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July 27, 2022 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

mini PCIe module features Rockchip RK1808K SoC with 3.0 TOPS NPU

Toybrick RK1808 mPCIe AI accelerator card

Rockchip RK1808 SoC with a built-in 3.0 TOPS AI accelerator has been around since 2019, and we’ve seen it in USB compute sticks, SBCs, and even in Pine64 SoEdge-RK1808 SO-DIMM module, but somehow never in the more widely used M.2 or mPCIe form factors. Toybrick TB-RK1808M0 changes that and offers Rockchip RK1808K SoC coupled with 1GB RAM and an 8GB eMMC flash in a mini PCIe module that exposes USB 3.0, USB 2.0, UART, and GPIO signals. Toybrick TB-RK1808M0 specifications: SoC – Rockchip RK1808K CPU – Dual-core Cortex-A35 processor @ up to 1.4 GHz AI Accelerator – 3.0 TOPS NPU for INT8 inference (300 GOPS for INT16, 100 GFLOPS for FP16) VPU – 1080p60 H.264 decode, 1080p30 H.264 encode System Memory – 1GB DDR Storage – 8GB eMMC flash Host interface – Mini PCIe edge connector with USB 3.0, USB 2.0, UART, and GPIO Misc – Heatsink for cooling Supply […]

July 1, 2021July 1, 2021 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Jevois Pro small AI camera with Amlogic A311D SoC offers up to 13 TOPS (Crowdfunding)

Jevois-A33 smart camera was a tiny Linux camera with Allwinner A33 processor designed for computer vision applications and announced in 2016. I had the opportunity to review the computer vision camera the following year, and it was fun to use to learn about computer vision with many examples, but since it relied on the CPU for processing, it would not have been suitable for all projects due to the lag, as for example, object detection took 500ms and Yolo V3 around 3 seconds per inference. But time has passed, and great progress has been made in the computer vision and AI fields with the tasks now usually handled by a built-in NPU, or an AI accelerator card. So JeVois Pro deep learning camera has just been launched with an Amlogic A311D processor featuring a 5 TOPS NPU, and support for up to 13 TOPS via a Myriad X or Google […]

January 31, 2021 by Jean-Luc Aufranc (CNXSoft) - 12 Comments

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 […]

December 27, 2020December 26, 2020 by Saumitra Jagdale - 1 Comment

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

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 […]

October 15, 2020October 15, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

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

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 […]

April 17, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

Boardcon RK1808 SBC Targets Smart Audio & Computer Vision Applications

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 […]

February 7, 2020February 12, 2020 by Jean-Luc Aufranc (CNXSoft) - No Comments

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

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 […]

January 13, 2020January 13, 2020 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

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 […]