K210 AI Accelerator Raspberry Pi pHAT targets secure AIoT projects (Crowdfunding)

Kendryte K210 is a dual-core RISC-V AI processor that was launched in 2018 and found in several smart audio and computer vision solutions. We previously wrote a Getting Started Guide for Grove AI HAT for Raspberry Pi using Arduino and MicroPython, and XaLogic XAPIZ3500 offered an even more compact K210 solution as a Raspberry pi pHAT with Raspberry Pi Zero form factor. The company is now back with another revision of the board called “XaLogic K210 AI accelerator” designed to work with Raspberry Pi Zero and larger boards with the 40-pin connector. K210 AI Accelerator board specifications: SoC – Kendryte K210 dual-core 64-bit RISC-V processor @ 400 MHz with 8MB on-chip RAM, various low-power AI accelerators delivering up to 0.5 TOPS, Host Interface – 40-pin Raspberry Pi header using: SPI @ 40 MHz via Lattice iCE40 FPGA I2C, UART, JTAG, GPIOs signals Security Infineon Trust-M cloud security chip 128-bit AES Accelerator and SHA256 Accelerator on Kendryte K210 SoC Expansion – […]

LG launches LG8111 AI SoC and development board for Edge AI processing

LG8111 AI Soc Development Board Eris

LG Electronics has designed LG8111 AI SoC for on-device AI inference and introduced the Eris Reference Board based on the processor. The chip supports hardware processing in artificial intelligence functions such as video, voice, and control intelligence. LG8111 AI development board is capable of implementing neural networks for deep learning specific algorithms due to its integrated “LG-Specific AI Processor.” Also, the low power and the low latency feature of the chip enhances its self-learning capacity. This enables the products with LG8111 AI chip to implement “On-Device AI.” Components and Features of the LG8111 AI SoC LG Neural engine, the AI accelerator has an extensive architecture for “On-Device” Inference/Leaning with its support on TensorFlow, TensorFlow Lite, and Caffe.  The CPU of the board comes with four Arm Cortex A53 cores clocked at 1.0 GHz, with an L1 cache size of 32KB and an L2 cache size of 1MB. The CPU also enables NEON, FPU, and Cryptography extension. The camera engine has […]

FPGA powered Corazon-AI gateway supports up to 8 IP cameras for video analytics

corazon-ai

Earlier this year, we covered some video analytics solutions based on AAEON UP Xtreme Edge embedded computer combining an Intel Whiskey Lake processor with Intel Movidius Myriad X AI accelerator modules, as well as video management & analytics software solutions from Milestones & SAIMOS, or aotu.ai BrainFrame. iWave Systems has now introduced a similar solution with Corazon-AI gateway capable of handling up to 8 IP cameras in real-time,  but instead of relying on AI accelerators, the company leverages Xilinx Zynq Ultrascale+ Arm Cortex-A53/R5 FPGA MPSoC for AI inference. Corazon-AI gateway specifications: SoC – Xilinz Zynq Ultrascale+ ZU2, ZU3, ZU4 or ZU5 MPSoC Processing System (PS) Quad/Dual Arm Cortex-A53 @ 1.5GHz, dual Cortex-R5 @ 600MHz Arm Mali-400MP2 GPU @ 677MHz H.264/H.265 Video Encoder/Decoder Programming Logic (PL) Up to 256K Logic cells PL GTH Transceivers x 4 @ 12.5 Gbps System Memory 64bit, 2GB DDR4 with ECC for PS (upgradable) 32bit, 1GB DDR4 for PL (upgradable) Storage – 8GB eMMC Flash (upgradable), […]

Boardcon RK1808 SBC Targets Smart Audio & Computer Vision Applications

RK1808 SBC

Rockchip RK1808 neural network processing unit was initially an IP Block inside RK3399Pro, but the company eventually launched RK1808 Cortex-A35 processor as a standalone solution now providing up to 3.0 TOPS for AI inferencing in modules, USB sticks, and development kits. Boardcon offers another option with EM1808, a Rockchip RK1808 SBC equipped with the processor. The board should be suitable for two main types of AI applications, namely smart audio applications thanks to four audio ports, speaker header, & an onboard 4-mic array, and computer vision with MIPI CSI & DSI interfaces. Boardcon EM1808 board is comprised of a baseboard and CPU module with the following overall specifications: SoC – Rockchip RK1808 dual Cortex-A35 processor up to 1.6GHz with 3.0 TOPS (for INT8) NPU, VPU supporting H.264 1080p60 decode, 1080p30 encode System Memory- 2GB LPDDR3 Storage – 8GB eMMC flash, MicroSD slot, M.2 NVMe SSD interface Display I/F – 26-pin MIPI DSI header Camera I/F – 26-pin MIPI CSI header […]

