Infrastructure for GPU devices #162
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aleksandr-mokrov
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Aug 28, 2021
igor-davidyuk
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dmitryagapov
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Sep 22, 2021
dmitryagapov
suggested changes
Sep 22, 2021
| resp.health_check_period.seconds = health_check_period | ||
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| return resp | ||
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| async def GetEnvoys(self, request, context): # NOQA:N802 | ||
| """Get a status information about envoys.""" | ||
| envoy_infos = self.director.get_envoys() | ||
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| return director_pb2.GetEnvoysResponse(envoy_infos=envoy_infos) | ||
| response = [] |
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It's not a response. It's envoy_infos or envoy_info_messages. Response is director_pb2.GetEnvoysResponse
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changed to envoy_statuses
openfl/interface/envoy.py
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| root_certificate, private_key, certificate): | ||
| """Start the Envoy.""" | ||
| logger.info('🧿 Starting the Envoy.') | ||
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| shard_descriptor = shard_descriptor_from_config(shard_config_path) | ||
| # Reed the Envoy config |
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And it looks like we can add a method read_envoy_config
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I would argue that we need a separate builder component, that would assemble our services and manage their plugins. For now, I would just leave the config reading logic in the cl interface
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ok to test |
itrushkin
reviewed
Sep 28, 2021
added a message to director.proto with gpu info
Co-authored-by: Ilya Trushkin <ilya.trushkin@intel.com>
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ok to test |
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An attempt to allow assigning GPU devices through OpenFL.
The PR introduces an optional 'device monitor' plugin for Envoy and two information flows:
The Director_Pytorch_Kvasir_UNET example is modified to utilize the new infrastructure.
There are 2 envoys, one that utilizes GPUs and one that does not.
Device assignment for an experiment is done through 'device assignment policy' which may be 'cuda preferred' or 'cpu only'