5.1.2 RC using the 19.04 container TensorFlow 1.13.1 with TensorRT 5.1.2 RC using the 19.03 container TensorFlow 1.13.0-rc0 with TensorRT 5.0.2 using the 19.02 container TensorFlow 1.12.0 with TensorRT 5.0.2 using the 19.01 container

18.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 18.01 release of an image was released in January, 2018.

18.xx container images

Table 2. Software stack packaged with the 18.xx container images
  Container Image 18.12 18.11 18.10 18.09 18.08 18.07 18.06 18.05 18.04 18.03 18.02 18.01
Supported Platform Host OS DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
DGX OS Server
  • 4.0.4+, 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 4.0.4+ and 3.1.2+ (DGX Station)
DGX Software Stack for Red Hat Enterprise Linux
  • EL7-18.11 (DGX-1)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
DGX OS Server
  • 3.1.2+ and 2.1.1+ (DGX-1)
  • 4.0.1+ (DGX-2)
DGX OS Desktop
  • 3.1.2+ (DGX Station)
NVIDIA Driver

Release 18.12 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Release 18.11 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Release 18.10 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Release 18.09 is based on CUDA 10.0, which requires NVIDIA driver release 410.72+.

However, if you are running on Tesla (Tesla V100, Tesla P4, Tesla P40, or Tesla P100), you may use NVIDIA driver release 384.111+.

The CUDA driver's compatibility package only supports particular drivers (see footnote 1).

Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Ubuntu 16.04
NVIDIA Driver 384.xx+
Supported Hardware GPU Model Volta and Pascal Volta and Pascal Volta and Pascal Volta and Pascal Volta and Pascal Volta and Pascal Volta and Pascal Volta and Pascal
Base Image Container OS Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04 Ubuntu 16.04
CUDA 10.0.130 10.0.130 10.0.130 10.0.130 includes:
  • Support for DGX-2
  • Support for Turing
  • Support for Jetson Xavier
  • CUDA 10 compatibility package version 410.484
9.0.176 9.0.176 9.0.176 9.0.176 9.0.176 9.0.176 9.0.176 9.0.176
cuBLAS 10.0.130 10.0.130 10.0.130 10.0.130 9.0.425 9.0.425 9.0.333 9.0.333 9.0.333 9.0.333 9.0.282 Patch 2 and cuBLAS 9.0.234 Patch 1 9.0.282 Patch 2
cuDNN 7.4.1 7.4.1 7.4.0 7.3.0 7.2.1 7.1.4 7.1.4 7.1.2 7.1.1 7.1.1 7.0.5 7.0.5
NCCL 2.3.7 2.3.7 2.3.6 2.3.4 2.2.13 2.2.13 2.2.13 2.1.15 2.1.15 2.1.2 2.1.2 2.1.2
NVIDIA Optimized Frameworks NVCaffe 0.17.2 including 0.17.1 including 0.17.1 including 0.17.1 including 0.17.1 including 0.17.1 and Python 2.7 0.17.0 and Python 2.7 0.17.0 and Python 2.7 0.17.0 and Python 2.7 0.16.6 and Python 2.7 0.16.5 and Python 2.7 0.16.5 and Python 2.7
Docker image size: 3.41 GB Docker image size: 3.41 GB Docker image size: 3.41 GB Docker image size: 3.40 GB Docker image size: 3.37 GB Docker image size: 4.29 GB
Caffe2         0.8.1 including 0.8.1 including 0.8.1 including 0.8.1 including 0.8.1 including 0.8.1 including 0.8.1 including 0.8.1 including
        Docker image size: 3.02 GB Docker image size: 2.94 GB
DIGITS 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.1 including 6.1.0 including 6.1.0 including 6.0.0 including
  • TensorFlow Docker image size: 5.03 GB
  • Caffe Docker image size: 3.56 GB
  • TensorFlow Docker image size: 5.03 GB
  • Caffe Docker image size: 3.56 GB
Docker image size: 6.17 GB Docker image size: 5.33 GB Docker image size: 6.20 GB Docker image size: 7.16 GB
Microsoft Cognitive Toolkit         2.5 including 2.5 including 2.5 including 2.5 including 2.4 including 2.4 including 2.3.1 including 2.3.1 including
        Docker image size: 6.17 GB Docker image size: 6.13 GB
MXNet 1.3.1 including 1.3.0 including 1.3.0 including 1.3.0 including 1.2.0 including 1.2.0 including 1.2.0 including 1.1.0 including 1.1.0 including 1.1.0 including 1.0.0 including 1.0.0 including
Docker image size: 3.69 GB Docker image size: 3.69 GB Docker image size: 3.68 GB Docker image size: 3.58 GB Docker image size: 4.09 GB Docker image size: 3.93 GB
PyTorch 0.4.1+ including 0.4.1+ including 0.4.1+ including 0.4.1+ including 0.4.1 including 0.4.0 including 0.4.0 including 0.4.0 including 0.3.1 and Python 3.6 0.3.0 and Python 3.6 0.3.0 and Python 3.6 0.3.0 and Python 3.6
Docker image size: 6.08 GB Docker image size: 6.08 GB Docker image size: 6.00 GB Docker image size: 5.89 GB Docker image size: 5.64 GB Docker image size: 5.67 GB
TensorFlow 1.12.0 including 1.12.0-rc2 including 1.10.0 including 1.10.0 including 1.9.0 including 1.8.0 including 1.8.0 including 1.7.0 including 1.7.0 including 1.4.0 including 1.4.0 including 1.4.0 including
Docker image size: 4.64 GB Docker image size: 4.64 GB Docker image size: 4.57 GB Docker image size: 3.75 GB Docker image size: 3.40 GB Docker image size: 3.34 GB
TensorFlow For Jetson     TensorFlow 1.10.0 on JetPack 4.1 Developer Early Access for Jetson AGX Xavier TensorFlow 1.10.0 on JetPack 4.1 Developer Early Access for Jetson AGX Xavier TensorFlow 1.9.0 on JetPack 3.2 for Jetson TX2              
TensorRT TensorRT 5.0.2 including: TensorRT 5.0.2 including: TensorRT 5.0.0 RC including: TensorRT 5.0.0 RC including Python 2.7 or Python 3.5 4.0.1 and Python 2.7 or Python 3.5 4.0.1 and Python 2.7 or Python 3.5 4.0.1 and Python 2.7 or Python 3.5 3.0.4 and Python 2.7 3.0.4 and Python 2.7 3.0.4 and Python 2.7 3.0.4 and Python 2.7 3.0.1 and Python 2.7
Docker image size: 3.00 GB Docker image size: 3.00 GB Docker image size: 2.99 GB Docker image size: 2.98 GB Docker image size: 2.56 GB Docker image size: 2.61 GB
TensorRT Inference Server 0.9.0 Beta including 0.8.0 Beta including 0.7.0 Beta including 0.6.0 Beta including 0.5.0 Beta including 0.4.0 Beta including 0.3.0 Beta including 0.2.0 Beta including 0.1.0 Beta      
Docker image size: 4.17 GB Docker image size: 4.17 GB Docker image size: 4.15 GB Docker image size: 4.42 GB Docker image size: 2.37 GB Docker image size: 2.47 GB
Theano         1.0.2 and Python 2.7 1.0.2 and Python 2.7 1.0.1 and Python 2.7 1.0.1 and Python 2.7 1.0.1 and Python 2.7 1.0.1 and Python 2.7 1.0.1 and Python 2.7 1.0.1 and Python 2.7
        Docker image size: 3.70 GB Docker image size: 3.74 GB
Torch         7 and Python 2.7 7 and Python 2.7 7 and Python 2.7 7 and Python 2.7 7 and Python 2.7 7 and Python 2.7 7 and Python 2.7 7 and Python 2.7
        Docker image size: 3.06 GB Docker image size: 3 GB

17.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 17.01 release of an image was released in January, 2017.

