Profiling AlexNet on Raspberry Pi and HiKey 960 with the Arm Compute LibraryOverview Set up your Raspberry Pi NFS on Pi Build the Arm Compute Library on Pi Run the graph_alexnet application on Pi Start Streamline gatord on Pi Add Streamline annotations and rebuild on Pi Build the Arm Compute Library on HiKey 960 Profile with Streamline on HiKey 960 Next steps
Set up your Raspberry Pi
- Raspberry Pi 2 or 3 with internet access.
- A blank Micro SD card. We recommend an 8 GB (minimum 6GB) Class 6 or Class 10 microSDHC card for installing the Raspberry Pi OS and storing the CNN model.
- Arm DS-5 installed on a host PC running Windows or Linux.
- Router and ethernet cable. This is to connect to the Raspberry Pi from a host PC using SSH.
Set up Ubuntu MATE
Set up your Pi with Ubuntu MATE and prepare it for SSH access from a separate host machine. The general steps for this are:
- Download the Ubuntu MATE 16.04.02 image file.
- Uncompress it using unxz.
- Write the image to the MicroSD card, we use dd on Linux but there are many ways.
- Insert the MicroSD card in a Raspberry Pi 3 and start it up.
Once the new system starts up, go through the configuration steps and connect to the network using a wired or wireless connection from your host machine.
Next, enable SSH by entering this on the command line:
$ sudo raspi-config
Then select Interfacing Options:
And then select SSH:
With SSH enabled, use the
ifconfig command to see the IP address of the Pi:
$ ifconfig wlan0
wlan0 Link encap:Ethernet HWaddr b8:27:eb:22:ab:26
inet addr:192.168.0.121 Bcast:192.168.0.255 Mask:255.255.255.0
And then check that you can SSH to it from your host machine.
To save time, you can setup SSH with no password. For example:
$ ssh-copy-id 192.168.0.121