[TRT RTX EP] Memory map the engine buffer#25909
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jywu-msft merged 1 commit intomicrosoft:mainfrom Sep 3, 2025
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@chilo-ms we would like to pick this to 1.23 |
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/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows ARM64 QNN CI Pipeline,Windows x64 QNN CI Pipeline |
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Azure Pipelines successfully started running 4 pipeline(s). |
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/azp run Windows GPU Doc Gen CI Pipeline |
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Azure Pipelines successfully started running 1 pipeline(s). |
jywu-msft
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Sep 3, 2025
tianleiwu
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Sep 4, 2025
### Description Change from fread to mmap to save on system memory. This also accelerated the load time of a ~4GB model in my testing by 1.5X.
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### Description Cherry-pick the following PRs: #25943 #25937 #25917 #25909 #25898 #25897 #25888 #25881 #25830 #25619 #25575 #25572 #25558 #25530 #25474 #25455 #25110 Also two dependent PRs for qMoE cpu: #25877 #25822 --------- Co-authored-by: xiaomsft <136376084+xiaomsft@users.noreply.github.com> Co-authored-by: Xiaoyan Hu <xiaoh@microsoft.com> Co-authored-by: Akshay Sonawane <111780983+apsonawane@users.noreply.github.com> Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com> Co-authored-by: Pradeep Sakhamoori <psakhamoori@microsoft.com> Co-authored-by: mingyue <131847423+mingyueliuh@users.noreply.github.com> Co-authored-by: Maximilian Müller <44298237+gedoensmax@users.noreply.github.com> Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com> Co-authored-by: Dmitri Smirnov <yuslepukhin@users.noreply.github.com> Co-authored-by: Emmanuel <91394589+kobby-kobbs@users.noreply.github.com> Co-authored-by: Emmanuel Assumang <eassumang@microsoft.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: praneshgo <pranesh.iitp@gmail.com> Co-authored-by: Hariharan Seshadri <shariharan91@gmail.com> Co-authored-by: Jing Fang <fajin@microsoft.com> Co-authored-by: Ishwar Raut <iraut@nvidia.com>
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Description
Change from fread to mmap to save on system memory. This also accelerated the load time of a ~4GB model in my testing by 1.5X.