Tag Archives: Intel

BeMicro SDK with Quartus 18.1 Lite

With a new laptop there are tons of software to install for getting back my development environment in the old machine. One of these is the Quartus Prime from Intel for toying with an old BeMicroSDK. Quartus is the IDE for Altera FPGA. BeMciroSDK is a development kit from Altera well before the fabless company acquired by Intel in 2015.  It sports an EP4CE22 Cyclone IV with 22K LE.
quartus18-4

The latest version of Quartus Pro is 19.1, but it no longer supports the Cyclone IV family and have to settle for the Standard  or Lite edition. The software download is available here.

The installation is smooth on Windows 10 Pro. After the installation, I plugged in the FPGA stick into the USB port, and no lights turn on. Started the Prime Programmer to check and it does not detect any device. Then I opened the device manager and saw that USB Blaster is not installed.
quartus18-2

Simply click Update driver button and browse to the installation of Quartus to complete the driver installation (Online driver searching does not find anything useful).quartus18-1

Finally the FPGA programming is successful on the new laptop.quartus18-3

Deep Learning with the Movidius Neural Compute Stick

IMAG1428

Deep Learning is a breakthrough in Artificial Intelligence. With its root from neural network, modern computing hardware advancement enabled new possibilities by sophisticated integrated circuits technology.

A branch of this exciting area in AI is machine learning. The leading development frameworks include TensorFlow and Caffe. Pattern recognition is a practical application of machine learning where photos or videos are analysed by machine to produce usable output as if a human did the analysis. GPU has been a favorite choice for its specialized architecture, delivering its supreme processing power not only in graphics processing but also popular among the neural network community. Covered in a previous installment is how to deploy an Amazon Web Services GPU instance to analyse real time traffic camera images using Caffe.

To bring this kind of machine learning power to IoT, Intel shrank and packaged a specialized Vision Processing Unit into the form factor of a USB thumb drive in the Movidius™ Neural Compute Stick.
IMAG1432

It sports an ultra low power Vision Processing Unit (VPU) inside an aluminium casing, weights only 30g (without the cap). Supported on the Raspberry Pi 3 model B makes it a very attractive add-on for development projects involving AI application on this platform.IMAG1435

In the form factor of an USB thumb drive, the specialized VPU geared for machine learning in the Movidius performs as an AI accelerator for the host computer.IMAG1439

To put this neural compute stick into action, an SDK available from git download provided by Movidius is required. Although this SDK runs on Ubuntu, Windows users with VirtualBox can easily install the SDK with an Ubuntu 16.04 VM.

While the SDK comes with many examples, and the setup is a walk in the park, running these examples is not so straight forward, especially on a VM. There are points to note from making this stick available in the VM including USB 3 and filters setting in VirtualBox, to the actual execution of the provided sample scripts. Some examples required two sticks to run. Developers should be comfortable with Python, unix make / git commands, as well as installing plugins in Ubuntu.
mod1

The results from the examples in the SDK alone are quite convincing, considering the form factor of the stick and its electrical power consumption. This neural computing stick “kept its cool” literally throughout the test drive, unlike the FPGA stick I occasionally use for bitcoins mining which turn really hot.