17.xx container images

Table 3. Software stack packaged with the 17.xx container images
  Container Image 17.12 17.11 17.10 17.09 17.07 17.06 17.05 17.04 17.03 17.02 17.01
Supported Platform DGX OS 3.1.2+ and 2.1.1+ 3.1.2+ and 2.1.1+ 3.1.2+ and 2.1.1+ 3.1.2+ and 2.1.1+ 2.x+ and 1.x+ 2.x+ and 1.x+ 2.x+ and 1.x+ 2.x+ and 1.x+ 2.x+ and 1.x+ 2.x+ and 1.x+ 2.x+ and 1.x+
NVIDIA Driver 384 384 384 384              
Base Image Ubuntu 16.04 16.04 16.04 16.04 16.04 16.04 16.04 16.04 16.04 14.04 14.04
CUDA 9.0.176 9.0.176 9.0 9.0 8.0.61.2 8.0.61 8.0.61 8.0.61 8.0.61 8.0.61 8.0.54
cuBLAS 9.0.234 9.0.234     patch 2            
cuDNN 7.0.5 7.0.4 7.0.3 7.0.2 6.0.21 6.0.21 6.0.21 6.0.20 6.0.20 6.0.13 6.0.10
NCCL 2.1.2 2.1.2 2.0.5 2.0.5 2.0.3 1.6.1 1.6.1 1.6.1 1.6.1 1.6.1 1.6.1
NVIDIA Optimized Frameworks NVCaffe 0.16.4 0.16.4 0.16.4 0.16.4 0.16 0.16 0.16 0.16 0.16 0.16 0.16
Caffe2 0.8.1 and OpenMPI 1.10.3 0.8.1 and OpenMPI 1.10.3 0.8.1 and OpenMPI 1.10.3 0.8.1 and OpenMPI 1.10.3 0.7.0 and OpenMPI 1.10.3 0.7.0 and OpenMPI 1.10.3 0.5.0+ and OpenMPI 1.10.3 0.5.0+ and OpenMPI 1.10.3      
DIGITS 6.0.0 including 6.0.0 including 6.0.0 including 6.0.0 including 6.0.0 including 5.0 including 5.0 including 5.0 including 5.0 including 5.0 including 5.0 including
Microsoft Cognitive Toolkit 2.2 and OpenMPI 3.0.0 2.2 and OpenMPI 3.0.0 2.2 2.1 2.0 2.0 2.0.rc2 2.0.beta15.0 2.0.beta12.0 2.0.beta9.0 2.0.beta5.0
MXNet 1.0.0 0.12.0 0.11.0 0.11.0.rc3 0.10.0 0.10.0 0.9.3a+ 0.9.3a+ 0.9.3    
PyTorch 0.2.0 0.2.0 0.2.0 0.2.0 0.1.12 0.1.12 0.1.12 0.1.10      
TensorFlow 1.4.0 1.3.0 1.3.0 1.3.0 1.2.1 1.1.0 1.0.1 1.0.1 1.0.0 0.12.1 0.12.0
TensorRT 3.0.1                    
Theano 1.0.0rc1 1.0.0rc1 0.10beta3 0.10beta1 0.9.0 0.9.0 0.9.0 0.9.0 0.9.0rc3 0.8.0 0.8.0
Torch 7 7 7 7 7 7 7 7 7 7 7

16.xx Framework Containers Support Matrix

Note: The deep learning framework container packages follow a naming convention that is based on the year and month of the image release. For example, the 16.12 release of an image was released in December, 2016.

16.xx container images

Table 4. Software stack packaged with the 16.xx container images
  Container Image 16.12
Supported Platform DGX OS 2.x+ and 1.x+
NVIDIA Driver  
Base Image Ubuntu 14.04
CUDA 8.0.54
cuBLAS  
cuDNN 6.0.5
NCCL 1.6.1
NVIDIA Optimized Frameworks NVCaffe 0.16
Caffe2  
DIGITS 5.0 including
Microsoft Cognitive Toolkit 2.0.beta5.0
MXNet  
PyTorch  
TensorFlow 0.12.0
TensorRT  
Theano 0.8.0
Torch 7

Notices

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Trademarks

NVIDIA, the NVIDIA logo, DGX, DGX-1, DGX-2, and DGX Station are trademarks and/or registered trademarks of NVIDIA Corporation in the Unites States and other countries. Other company and product names may be trademarks of the respective companies with which they are associated.

1 For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.
2 For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.
3 For a complete list of supported drivers, see the CUDA Application Compatibility topic. For more information, see CUDA Compatibility and Upgrades.
4 The compatibility package ensures that Linux drivers R384 are compatible with Tesla GPUs.