Computational Graph Loop State Management
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Solution Overview
Problem
Existing systems face challenges in efficiently processing computational graphs representing neural networks, particularly in handling control flow statements like loops, which require distributed execution across multiple devices.
Innovation Solution
The system processes computational graphs by identifying control flow statements, generating structures to represent the current state of recursion or iteration, and modifying the graph allocation to enable each device to independently determine and manage loop states, thereby facilitating efficient distributed execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If control flow statements like loops are processed in a distributed manner across multiple devices, then the overall processing time is reduced and productivity is improved, but the device complexity and difficulty of managing loop states increase
Solution Approach 1:
The patent introduces intermediary nodes in the computational graph that represent loop state information. These intermediary nodes act as mediators between different devices, allowing them to coordinate loop execution without each device needing to independently track the entire loop state. The intermediary nodes capture and transmit loop state information across device boundaries, simplifying the management complexity while enabling distributed execution.
Solution Approach 2:
The patent segments the computational graph into subgraphs that can be distributed across multiple devices. By dividing the graph and identifying which nodes represent loop state, the system allows each device to process its assigned subgraph independently while maintaining coordination through the segmented loop state nodes. This segmentation enables parallel processing without requiring centralized loop state management.
2Productivity
If each device independently determines the current state of recursion or iteration in loops, then distributed execution efficiency is improved, but the complexity of ensuring correct collective execution increases
Solution Approach 1:
The patent implements feedback mechanisms where loop state nodes receive inputs from operations that modify loop state (such as iteration counters or recursion depth trackers) and propagate this state information to other parts of the computational graph. This feedback ensures that each device can independently determine loop state while maintaining consistency with the overall execution, as the state is explicitly carried through the graph rather than requiring implicit coordination.
3Adaptability or versatility
If computational graphs with loops are distributed across multiple devices, then the handling of complex control flow statements is improved, but the overall system complexity increases
Solution Approach 1:
The patent creates a universal representation of loop state that can be applied to any control flow statement distributed across devices. By defining standard node types and edge relationships that represent loop state generically, the system can handle various types of loops (for-loops, while-loops, recursive calls) using the same framework. This universal approach increases adaptability while avoiding the need for device-specific or loop-type-specific complexity.
Data Source
AI summary
Systems and methods for processing loops in computational graphs representing machine learning models are disclosed. An example method begins with obtaining data representing a computational graph. Data identifying an allocation of the computational graph across devices is obtained. Additionally, one or more nodes in the computational graph that represent a respective control flow statement are identified. For each identified node, a structure of nodes and edges that represents an operation that provides a current state of recursion or iteration in the respective control flow statement is generated. This structure is inserted into the computational graph and the allocation of nodes to devices is modified to assign the structure to a device.