Hailo-8™ Century High Performance PCIe Cards

Prototype & Develop High-Performance, High-Efficiency Edge AI Video Analytics Systems with Multiple Hailo-8™ AI Processors​

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Today’s intelligent vision systems are high-resolution, high-frame-rate and multi-sensor, requiring more powerful and accurate real-time AI processing power.
To support developers of high-performance edge video analytics systems across industry verticals, the Hailo industry-leading Hailo-8 AI accelerator is now available in a PCIe form factor, delivering a range of up to 208 TOPS of AI performance at a low power consumption.
The high-performance Century PCIe cards enable deep neural network inferencing in real-time with low power consumption for a broad range of market segments and applications on any platform with a 16-lane PCIe slot.

  • Delivering 52-208 Tera Operations Per Second (TOPS)
  • Supporting industrial temperature range of -40°C to 85°C
  • Best-in-class power efficiency, at 400 FPS/W in ResNet50 benchmark model
  • Highest cost-efficiency, starting at $249
  • Enabling real-time, low latency, and highefficiency concurrent processing of complex pipelines with multi-streams and multi-models
  • Robust software suite supports state-of-the-art deep learning models & applications out-of-the-box

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Small form factor Wide host compatibility
Model number 0802 0803 0804 0804S 0805S 0806S 0807S 0808S
# of TOPS 52 78 104 104 130 156 182 208
Form factor single slot, HHHL single slot, HHFL
Interface PCleX16 slot with bifurcation PCleX16 slot
Dimensions 69 X 168 mm 111 X 210 mm
Max thermal design power (TDP) 10W-25W 35-65W
Supported OS Linux, Windows
Supported AI frameworks Tensorflow, Tensorflow Lite, Keras, Pytorch & ONNX
Century_Wide_host_compatibility

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Title File type Date modified
Hailo-8™ Century PCIe Product Brief PDF 15/08/2023
Breathe life into your edge products
with the Hailo-8™ AI processor

EU Research and Innovation Program

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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 849921

This project has received funding from the European Union’s Horizon 2020.