Nexcom AIBooster-X8-MXM Intel Movidius Myraid X VPU Deep Learning Accelerator

Nexcom AIBooster-X8-MXM Intel Movidius Myraid X VPU Deep Learning Accelerator

AIBooster-X8-MXM

  • Eight Myriad X MA2485 VPU
  • MXM form factor
  • Total 32Gb LP-DDR4 SDRAM on chips
  • Support OpenVINO™ toolkit
  • M/JPEG 4K at 60Hz encoder
  • H.264/H.265 4K at 30Hz encoder
  • Low power consumption

Customisation Service

We can configure this device for you to your exact specification. So we can provide you with the best possible service, please let us know a little about your project if you need this service.

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Details

AIBooster-X8-MXM MXM module integrated with Intel® Movidius™ VPUs drive the demanding workloads of modern computer vision and AI applications at ultra-low power. The dedicated Neural Compute Engine in Myriad X delivers more performance per Watt, and it helps AIBooster-X8-MXM achieves a perfect balance of power efficiency and high performance. Since AIBooster-X8-MXM is also designed for power constrained environments, it provides the ideal solution for device makers seeking to deploy advanced AI mobile applications at the edge.

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Specification

VPU Engine Eight Myriad X MA2485 VPU Per VPU with– Up to 1 TOPS– 16 programmable 128-bit VLIW vector processors– CPUs 2x LEON 4 cores (RISC; SPARC V8)– On-chip accelerators 20+ image/vision processing accelerator Neural compute engine (DNN accelerator)– Neural network capability neural compute engine
Memory Total 32Gb LP-DDR4 SDRAM on chips
Encoder M/JPEG 4K at 60Hz encoder H.264/H.265 4K at 30Hz encoder
MXM (PCIe x4) MXM (PCIe x4)
OS Support Ubuntu 16.04.1/Kernel 4.10.0 Ubuntu 16.04.3/Kernel 4.14.20 Windows 10 Enterprise 64-bit
Feature Support Intel® OpenVINO toolkit
Supported Network Topology AlexNet, GoogleNet v1 & v2, Yolo Tiny* V1 & V2, Yolo V2, MobileNet-SSD, VGG-d , ResNet-18, Faster-RCNN
Dimensions 113 x 82 mm
Power Consumption < 30 W
Operating Temperature -30°C to +85°C
Memory Capacity Up to 32GB
OS Support Linux, Windows 10