Neural Network Graph Orchestrator for Barrier Dependency Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current DNN execution techniques face challenges with high computing demands, significant memory bandwidth requirements, and runtime overhead due to limited hardware resources, especially in resource-constrained devices, and existing barrier management methods are inadequate for large networks, leading to inefficiencies and hardware hazards.
Innovation Solution
A graph orchestrator block is introduced to manage producer and consumer dependencies by tracking barrier status, allowing for a higher number of barriers and reducing runtime intervention, thus improving DNN execution efficiency and avoiding hardware/software race conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional barrier management methods are used in resource-constrained devices, then hardware resources are limited, but runtime overhead increases and hardware hazards occur
Solution Approach 1:
The system segments barrier management into two distinct parts: software-managed barrier insertion (producer side) and hardware-managed barrier tracking (consumer side). This segmentation allows the software to set barriers without runtime intervention, while the hardware autonomously tracks barrier status, eliminating the need for continuous software polling and reducing runtime overhead while maintaining execution correctness.
Solution Approach 2:
A dedicated hardware barrier tracking unit is introduced as an intermediary between the software runtime and the compute elements. This intermediary autonomously manages barrier status tracking, allowing producers to insert barriers via simple software instructions without further intervention, while consumers can safely wait for barrier completion. This mediator eliminates race conditions and reduces software runtime overhead.
2Adaptability or versatility
If the number of barriers is increased to manage producer-consumer dependencies, then dependency management improves, but hardware complexity and resource requirements increase
Solution Approach 1:
The hardware barrier tracking unit operates autonomously without requiring software intervention for each barrier operation. Producers simply insert barriers via software instructions, and the hardware automatically tracks their status, manages consumer waiting, and signals completion. This self-service mechanism allows the system to handle a large number of barriers without proportionally increasing software complexity or runtime overhead.
3Reliability
If software intervention is used to manage barriers, then barrier status can be tracked, but runtime overhead and execution efficiency decrease
Solution Approach 1:
The system replaces the mechanical approach of software polling and intervention with an event-driven hardware mechanism. The hardware barrier tracking unit automatically detects when producers have completed their work and when consumers are ready, signaling barrier completion without software intervention. This substitution of hardware autonomy for software control eliminates the performance penalty of runtime intervention while maintaining reliable barrier status tracking.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A barrier may be inserted into a graph representing workloads in an execution of a neural network and placed between a producing workload performed by a producer and a consuming workload performed by a consumer. The consuming workload is to be performed using data generated from the producing workload. A graph orchestrator may modify status information of the barrier in response to receiving a message from the producer. The status information indicates whether one or more producing workloads associated with the barrier are complete. The message indicates that the producing workload is complete. The graph orchestrator may determine whether the one or more producing workloads are complete based on the modified status information. In response to determining that the one or more producing workloads are complete, the graph orchestrator may provide a barrier lift message to the consumer. The barrier lift message causing the consumer to start the consuming workload.