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Learning frameworks are tuned, optimized, tested, and containerized for your use. To optimize and tune the frameworks for GPUs. Moreover, these frameworks are being updated weekly, if not daily. Containers can be used to resolve network-port conflicts between applications by mappingĬontainer-ports to specific externally-visible ports when launching the container.īuilding deep learning frameworks can be quite a bit of work and can be very time consuming.Having one or more specific GPUs assigned.
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Multiple instances of a given deep learning framework can be run concurrently with each.You can easily share, collaborate, and test applications across different.Specific GPU resources can be allocated to a container for isolation and better.Legacy accelerated compute applications can be containerized and deployed on newer.
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Systems uses Docker containers as the mechanism forĪ Docker container is composed of layers. Therefore, all kernel calls from the container are handled by the host system kernel. Unlike a VM which has its own isolated kernel, containers use the host system kernel. Its libraries, data files, and environment variables so that the execution environment isĪlways the same, on whatever Linux system it runs and between instances on the same host. A Docker container is a mechanism for bundling a Linux application with all of