Vector Clocks for Neural Network Dependency Graph Simplification
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Solution Overview
Problem
Integrated circuit devices with multiple execution engines face inefficiencies due to redundant edges in dependency graphs, which complicate synchronization and resource management, leading to suboptimal performance in concurrent computations.
Innovation Solution
The use of vector clocks to identify and remove redundant edges in dependency graphs, optimizing the graph structure through transitive reduction algorithms, thereby simplifying synchronization and resource allocation between execution engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dependency graphs include all possible edges between execution engines, then all data and resource dependencies are captured, but the graph complexity increases and synchronization overhead increases
Solution Approach 1:
The patent extracts and removes redundant edges from the dependency graph while preserving essential synchronization requirements. By identifying edges that are implied through transitive relationships and removing them, the system maintains complete dependency tracking accuracy while significantly reducing graph complexity and synchronization overhead.
Solution Approach 2:
The patent performs preliminary analysis of the dependency graph to identify redundant edges before execution. By pre-computing which edges are necessary and which are redundant, the system prepares an optimized graph structure that eliminates unnecessary synchronization points while ensuring all critical dependencies are preserved.
2Productivity
If vector clocks are used to identify redundant edges, then synchronization overhead is reduced, but computational overhead for maintaining vector clocks increases
Solution Approach 1:
The patent implements self-service mechanisms where each execution engine autonomously maintains its own vector clock and independently determines which edges are redundant. This distributed approach eliminates the need for centralized coordination overhead while still achieving complete dependency optimization, as each engine serves itself in tracking and optimizing its dependencies.
3Productivity
If redundant edges are removed from dependency graphs, then synchronization points are reduced and performance improves, but the risk of missing necessary dependencies increases
Solution Approach 1:
The patent implements feedback mechanisms through vector clock comparisons that continuously verify dependency relationships. By monitoring vector clock values and comparing them across execution engines, the system provides real-time feedback to ensure that removing an edge does not violate any necessary dependency constraints, thus maintaining reliability while improving efficiency.
Data Source
AI summary
Methods for simplifying a dependency graph in a neural network accelerator are provided. Computations and data movements for the neural network accelerator may be described with a flow graph, where graph nodes represent computation or data movement operations and graph edges represent dependencies between operations. A flow graph may contain redundant edges that can be removed while retaining the reachability of each of the nodes in the graph. To identify redundant edges, a compiler may generate vector clocks to track the relationships of operations performed by various execution engines prior to execution of a program reaching a given node or operation. Redundant edges may be identified and removed based on the relative values of the vector clocks to reduce the complexity of the graph.