Make Long-Running NVIDIA TensorRT Engine Builds Observable and Cancelable in Python or C++
Quick Answer
NVIDIA's TensorRT now allows observable and cancelable engine builds in Python and C++ via the IProgressMonitor API, enhancing user experience during long builds.
Quick Take
This tutorial provides a step-by-step implementation guide, enabling developers to track progress and abort builds effectively.
Key Points
- IProgressMonitor API allows tracking and canceling long TensorRT engine builds.
- Developers can implement this feature in both Python and C++.
- Cancellation can be triggered via Ctrl-C or programmatic signals.
- The tutorial includes sample code for practical implementation.
- Thread safety is crucial as multiple threads may access the monitor.
DeepSignal Analysis
What happened
NVIDIA's TensorRT has introduced the IProgressMonitor API, enabling observable and cancelable engine builds in both Python and C++. This enhancement addresses the issue of long build times, allowing developers to monitor progress and abort builds if necessary. The tutorial provides a detailed implementation guide for integrating this feature into existing workflows.
Key evidence
- TensorRT engine builds can take from seconds to many minutes, leading to potential inefficiencies during long-running workflows.
- The IProgressMonitor API has been available in NvInfer.h for several releases, allowing developers to track build progress.
- The tutorial includes code examples for implementing IProgressMonitor in both Python and C++, demonstrating its usage with sample models like ResNet-50 and MNIST.
Why it matters
The ability to monitor and cancel long-running builds is significant for developers using TensorRT, as it can prevent wasted GPU resources and improve overall workflow efficiency. By providing real-time feedback during the build process, developers can make informed decisions about whether to continue or abort a build. This feature is particularly relevant for large models and complex tasks that can lead to extended build times.
Source Excerpt
A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can…
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