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TensorRT-RTX 1.2 Release

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@tp5uiuc tp5uiuc released this 12 Nov 21:36
· 5 commits to main since this release
v1.2.0.44
b138f96

This OSS release supports TensorRT-RTX 1.2, and contains sample code to showcase its capabilities and recommended usage.

Details are available in the release notes. Notable features in this release include:

  • Built-in CUDA Graphs with automatic dynamic shape support, which can be enabled with a one-line change to existing workflows, gives users the potential to further accelerate their inference workflows by reducing the GPU kernel launch overhead at runtime.
  • Users can set a new kREQUIRE_USER_ALLOCATION builder flag to require that engines use application-provided memory where possible (in contrast to runtime-allocated memory). This is required when using CUDA stream capture. However, stream capture is not possible for all models, especially when using data-dependent dynamic shapes or certain on-device control flows. A new IExecutionContext::isStreamCapturable() API allows querying whether stream capture is possible in the current execution context or not.
  • The DLL libraries have moved from the lib subdirectory to the bin subdirectory.

This release includes support for the CUDA 13.0 Toolkit, available on both Linux and Windows. Users should download the CUDA 12.9 and CUDA 13.0 TensorRT-RTX build separately as needed.

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