zoukankan      html  css  js  c++  java
  • Jetson Nano Vs. Intel Neural Compute Stick 2

    https://devblogs.nvidia.com/jetson-nano-ai-computing/

    Table 2 provides full results, including the performance of other platforms like the Raspberry Pi 3, Intel Neural Compute Stick 2, and Google Edge TPU Coral Dev Board:

    Table 2. Inference performance results from Jetson Nano, Raspberry Pi 3, Intel Neural Compute Stick 2, and Google Edge TPU Coral Dev Board

    Model

    Application

    Framework

    NVIDIA Jetson Nano

    Raspberry Pi 3

    Raspberry Pi 3 + Intel Neural Compute Stick 2

    Google Edge TPU Dev Board

    ResNet-50
    (224×224)

    Classification

    TensorFlow

    36 FPS

    1.4 FPS

    16 FPS

    DNR

    MobileNet-v2
    (300×300)

    Classification

    TensorFlow

    64 FPS

    2.5 FPS

    30 FPS

    130 FPS

    SSD ResNet-18 (960×544)

    Object Detection

    TensorFlow

    5 FPS

    DNR

    DNR

    DNR

    SSD ResNet-18 (480×272)

    Object Detection

    TensorFlow

    16 FPS

    DNR

    DNR

    DNR

    SSD ResNet-18 (300×300)

    Object Detection

    TensorFlow

    18 FPS

    DNR

    DNR

    DNR

    SSD Mobilenet-V2 (960×544)

    Object
    Detection

    TensorFlow

    8 FPS

    DNR

    1.8 FPS

    DNR

    SSD Mobilenet-V2 (480×272)

    Object Detection

    TensorFlow

    27 FPS

    DNR

    7 FPS

    DNR

    SSD Mobilenet-V2

    (300×300)

    Object Detection

    TensorFlow

    39 FPS

    1 FPS

    11 FPS

    48 FPS

    Inception V4

    (299×299)

    Classification

    PyTorch

    11 FPS

    DNR

    DNR

    9 FPS

    Tiny YOLO V3

    (416×416)

    Object Detection

    Darknet

    25 FPS

    0.5 FPS

    DNR

    DNR

    OpenPose

    (256×256)

    Pose Estimation

    Caffe

    14 FPS

    DNR

    5 FPS

    DNR

    VGG-19 (224×224)

    Classification

    MXNet

    10 FPS

    0.5 FPS

    5 FPS

    DNR

    Super Resolution (481×321)

    Image Processing

    PyTorch

    15 FPS

    DNR

    0.6 FPS

    DNR

    Unet

    (1x512x512)

    Segmentation

    Caffe

    18 FPS

    DNR

    5 FPS

    DNR

  • 相关阅读:
    01、启动优先和安全设置
    5、bam格式转为bigwig格式
    1、蛋白质二级结构预测方法
    12、IGV-Integrative Genomics Viewer
    docker-compose 工具安装
    docker-compose.yml 语法说明
    docker 镜像和容器的批量清理
    rancher 笔记 之 rancher应用中心
    golang 学习笔记
    docker registry 搭建
  • 原文地址:https://www.cnblogs.com/cloudrivers/p/11912121.html
Copyright © 2011-2022 走看看