[Umbrella] Natively support GPU configuration/discovery/scheduling/isolation on YARN

As varieties of workloads are moving to YARN, including machine learning / deep learning which can speed up by leveraging GPU computation power. Workloads should be able to request GPU from YARN as simple as CPU and memory.

To make a complete GPU story, we should support following pieces:
1) GPU discovery/configuration: Admin can either config GPU resources and architectures on each node, or more advanced, NodeManager can automatically discover GPU resources and architectures and report to ResourceManager

2) GPU scheduling: YARN scheduler should account GPU as a resource type just like CPU and memory.

3) GPU isolation/monitoring: once launch a task with GPU resources, NodeManager should properly isolate and monitor task's resource usage.

For #2, YARN-3926 can support it natively. For #3, YARN-3611 has introduced an extensible framework to support isolation for different resource types and different runtimes.

Related JIRAs:
There're a couple of JIRAs (YARN-4122/YARN-5517) filed with similar goals but different solutions:
For scheduling:

• YARN-4122/YARN-5517 are all adding a new GPU resource type to Resource protocol instead of leveraging YARN-3926.

For isolation:

• And YARN-4122 proposed to use CGroups to do isolation which cannot solve the problem listed at https://github.com/NVIDIA/nvidia-docker/wiki/GPU-isolation#challenges such as minor device number mapping; load nvidia_uvm module; mismatch of CUDA/driver versions, etc.