针对你提出的“cuda lazy loading is not enabled”问题,我将按照提供的提示逐一解答,并尽量包含相关代码片段(如果适用)。 1. 确认CUDA是否已正确安装 首先,确保CUDA已经正确安装在你的系统上。你可以通过运行以下命令来检查CUDA是否安装以及安装的版本: bash nvcc --version 或者,如果你使用的是Linux系统,也可以检...
(base) root@VM-24-95-ubuntu:/workspace# python -c "import tensorrt;print(tensorrt.__version__);assert tensorrt.Builder(tensorrt.Logger())" 10.9.0.34 [03/11/2025-01:49:50] [TRT] [W] CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage and speed ...
Lazy loading is not enabled in the CUDA stack by default in this release. To evaluate it for your application, run with the environment variable CUDA_MODULE_LOADING=LAZY set. Compatibility CUDA minor version compatibility is a feature introduced in 11.x that gives you the flexibility to dynamica...
All libraries used with lazy loading must be built with 11.7+ to be eligible for lazy loading. Lazy loading is not enabled in the CUDA stack by default in this release. To evaluate it for your application, run with the environment variableCUDA_MODULE_LOADING=LAZYset. Improved MPS signal hand...
▶ Add support for debugging applications using CUDA Lazy Loading. ▶ Debugger is now enabled on Windows Subsystem for Linux (WSL). ▶ Add basic type support for printing FP8 values (E4M3 and E5M2). Notes ▶ By default, cuda-gdb will use the new Unified Debugger (UD) backend. ...
‣ Add support for debugging applications using CUDA Lazy Loading. ‣ Debugger is now enabled on Windows Subsystem for Linux (WSL). ‣ Add basic type support for printing FP8 values (E4M3 and E5M2). Notes ‣ By default, cuda-gdb will use the new Unified Debugger (UD) backend. ...
Python platform: Linux-5.15.0-113-generic-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 12.4.131 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4090 GPU 1: NVIDIA GeForce RTX 4090 ...
Python platform: Linux-6.8.0-52-generic-x86_64-with-glibc2.39 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A100 80GB PCIe GPU 1: NVIDIA A100 80GB PCIe ...
In addition, runtime compilation via NVRTC available with CUDA 7.0 is incorporated into the presented framework that not only helps unroll innermost loop to yield upto 2 to 3-fold speedup than static compilation but also enables dynamic loading and switching of kernels depending on the query model...
HMM is also not yet fully optimized and may perform slower than programs usingcudaMalloc(),cudaMallocManaged(), or other existing CUDA memory management APIs. Lazy loading A feature NVIDIA initially introduced in CUDA 11.7 as an opt-in, lazy loading is now enabled by default on Linux w...