[GraphBolt][CUDA] Cooperative Minibatching - Feature Loading

[mfbalin]

Description

Towards implementing #7273. We reuse the all_to_all function for feature loading.

Follow-up PRs will refactor the functionality added so far, add more tests, fixing any bugs and adding a multiGPU example utilizing the new functionality.

Checklist

Please feel free to remove inapplicable items for your PR.

• The PR title starts with [$CATEGORY] (such as [NN], [Model], [Doc], [Feature]])
• I've leverage the tools to beautify the python and c++ code.
• The PR is complete and small, read the Google eng practice (CL equals to PR) to understand more about small PR. In DGL, we consider PRs with less than 200 lines of core code change are small (example, test and documentation could be exempted).
• All changes have test coverage
• Code is well-documented
• To the best of my knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change
• Related issue is referred in this PR
• If the PR is for a new model/paper, I've updated the example index here.

Changes

[dgl-bot]

To trigger regression tests:

• @dgl-bot run [instance-type] [which tests] [compare-with-branch];
  For example: @dgl-bot run g4dn.4xlarge all dmlc/master or @dgl-bot run c5.9xlarge kernel,api dmlc/master

[dgl-bot]

Commit ID: bb03069

Build ID: 1

Status: ⚪️ CI test cancelled due to overrun.

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[dgl-bot]

Commit ID: 20bc92e

Build ID: 2

Status: ✅ CI test succeeded.

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[dgl-bot]

Commit ID: e465945

Build ID: 3

Status: ✅ CI test succeeded.

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Full logs path: link