Implement parallel model preloading #211
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@AlexCheema
Implement Parallel Model Preloading
Description
This PR introduces parallel model preloading to significantly reduce startup times for large models distributed across multiple nodes. By leveraging asyncio, we now preload model shards into memory concurrently, followed by a sequential initialization step.
Changes
preload_model
method to theInferenceEngine
abstract classpreload_model
inMLXDynamicShardInferenceEngine
ensure_shard
method to work with preloaded modelsmain.py
to use parallel preloadingImplementation Details
InferenceEngine
now has an abstractpreload_model
methodMLXDynamicShardInferenceEngine.preload_model
loads model config and weights without full initializationensure_shard
completes initialization using preloaded dataasyncio.gather
for parallel preloadingPerformance Improvements
How to Test
Future Work
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