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Ray Scheduler Prototype

Overview

Aims of the scheduler prototype include the following:

  • Same APIs as a production scheduler
  • Easy to add new algorithms
  • Able to replay production logs
  • Support unit tests for core scheduler and for database (Redis) integration

Usage Example

(NUM_NODES=3
NUM_WORKERS_PER_NODE=1
for trace in $(ls traces/*.json); do
    python replaytrace.py $NUM_NODES $NUM_WORKERS_PER_NODE 0.001 trivial $trace;
done)

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Experimental code for Ray scheduler evaluation

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  • Python 100.0%