[PERF] Update number of cores on every iteration #1480
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xcharleslin
reviewed
Oct 10, 2023
| # This call takes about 0.3ms and hits a locally in-memory cached record of cluster resources | ||
| cores: int = int(ray.cluster_resources()["CPU"]) - self.reserved_cores | ||
| max_inflight_tasks = cores + self.max_task_backlog | ||
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| while True: # Loop: Dispatch (get tasks -> batch dispatch). | ||
| tasks_to_dispatch: list[PartitionTask] = [] | ||
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You might even want to do it here, this is where batches are dispatched up to the limit
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Github UI is being unclear, but I mean the last line of that block, 458/456
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Moved into inner loop and guarded it with a TTL
Codecov Report
Additional details and impacted files@@ Coverage Diff @@
## main #1480 +/- ##
==========================================
+ Coverage 74.70% 74.86% +0.15%
==========================================
Files 60 60
Lines 6061 6102 +41
==========================================
+ Hits 4528 4568 +40
- Misses 1533 1534 +1
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samster25
approved these changes
Oct 10, 2023
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Updates the number of cores available before/after every batch dispatch
This should allow us to take advantage of autoscaling of the Ray cluster better as we will schedule larger batches of tasks + more total inflight tasks as the cluster autoscales.