Artificial Intelligence

Radio Transceiver (AIR-T)

AIR-T Embedded Series Product Line

Overview

Key Specifications
Deepwave’s AIR-T is the first software defined radio with embedded high performance computing. It contains three unique digital processors for any application:

• FPGA for strict real-time operations
• GPU for highly parallelized processing
• CPU for control, I/O, and software applications
  This versatile system can function as a highly parallel SDR, data recorder, or inference engine for deep learning algorithms. The embedded GPU allows for SDR applications to process bandwidths greater than 200 MHz in real-time.
• Dual Channel MIMO Transceiver
  • 300 MHz to 6 GHz
  • 100 MHz bandwidth Rx (per channel)
  • 100 MHz bandwidth Tx (per channel)
• Digital Signal / Deep Learning Processors
  The AIR-T allows users to easily incorporate artificial intelligence into their radio frequency and wireless technologies.
• High-speed digital I/O (GPIO/UART)
  • 1 Gbps Ethernet
    • Dual Power Mode:
      • ARM Cortex-A57 CPU (4 core)
      • NVIDIA Denver2 CPU (2 core)
      • NVIDIA Pascal GPU (256 core)
• Dual Power Mode:
  • 22 / 14 Watts

Software Support

• K Keras
• HPC with CUDA toolkit using C/C++ or Python interfaces
• GNURadio
  THE FREE & OPEN SOFTWARE RADIO ECOSYSTEM

Signal Processing Support for

Deepwave Digital, Inc.
1429 Walnut St, Suite 1000, Philadelphia, PA 19102
www.deepwavedigital.com
salesteam@deepwavedigital.com

Mechanical

• Size - 6.7 x 6.7 x 1.4 inches
• Weight - 0.35 kg (0.8 lbs)
  Support for industry leading SDR development environment

Deep Learning

DEEPWAVE DIGITAL

Performance

The AIR-T uses 256 GPU cores to create a highly parallel compute environment making wideband processing for software defined radio (SDR) applications obtainable.
Using the embedded NVIDIA
The AIR-T uses zero copy memory access to overcome the data transfer overhead typically associated with GPU processing.

Real-time DSP Measurements

AIR-T Hardware Abstraction

Fourier Transform Size

AIR-T Hardware

• Pre-trained AI Cores
• AI Frameworks
• User Developed Applications

Embedded Series Models

Performance Table