Neural Network Breakpoints for Asynchronous Engine Debugging

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Solution Overview

Problem

Debugging neural networks executed by multiple asynchronous execution engines is challenging due to the difficulty in synchronizing the halt of engines at a target layer, as they receive different sets of instructions and may execute them at different times.

Innovation Solution

The technique involves a compiler that generates offset values for each layer of the neural network, allowing a debugger to set breakpoints at adjusted offsets for each execution engine, ensuring simultaneous halt at the target layer.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple asynchronous execution engines are used to execute neural network instructions, then processing speed and productivity are improved, but synchronization difficulty and debugging complexity increase

Engineering Contradiction:

Improveneural network processing speedVSAvoidsynchronization complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The instruction stream is divided into multiple separate instruction streams, with each stream being assigned to a different execution engine. This segmentation allows independent execution while maintaining traceability through breakpoint offsets, resolving the contradiction between parallel processing capability and synchronization complexity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Breakpoint offsets serve as intermediary markers that mediate between the high-level debugging interface and the low-level asynchronous execution engines. These offsets enable synchronized halting across multiple engines without requiring direct coordination mechanisms, thus improving productivity while managing complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Difficulty of detecting and measuring

If breakpoints are set in asynchronous execution engines, then debugging capability is improved, but halting synchronization accuracy deteriorates

Engineering Contradiction:

Improvedebugging capabilityVSAvoidhalting synchronization accuracy

Core Design Contradiction:

Difficulty of detecting and measuringVSMeasurement precision

Solution Approach 1:

Breakpoint offsets are pre-calculated and stored during the compilation phase before execution begins. This preliminary action ensures that when debugging is needed, the exact offset values are already available, enabling precise halting synchronization without requiring real-time measurement or calculation during execution

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces complex runtime synchronization mechanisms with a simpler offset-based addressing system. Instead of using intricate timing coordination or signal synchronization, the system uses predetermined offset values to locate and halt execution at breakpoints across multiple asynchronous engines, improving debugging capability while maintaining synchronization accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If instruction sets are distributed to multiple execution engines, then processing throughput is improved, but breakpoint location precision deteriorates

Engineering Contradiction:

Improveprocessing throughputVSAvoidbreakpoint location precision

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

Each execution engine receives a customized instruction stream with breakpoints marked by locally-adjusted offsets. This local quality approach ensures that each engine has precise breakpoint information tailored to its specific instruction set, maintaining breakpoint location precision while enabling distributed high-throughput execution

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent introduces an additional dimension of precision by using offset values that account for the specific positioning of instructions within each engine's instruction stream. This dimensional extension allows accurate breakpoint localization even though instructions are distributed across multiple engines, thus maintaining precision while improving throughput

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Data Source

PatentUS12210438B1Breakpoints in neural network accelerator

Publication Date: 2025.01.28 AMAZON TECH INC

AI summary

Techniques are disclosed for setting a breakpoint for debugging a neural network. User input is received by a debugger program executable by a host processor indicating a target layer of a neural network at which to halt execution of the neural network. The neural network includes a first set of instructions to be executed by a first execution engine and a second set of instructions to be executed by a second execution engine. A first halt point is set within the first set of instructions and a second halt point is set within the second set of instructions. It is then determined that operation of the first execution engine and the second execution engine has halted. It is then determined that the first execution engine has reached the first halt point. The second execution engine is then caused to move through instructions until reaching the second halt point.