1. What Is TensorRT TensorRT is a C++ library mainly used for high-performance inference acceleration on NVIDIA GPUs. It provides both a C++ API and a Python API for integration. The mainstream deep learning frameworks TensorRT supports are: Caffe, where TensorRT can read the prototxt format directly TensorFlow, where the

1. Compiling Models with TensorRT-LLM 1.1 Introduction to TensorRT-LLM When using TensorRT, you usually need to convert the model to ONNX format, then convert the ONNX to TensorRT format, and finally run inference in TensorRT or Triton Server. But this conversion process is not simple, and you often run into

1. What Is nvidia-smi nvidia-smi stands for NVIDIA System Management Interface, the interface NVIDIA provides for managing and monitoring GPUs. nvidia-smi calls NVML. NVML stands for NVIDIA Management Library, a library that provides a set of C APIs for NVIDIA GPU monitoring and management. 1.1 Queryable State ECC error counts GPU utilization Active compute processes Clocks and PState Temperature and fan speed Power management Hardware identification 1.

1. Disk Handling 1.1 Inspect Disks Inspect the new disk 1 fdisk -l Disk /dev/nvme1n1: 3.91 TiB, 4294967296000 bytes, 8388608000 sectors 1.2 Build a RAID0 If you have several small disks, a better approach is to build a RAID0 — this gives you not only a larger storage directory but also higher speed.

Using CentOS 7.7 and a Tesla P100 GPU as an example. 1. Preparing the Base Environment Install the lspci command 1 yum install -y pciutils Check whether the GPU supports CUDA 1 2 3 lspci | grep -i nvidia 00:09.0 3D controller: NVIDIA Corporation GP100GL [Tesla P100 PCIe 12GB] (rev a1) List of CUDA-capable GPUs: https://developer.