Refactor workload tracking and message generation #72
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solidpixel
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…amic dispatch. Switch to a variant based instruction, rather than using dynamic dispatch + enum as this is more type safe. Remove the duplicated object in command_buffer.
No need to carry around the extra state uncessarily. This also makes clear from the type, rather than from the magic tagID value that the renderpass is a continuation. This makes refactoring to separate out the the workload as a data object from operations on that data safer since they will not need to propogate this magic knowledge forward.
…kloadMetadataEmitterVisitor. This centralizes the construction of metadata payloads into one place, decoupling the metadata format from the layer driver handler functions.
This is now moved into the centralized serializer for the layer driver in workload_metadata_builder and fully decouples the state tracker from the timeline layer's data serialization
of JSON. * Uses "protobuf" C++ header only library for encoding the messages as they are simple and we want to avoid a larger dependency on libprotobuf and the necessary build-time changes to build or require protoc for host and libprotobuf for target.
into JSON objects that the viewer expects
The protocol supports multiple devices, as does the API but historically we just assumed a single device. Modify the state tracking in service_gpu_timeline.py so that we collect frames and submits on a per-device basis.
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Renamed workload_metadata_builder to timeline_protobuf_encoder to better reflect what it does
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solidpixel
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This reworks some of the state tracking, decoupling it from the timeline-layer specific data serialization.
This shouldn't change the serialized JSON data, but it is preparation work for moving to protobufs.