Jetson TX2 初体验_jetsontx2板载供电

0. 简介

Jetson TX2【1】是基于 NVIDIA Pascal™ 架构的 AI 单模块超级计算机，性能强大（1 TFLOPS），外形小巧，节能高效（7.5W），非常适合机器人、无人机、智能摄像机和便携医疗设备等智能终端设备。
Jatson TX2 与 TX1 相比，内存和 eMMC 提高了一倍，CUDA 架构升级为 Pascal，每瓦性能提高一倍，支持 Jetson TX1 模块的所有功能，支持更大、更深、更复杂的深度神经网络。

TX2 内部结构如下：

1. 开箱

过程细节不展开，板卡上电后来张照片：

2. 刷机

TX2 出厂时，已经自带了 Ubuntu 16.04 系统，可以直接启动。但一般我们会选择刷机，目的是更新到最新的 JetPack L4T，并自动安装最新的驱动、CUDA Toolkit、cuDNN、TensorRT。

刷机注意以下几点：

• Host 需要安装 Ubuntu 14.04，至少预留 15 GB 硬盘空间，不要用 root 用户运行 JetPack-${VERSION}.run，我用的是 JetPack-L4T-3.1-linux-x64.run
• TX2 需要进入 Recovery Mode，参考随卡自带的说明书步骤
• 刷机时间大概需要 1~2 小时，会格式化 eMMC，主要备份数据

3. 运行视频目标检测 Demo

刷机成功后，重启 TX2，连接键盘鼠标显示器，就可以跑 Demo 了。

nvidia@tegra-ubuntu:~/tegra_multimedia_api/samples/backend$ ./backend 1 ../../data/Video/sample_outdoor_car_1080p_10fps.h264 H264 --trt-deployfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.prototxt --trt-modelfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.caffemodel --trt-forcefp32 0 --trt-proc-interval 1 -fps 10

视频截图如下：

4. 运行 TensorRT Benchmark

TensorRT 【3】是 Nvidia GPU 上的深度学习 inference 优化库，可以将训练好的模型通过优化器生成 inference 引擎

将 TX2 设置为 MAXP （最高性能）模式，运行 TensorRT 加速的 GoogLeNet、VGG16 得到处理性能如下：

5. TX2 不支持的 feature

• 不支持 int8
• 待发现

参考文献

【1】嵌入式系统开发者套件和模块 | NVIDIA Jetson | NVIDIA
【2】Download and Install JetPack L4T
【3】TensorRT

附录

deviceQuery

nvidia@tegra-ubuntu:~/work/TensorRT/tmp/usr/src/tensorrt$ cd /usr/local/cuda/samples/1_Utilities/deviceQuery
nvidia@tegra-ubuntu:/usr/local/cuda/samples/1_Utilities/deviceQuery$ ls
deviceQuery  deviceQuery.cpp  deviceQuery.o  Makefile  NsightEclipse.xml  readme.txt
nvidia@tegra-ubuntu:/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery
./deviceQuery Starting...
 
 CUDA Device Query (Runtime API) version (CUDART static linking)
 
Detected 1 CUDA Capable device(s)
 
Device 0: "NVIDIA Tegra X2"
  CUDA Driver Version / Runtime Version          8.0 / 8.0
  CUDA Capability Major/Minor version number:    6.2
  Total amount of global memory:                 7851 MBytes (8232062976 bytes)
  ( 2) Multiprocessors, (128) CUDA Cores/MP:     256 CUDA Cores
  GPU Max Clock rate:                            1301 MHz (1.30 GHz)
  Memory Clock rate:                             1600 Mhz
  Memory Bus Width:                              128-bit
  L2 Cache Size:                                 524288 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 32768
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  2048
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            Yes
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  Device supports Unified Addressing (UVA):      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 0 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
 
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = NVIDIA Tegra X2
Result = PASS

内存带宽测试

nvidia@tegra-ubuntu:/usr/local/cuda/samples/1_Utilities/bandwidthTest$ ./bandwidthTest
[CUDA Bandwidth Test] - Starting...
Running on...
 
 Device 0: NVIDIA Tegra X2
 Quick Mode
 
 Host to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)    Bandwidth(MB/s)
   33554432         20215.8
 
 Device to Host Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)    Bandwidth(MB/s)
   33554432         20182.2
 
 Device to Device Bandwidth, 1 Device(s)
 PINNED Memory Transfers
   Transfer Size (Bytes)    Bandwidth(MB/s)
   33554432         35742.8
 
Result = PASS
 
NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.

GEMM 测试

nvidia@tegra-ubuntu:/usr/local/cuda/samples/7_CUDALibraries/batchCUBLAS$ ./batchCUBLAS -m1024 -n1024 -k1024
batchCUBLAS Starting...
 
GPU Device 0: "NVIDIA Tegra X2" with compute capability 6.2
 
 
 ==== Running single kernels ====
 
Testing sgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0xbf800000, -1) beta= (0x40000000, 2)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 0.00372291 sec  GFLOPS=576.83
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0x0000000000000000, 0) beta= (0x0000000000000000, 0)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 0.10940003 sec  GFLOPS=19.6296
@@@@ dgemm test OK
 
 ==== Running N=10 without streams ====
 
Testing sgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0xbf800000, -1) beta= (0x00000000, 0)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 0.03462315 sec  GFLOPS=620.245
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0xbff0000000000000, -1) beta= (0x0000000000000000, 0)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 1.09212208 sec  GFLOPS=19.6634
@@@@ dgemm test OK
 
 ==== Running N=10 with streams ====
 
Testing sgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0x40000000, 2) beta= (0x40000000, 2)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 0.03504515 sec  GFLOPS=612.776
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0xbff0000000000000, -1) beta= (0x0000000000000000, 0)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 1.09177494 sec  GFLOPS=19.6697
@@@@ dgemm test OK
 
 ==== Running N=10 batched ====
 
Testing sgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0x3f800000, 1) beta= (0xbf800000, -1)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 0.03766394 sec  GFLOPS=570.17
@@@@ sgemm test OK
Testing dgemm
#### args: ta=0 tb=0 m=1024 n=1024 k=1024  alpha = (0xbff0000000000000, -1) beta= (0x4000000000000000, 2)
#### args: lda=1024 ldb=1024 ldc=1024
^^^^ elapsed = 1.09389901 sec  GFLOPS=19.6315
@@@@ dgemm test OK
 
Test Summary
0 error(s)