Mustang-M2BM-MX2 M.2 Card Features Two Intel Movidius Myriad X VPUs

Mustang-M2BM-MX2

We’ve already seen M.2 cards based on one or more Intel Movidius Myriad X VPU with the likes of AAEON AI Core XM2280 M.2 card, but there’s now another option from Taiwan-based IEI Integration Corp with their Mustang-M2MB-MX2 card. Specifications: AI Accelerators – 2x Intel Movidius Myriad X MA2485 VPU Dataplane Interface – M.2 BM Key Power Consumption – Around 7.5W Cooling – Active Heatsink Dimensions – 22 x 80 mm Temperature Range – -20°C~60°C Humidity – 5% ~ 90% Just like other Myriad X devices, the card relies on Intel OpenVINO toolkit working on Ubuntu 16.04.3 LTS 64-bit, CentOS 7.4 64-bit or Windows 10 64-bit operating systems, and supporting AlexNet, GoogleNetV1/V2, MobileNet SSD, MobileNetV1/V2, MTCNN, Squeezenet1.0/1.1, Tiny Yolo V1 & V2, Yolo V2, ResNet-18/50/101 topologies, as well as TensorFlow, Caffe, MXNet, and ONNX AI frameworks. The heatsink is really thick (~2 cm high), so it’s not something you’d just put in your laptop, and instead, it’s better suited to […]

SolidRun Janux GS31 Edge AI Server Combines NXP LX2160A & i.MX 8M SoCs with 128 Gyrfalcon AI Accelerators

SolidRun Janux GS31-Edge AI Inference Server

AI inference used to happen exclusively in powerful servers hosted in the cloud, but in recent years great efforts have been made to move inference at the edge, usually meaning on-device, due to much lower latency, and improved privacy. On-device inference works, but obviously, performance is limited, and on battery-operated devices, one also has to consider power consumption. So for some applications, it makes sense to have a local server with much more processing power than devices, and lower latency than the cloud. That’s exactly the use case SolidRun Janux GS31 Edge AI inference server is trying to target using several NXP processors combined with up to 128 Gyrfalcon Lightspeeur SPR2803 AI accelerators Janux GS31 server specifications: CPU Module – CEx7 LX2160A COM Express module with NXP LX2160A 16-core Arm Cortex A72 processor @ 2.0 GHz System Memory – Up to 64GB DDR4 RAM via 2x SO-DIMM sockets “Video” Processors – Up to 32x NXP i.MX 8M Cortex-A53 SoC with […]

AAEON M.2 and mPCIe Cards for AIoT Acceleration Run Kneron KL520 AI SoC

The AAEON announcement of its AI Acceleration M.2 and mini-PCIe cards AAEON uses Kneron KL520 AI SoC dual Cortex-M4 on a series of new modules that are accelerating AI edge computing and that only need 0.5 Watt of power. The modules are M.2 and mini-PCIe AI acceleration cards, that offer a new way to come at AI acceleration. What AI Features are Enhanced The cards are meant to enhance and accelerate AI functions, like gesture detection, facial and object recognition, driver behavior in such AIoT areas as access control, automation, and security. History of the AAEON Development Previously AAEON has been offering the M.2 and mini-PCIe AI core modules for the Boxer computers that are based on the Intel Movidius Myriad 2 and Myriad X Vision Processing Units (VPU). Reporting was done on these previous releases in the articles on the UP AI core mini-PCIe card and the  AI Core XM2280 M.2 card, using two Myriad X VPUs. AAEON is […]

AAEON BOXER-8310AI Rugged Fanless Mini PC Combines Apollo Lake Processor & Myriad X VPU for AI Edge Applications

AAEON BOXER-8310AI rugged fanless mini PC

We’ve covered several of AAEON rugged mini PCs part of BOXER-8100 family powered by an NVIDIA Tegra X2 processor and targetting AI Edge applications. The company has now introduced three new AI embedded computers for the same AI edge applications but using Intel processors together with Intel/Movidius Myriad X VPU (Vision Processing Unit) for AI acceleration. The three models are BOXER-8310AI, BOXER-8320AI, and the upcoming BOXER-8330AI based on respectively Intel Celeron/Pentium Apollo Lake processor, Intel Core i3 7th gen processor, and an Intel Core i3/77 or Xeon processor. I’ll focus on the Apollo Lake model in this post to introduce AAEON BOXER-8300AI family of rugged mini PCs. BOXER-8310AI specifications: SoC (one or the other) Intel Pentium N4200 quad-core Apollo Lake processor Intel® Celeron N3350 dual-core Apollo Lake processor System Memory –  1x DDR3L SODIMM slot supporting up to 8GB RAM @ 1867 MHz Storage Device – mSATA socket AI Module – AI Core X with Intel Movidius Myriad X VPU […]