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Increased Data Intelligence in New Rugged GPGPU System Provides Critical Real-Time Image Recognition

Aitech’s next-generation A176 uses high-performance, low-Power NVIDIA Jetson TX2

 

Technical highlights:

  • Next-generation rugged GPGPU COTS system enables deep learning capabilities
  • Faster, more accurate data and image processing for better military intelligence
  • Offers high performance computing, while drawing very little power

Chatsworth, Calif., May 2017 – Military intelligence now has access to enhanced data and imaging processing through Aitech Defense Systems’ next generation A176, a rugged GPGPU system that incorporates the NVIDIA Jetson TX2 system-on-module (SoM).

Building on the company’s field-proven A176 Cyclone GPGPU supercomputer launched in 2016, Aitech’s latest high-performance embedded computer (HPEC) uses the Jetson TX2 to provide twice the performance of its predecessor, or run at more than twice the power efficiency, while drawing less than 7.5 watts of power.

The new A176 features the same fanless, conduction-cooled design and measures only 25.5 cubic inches for high performance in a small form factor (SFF) HPEC system.

“With the increased power to performance ratio that the Jetson TX2 infuses into our next generation A176 GPGPU, we believe the use of deep learning in embedded computing is poised to grow exponentially,” said Dan Mor, product line manager, Aitech Defense Systems. “The industry hasn’t seen this type of processing in a compact form factor to date – it’s truly redefining what is possible.”

In addition to incorporating the new NVIDIA Jetson TX2 module, the unit now supports more hardware I/O and software options (1553, ARINC 429, Camera Link Frame Grabber), allowing even faster integration to save development time and money.

The internal microSD storage enables more design flexibility to scale the supercomputer to more complex compute-intensive applications. This includes data convolutions and transpositions, image and data manipulation, application of digital filters, image and frame object edge detection, and image recognition and data analysis.

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