Massively parallel CPU processes 256 shades of gray

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The 1980s were a heyday for strange computer architectures; instead of the von Neumann architecture you’d find in one of today’s desktop computers or the Harvard architecture of a microcontroller, a lot of companies experimented with strange parallel designs. While not used much today, at the time these were some of the most powerful computers of their day and were used as the main research tools of the AI renaissance of the 1980s.

Over at the Norwegian University of Science and Technology a huge group of students (13 members!) designed a modern take on the massively parallel computer. It’s called 256 Shades of Gray, and it processes 320×240 pixel 8-bit grayscale graphics like no microcontroller could.

The idea for the project was to create an array-based parallel image processor with an architecture similar to the Goodyear MPP formerly used by NASA or the Connection Machine found in the control room of Jurassic Park. Unlike these earlier computers, the team implemented their array processor in an FPGA, giving rise to their Lena processor this processor is in turn controlled by a 32-bit AVR microcontroller with a custom-build VGA output.

The entire machine can process 10 frames per second of 320×240 resolution grayscale video. There’s a presentation video available (in Norwegian), but the highlight might be their demo of The Game of Life rendered in real-time on their computer. An awesome build, and a very cool experience for all the members of the class.

Building a spectrum analyzer with parallel processing

fft

It’s the end of the semester for [Bruce Land]‘s microcontroller design class at Cornell, and the projects coming off the workbench this semester look as awesome as any before. For their final project, [Alexander Wang] and [Bill Jo] designed an audio frequency spectrum analyzer using two microcontrollers in a parallel setup.

This spectrum analyzer takes an audio signal from an iPod, phone, or CD player through a 3.5 mm jack and displays the level for dozens of frequency bands much like an audio visualizer in iTunes or a nice car stereo display. To display these frequency bands, the spectrum analyzer first needs to perform a Fast Fourier Transform on the incoming audio signal. While FFT is extremely fast, the calculations are rather hardware intensive; calculating the frequencies and displaying them on a TV would be a bit much even for the ATMega1284 used in the project.

To graph the audio signal on their small display, [Alexander] and [Bill] broke the build up into two parts – one to do the math on the audio, and another to generate the NTSC video signal for the display.

As seen in the video after the break, the spectrum analyzer works wonderfully, and even though it only functions up to 4kHz, it’s more than enough to see what’s going on in most music.

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