GPU Stress Testing with Dynamic Random Loads
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Solution Overview
Problem
Conventional GPU testing methods operate at fixed power and duty cycles, failing to accurately simulate real-world conditions and neglect the dynamic performance of GPUs and supporting system components, such as power supply.
Innovation Solution
A method involving a CPU that performs stress testing on a GPU using dynamic loading, with randomly controlled operations and idle periods, simulating real-world scenarios by varying matrix dimensions and operation durations through a random number generator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional fixed power and duty cycle testing is used, then testing simplicity is maintained, but accuracy of simulating real-world conditions deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from fixed, static testing parameters to dynamic, variable testing parameters. The testing system now varies power levels, duty cycles, and load conditions randomly over time to simulate real-world driving scenarios, thereby improving measurement precision while maintaining operational simplicity through automated control.
Solution Approach 2:
The patent implements parameter changes by systematically varying multiple testing parameters including power consumption levels, duty cycles, and operational loads. These parameters are changed dynamically during testing to accurately replicate real-world conditions, resolving the contradiction between testing simplicity and simulation accuracy.
2Stability of the object's composition
If fixed duty cycle testing is used, then testing consistency is maintained, but dynamic performance verification deteriorates
Solution Approach 1:
The patent applies periodic action by implementing cyclic patterns of varying load conditions, power states, and operational modes during testing. These periodic variations include alternating between high and low power states, different duty cycles, and various computational workloads, enabling comprehensive dynamic performance verification while maintaining testing consistency through structured repetition.
3Measurement precision
If comprehensive dynamic testing is implemented, then accuracy of performance assessment is improved, but testing complexity increases
Solution Approach 1:
The patent implements self-service by designing a testing system that automatically generates and executes complex dynamic test sequences without requiring extensive manual configuration. The system autonomously manages parameter variations, monitors performance metrics, and adapts testing conditions based on real-time system responses, thereby improving assessment accuracy while minimizing the increase in testing complexity.
Data Source
AI summary
A data processing system of an autonomous driving vehicle (ADV) may include a central processing unit (CPU) and a graphics processing unit (GPU). The CPU may be configured to monitor a behavior of a graphics processing unit (GPU), operate the GPU to perform a randomly controlled operation using a random number generator, operate the GPU to perform an idle period, and operate the GPU to repeat the randomly controlled operation. The idle period may be performed between each repetition of the randomly controlled operation, and each repetition may utilize the random number generator.