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- Third Party Software: I want the latest version CUDA software. Should I pick it up from NVIDIA? Answer: I want the latest version CUDA software. Should I pick it up from NVIDIA? No. But its version is higher. And I want the latest on my ...
- Third Party Software: How do I upgrade to CUDA 5.5? Answer: How do I upgrade from, say, CUDA 5 to to CUDA 5.5? By replacing the old packages with the new ones appropriately. Details follow: Contents 1 How do ...
- Third Party Software: How can I use CUDA MPS with Bright? Answer: Introduction CUDA MPS is a feature that allows multiple CUDA processes to share a single GPU context. A CUDA program runs in MPS mode, if the ...
- General: I want the latest version CUDA software. Should I pick it up from NVIDIA? Answer: I want the latest version CUDA software. Should I pick it up from NVIDIA? No. But its version is higher. And I want the latest on my ...
- Containers: How can I use GPUs with Bright Deep learning stack? Answer: This is a Dockerfile that can be used to create a Bright Deep Learning Docker image. Once instantiated using the nvidia-docker command, applications running within ...
- Configuring: How do I create an InfiniBand subinterface? Answer: How do I create an IB subinterface? Subinterfaces divide primary (parent) interfaces to provide traffic isolation. Partition assignments distinguish subinterfaces from parent interfaces. Subinterface creation and ...
- NVIDIA DGX: How do I add NVIDIA DGX nodes to a Bright cluster using the official Ubuntu Answer: How do I add NVIDIA DGX nodes to a Bright cluster using the official Ubuntu DGX software stack? Bright provides a software image for the official ...
- Containers: Installing NVIDIA docker on Bright 8.0 Answer: Preliminary support for NVIDIA docker has been implemented for 8.0, deeper integration with Bright Cluster Manager is still a work in progress. It is recommended to ...
- Containers: How do I configure Kubernetes to use NVIDIA GPUs on a Bright 8.0 cluster? Answer: Kubernetes 1.6 allows NVIDIA GPUs to be used from within containers. However, one GPU cannot be shared among multiple containers. This means that if there are ...