We first discovered Hailo-8 AI accelerator with claims of up to 26 TOPS performance and 3TOPS/W efficiency in October 2020. Since then, we’ve seen several integrate an Hailo-8 M.2 module into their design including EdgeTuring Edge AI camera and Vecow VAC-1000 gateway with a 24-core Foxconn processor. Vecow has now integrated the Hailo-8 AI accelerator into another gateway, but instead of relying on an Arm processor, the Vecow ABP-3000 AI computing system features an 8th generation Intel Core Whiskey Lake processor. Vecow ABP-3000 specifications: SoC – Intel Core i7-8665UE or i3-8145UE quad-core Whiskey Lake processor with Intel UHD Graphics 620; 15W TDP System Memory – 2x DDR4 2400MHz SO-DIMM, up to 64GB Storage – 1x M.2 Key B Socket (PCIe x2/SATA) AI Accelerator – Hailo-8 AI Processor, up to 26 TOPS with TensorFlow, ONNX frameworks support System IO chip – IT8786E Video Output – 2x DisplayPort up to 4096 x […]
Learn more about Hailo-8 AI accelerator and understanding AI benchmarks
Last week we wrote about Hailo-8 M.2 card delivering up to 26 TOPS of AI performance, and comparing well against Google Edge TPU and Intel Movidius Myriad X both in terms of footprint, performance, and efficiency. I’ve since then had a conference call with Liran Bar, VP of Business Development for Hailo, where we had time to discuss more about Hailo’s AI solutions, and how to interpret & understand AI benchmarks that may be misleading in many instances. Hailo-8 Architecture In the first post, we noted the chip managed to get the extra performance and efficiency thanks to a “proprietary novel structure-driven Data Flow architecture instead of the usual Von Neumann architecture”. But that’s a bit abstract, so Liran told me one of the key reasons for the performance improvement is that RAM is self-contained without the need for external DRAM like other solutions. This decreases latency a lot and […]