MEMS and Sensors

Newark now stocking BeagleBone 64 bit SBC

29 July 2022
The BeagleBone 64-bit single board computer contains numerous options on the board itself as well as dozens of off-the-shelve expansion options. Source:

Newark, a division of Avnet, is now carrying BeagleBone AI-64, what is billed as the first 64-bit open hardware single board computer (SBC) designed for makers and engineers to build embedded applications with complete artificial intelligence (AI) and machine learning systems.

The BeagleBone platform comes with the on-board peripherals required to start learning and building applications with expansion possibilities with hundreds of open-source hardware examples and dozens of readily available off-the-shelf expansion options.

The SBC uses Linux and is powered by Texas Instruments’ TDA4VM system-on-chip (SoC) dual Arm Cortex-A72 cores, a programmable C7x digital signal processor (DSP) core and deep learning, vision and multimedia accelerators.

Newark said this allows developers a wide range of computing power to create applications such as autonomous robots and drones, smart buildings and factories, home security, retail automation, media services, machine learning, machine vision and computer vision.

“We believe this board will capture the imaginations of designers and empower them to build complete and powerful AI systems,” said Christine Long, CEO of the Foundation. “At an extremely competitive price point, we are excited about the new applications that BeagleBone AI-64 will enable for new and experienced users.”

Other features of the BeagleBone AI-64 include:

  • Expansion add-in boards and ikroBUS Shuttle header with access to hundreds of existing click sensors and actuators.
  • 4 GB of LPDDR4, 6 GB eMMC flash with high-speed interface and a MicroSD card.
  • M.2 E-key PCIe connector to interface with Wi-Fi/Bluetooth adapters, USB 3.0 Type C, two USB 3.0 Type-A and Gigabit Ethernet.
  • Mini DisplayPort interface.
  • Boot, reset and power buttons, power indication LED and five user LEDs.
  • Image signal processor and multiple vision assist accelerators.
  • TDA4VM Dual 64-bit Arm Cortex-A72, 2.0 GHz processor with a C7x floating point, vector DSP, 80 GFLOPS, 256 GOPS, deep-learning MMA and up to 8 TOPS (8b) up to 1.0 GHz.
  • DMPAC, dual 64-bit Arm Cortex-A72 microprocessor subsystem at up to 2.0 GHz, six Arm Cortex-R5F MCUs at up to 1.0 GHz, memory subsystem with up to 8 MB of on-chip L3 RAM with ECC and coherency and 12 multichannel audio serial port modules.
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