Compiler Synchronization Logic for Parallel Data Flow Pipelines
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Solution Overview
Problem
Current data processing methods in machine learning and deep learning environments face inefficiencies due to low compilation performance and data processing efficiency, particularly in asynchronous and parallel operation pipelines where synchronization is crucial but challenging to manage effectively.
Innovation Solution
A data flow processing method that involves obtaining dependency relationships and execution sequences between processing units, generating synchronization logic, and inserting it into operation pipelines to ensure correct and efficient data processing, using techniques like barrier instructions and event synchronization to manage concurrency and eliminate transfer dependencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If asynchronous and parallel operation pipelines are used to improve parallel throughput capability, then data processing efficiency is improved, but incorrect calculation results are generated due to lack of time sequence dependency
Solution Approach 1:
A synchronization instruction is introduced as an intermediary element between operation pipelines. This synchronization instruction acts as a mediator that coordinates the timing and sequence of operations across different pipelines, ensuring that data is read and written in the correct time sequence while maintaining parallel processing capabilities. The synchronization instruction resolves the conflict between asynchronous parallel execution and time sequence dependency requirements.
2Reliability
If pipeline synchronization instruction is provided to manage asynchronous and parallel operation pipeline, then calculation result correctness is improved, but compilation performance and data processing efficiency remain low
Solution Approach 1:
The system automatically generates and inserts synchronization instructions without requiring manual intervention or complex user configuration. The compiler autonomously analyzes data flow dependencies, determines where synchronization is needed, and inserts appropriate synchronization instructions into the operation pipelines. This self-service approach eliminates the need for users to manually manage synchronization complexity while maintaining correct time sequence execution.
3Reliability
If manual synchronization management is used to ensure time sequence consistency, then calculation result correctness is improved, but programming complexity increases
Solution Approach 1:
The compiler automatically performs dependency analysis and generates synchronization instructions without requiring user intervention. Users simply need to write high-level data flow descriptions, and the compiler handles the complex synchronization logic automatically. This eliminates the need for users to manually manage synchronization complexity while maintaining correct time sequence execution.
Solution Approach 2:
The system changes the abstraction level of programming by transforming detailed synchronization control parameters into high-level data flow descriptions. Instead of requiring users to specify timing and sequence parameters manually, the system accepts high-level semantic descriptions and automatically translates them into correct synchronization implementations, reducing programming complexity while maintaining reliability.
Data Source
AI summary
The present disclosure relates to data flow processing methods and devices. One example method includes obtaining a dependency relationship and an execution sequence of operating a data flow by a plurality of processing units, generating synchronization logic based on the dependency relationship and the execution sequence, and inserting the synchronization logic into an operation pipeline of each of the plurality of processing unit to generate executable code.