[NV TRT RTX EP] Cumulative TRT RTX EP merge #25656
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TRT RTX workspace allocation using ORT Arena allocator See merge request winai/onnxruntime!4
Reduce CPU overhead of TRT-RTX EP's compute function See merge request winai/onnxruntime!20
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/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline,Windows x64 QNN CI Pipeline |
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gedoensmax
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Aug 5, 2025
chilo-ms
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Aug 6, 2025
adrianlizarraga
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Aug 8, 2025
This currently holds 2 major improvements: - dynamic shape models should have much lower memory usage and in addition to that the management is move towards ORT allocators - the overhead for shape binding and address updates is reduce per inference --------- Co-authored-by: Gaurav Garg <[email protected]>
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…5, 25652 (#25701) ### Description Cherry-pick the following PRs into the `rel-1.23.0` branch: - #25391 - #25611 - #25656 - #25346 - #25374 - #25664 - #25675 - #25652 ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. --> --------- Co-authored-by: Yulong Wang <[email protected]> Co-authored-by: Ishwar Raut <[email protected]> Co-authored-by: Maximilian Müller <[email protected]> Co-authored-by: Gaurav Garg <[email protected]> Co-authored-by: Scott McKay <[email protected]> Co-authored-by: Chi Lo <[email protected]> Co-authored-by: Abhishek Jindal <[email protected]> Co-authored-by: Dmitri Smirnov <[email protected]>
sanketkaleoss
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Aug 11, 2025
This currently holds 2 major improvements: - dynamic shape models should have much lower memory usage and in addition to that the management is move towards ORT allocators - the overhead for shape binding and address updates is reduce per inference --------- Co-authored-by: Gaurav Garg <[email protected]>
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This currently holds 2 major improvements: