MangoPi mCore-R818 module powers CyberPad 3.1-inch handheld android “tablet”

CyberPad Components

mCore-R818 is the first time that MangoPi adopts the design combination of a core-lite module and a carrier board. As its name suggests, it is an AllWinner R818 SoM whose SoC integrates an Imagination PowerVR GE8300 GPU for UI rendering, can drive MIPI DSI, LVDS, and RGB displays, as well as cameras through a MIPI CSI interface, 8MP/5MP/2MP interfaces. The Allwinner R818 system-on-module powers a feature-rich carrier board as well as an upcoming Cyberpad Android “tablet” with a 3.1-inch display. MangoPi mCore-R818 The package design of the processor itself is small, so the MCore-R818 core board is only 3x3cm in size, but still contains four components with the Allwinner R818, the eMMC flash, LPDDR4 memory, and the AXP717 PMU. MangoPi provides two hardware configurations: 2GB DDR with 16GB eMMC flash, and 4GB DDR with 32GB eMMC flash. MCore-R818 Core Lite Specifications: SoC – Allwinner R818 CPU – Quad-core Arm Cortex-A53 […]

AndesAIRE AnDLA I350 AI/ML IP block is configurable from 64 GOPS to 8TOPS for Edge AI SoCs

Andes Technology has just announced the AndesAIRE product line, where AndesAIRE stands for Andes AI Runs Everywhere, comprised of the AndesAIRE AnDLA I350 (Andes Deep Learning Accelerator) AI/ML hardware accelerator intellectual property (IP) and the AndesAIRE NN SDK with neural network software tools and runtimes. AndesAIRE AnDLA I350 AnDLA I350 specifications: Configurable MACs from 32 to 4096 (INT8) Maximum performance – 8 TOPS at 1GHz Configurable local memory – 16KB to 4MB Multi-dimension DMA Four 64-bit AXI bus interfaces NN type – CNN inference NN models Image and Video: AlexNet, VGG-16/19, MobileNet-v1/v2/v3, ResNet-8/50, Tiny YOLO v1/v2, YOLO v1/v2/v3/v4/v5, SSD MobileNet v1/v2, Inception v2, EfficientNet-lite, MobileFaceNet, BlazeNet Speech/Voice and audio: LSTM, RNN, GRU Operators: Conv2d, depthwise convolution, pointwise convolution, transpose convolution, dilated convolution, element-wise (add, sub, mul), fully-connected, activation (ReLU, leaky ReLU, sigmoid, Tanh, ReLU6, SiLU), pooling (max, ave), upsample, concatenation, batch normalization, channel padding Operator fusion NHWC data format The IP […]

HARDWARIO CHESTER – A configurable Zephyr OS LPWAN IoT gateway with LoRaWAN, LTE IoT, GNSS connectivity

HARDWARIO CHESTER platform is a configurable LPWAN IoT gateway whose main function is to connect as many devices and environments as possible to the Internet using connectivity such as LoRaWAN, LTE Cat M1, or NB-IoT, as well as GNSS for geolocation. Contrary to most IoT gateways, it does not run Linux on an application processor, and instead, the “brain” of the CHESTER IoT gateway is a Raytac Bluetooth 5.0 module based on a Nordic Semi nRF52840 Arm Cortex-M4 microcontroller running Zephyr real-time operating system, which connects to LTE IoT modem and a LoRaWAN module through UART, and expansion modules through I2C, 1-wire, and GPIO interfaces. HARDWARIO CHESTER specifications: Wireless modules/chips Raytac MDBT50Q-P1MV2 Bluetooth 5.0 module based on Nordic Semi nRF52840 Arm Cortex-M4F MCU with 1MB Flash memory, 256kB RAM Nordic Semi nRF9160-SICA-B1A-R7 LTE-M/NB-IoT system-in-package (SiP) with Arm Cortex-M33 MCU, 1024 KB flash, 256 KB SRAM Murata CMWX1ZZABZ-078 LoRa module as […]

Sony IMX500-based smart camera works with AITRIOS software

Raspberry Pi recently received a strategic investment from Sony (Semiconductor Solutions Corporation) in order to provide a development platform for the company’s edge AI devices leveraging the AITRIOS platform. We don’t have many details about the upcoming Raspberry Pi / Sony device, so instead, I decided to look into the AITRIOS platform, and currently, there’s a single hardware platform, LUCID Vision Labs SENSAiZ SZP123S-001 smart camera based on Sony IMX500 intelligent vision sensor, designed to work with Sony AITRIOS software. LUCID SENSAiZ Smart camera SENSAiZ SZP123S-001 specifications: Imaging  sensor – 12.33MP Sony IMX500 progressive scan CMOS sensor with rolling shutter, built-in DSP and dedicated on-chip SRAM to enable high-speed edge AI processing. Focal Length  – 4.35 mm Camera Sensor Format – 1/2.3″ Pixels (H x V) – 4,056 x 3,040 Pixel Size, H x V – 1.55 x 1.55 μm Networking – 10/100M RJ45 port Power Supply – PoE+ via […]

AMD Alveo MA35D media accelerator transcodes up to 32 1080p60 AV1 streams in real-time

AMD Alveo MA35D media accelerator PCIe card is based on a 5nm ASIC capable of transcoding up to 32 Full HD (1080p60) AV1 streams in real-time and designed for low-latency, high-volume interactive streaming applications such as watch parties, live shopping, online auctions, and social streaming. AMD says the Alveo MA35D utilizes a purpose-built VPU to accelerate the entire video pipeline, and the ASIC can also handle up to 8x 4Kp60, or 4x 8Kp30 AV1 streams per card. H.264 and H.265 codecs are also supported, and the company claims its “next-generation AV1 transcoder engines” deliver up to a 52% reduction in bitrate at the same video quality against “an open source x264 veryfast SW model”. AMD Alveo MA350 highlights: Auxiliary CPU – 2x 64-bit quad-core RISC-V to perform control and board management tasks AI Processor – 22 TOPS per card for AI-enabled “smart streaming” for video quality optimization Memory – 16GB […]

SOPHON BM1684/BM1684X Edge AI computer delivers up to 32 TOPS, decodes up to 32 Full HD videos simultaneously

Firefly EC-A1684JD4 FD and EC-A1684XJD4 FD are nearly identical Edge AI embedded computers based on respectively SOPHON BM1684 and BM1684X Arm AI SoC delivering up to 32 TOPS of AI inference, and capable of decoding up to 32 H.265/H.264 Full HD videos simultaneously for video analytics applications. The BM1684(X) SoCs are equipped with eight Cortex-A53 cores clocked at 2.3 GHz to run Linux, and the systems come with up to 16GB RAM, 128GB flash, two Gigabit Ethernet ports to receive the video streams, one HDMI output up to 1080p30 for monitoring,  as well as RS232 and RS485 DB9 connectors, and a few USB ports. Firefly EC-A1684JD4 FD and EC-A1684XJD4 FD specifications: SoC – SOPHGO SOPHON BM1684/BM1684X CPU – Octa-core Arm Cortex-A53 processor @ up to 2.3GHz TPU BM1684 64 NPU arithmetic units with each NPU containing 16 EU arithmetic units, or 1,024 EU in total Up to 17.6 TOPS (INT8), […]

$499 NVIDIA Jetson Orin Nano Developer Kit delivers up to 80x Jetson Nano Devkit performance

NVIDIA Jetson Orin Nano Developer Kit is an upgrade to the popular Jetson Nano Developer Kit that delivers 80 times the performance, up to 50 times the performance per watt, and gives the developers the ability to design entry-level AI-powered robots, smart drones, intelligent vision systems, and more. The Jetson Orin Nano has a similar form factor as the original Jetson Nano, but is fitted with a Jetson Orin Nano 8GB module with up to 40 TOPS AI performance, and is equipped with a DisplayPort video output, USB 3.2 Gen 2 ports, two M.2 Key M sockets for SSDs, Gigabit Ethernet, a pre-installed Wi-Fi module, and connectors for cameras. NVIDIA Jetson Orin Nano Developer Kit specifications (compared to Jetson Nano Developer Kit-B01) The new developer kit is supported by the Ubuntu 20.04-based NVIDIA JetPack 5.1.1 SDK, as well as application-specific frameworks such as NVIDIA Isaac ROS and DeepStream, which are […]

Android 14 developer preview brings enhancements to performance, privacy, security, and user customization

Google has just released the first developer preview of Android 14 with productivity improvements for developers, as well as enhancements to performance, privacy, security, and user customization. Android 14 aims to work better across devices and form factors with improved support for tablets and foldables and adds window size classes, sliding pane layout, Activity embedding, and box with constraints, etc… To help developers, the company also published “Get started with large screens” documentation and released a Cross-device SDK preview. The new version of the mobile operating systems also further streamlines background work to optimize system health and battery life and provide a better end-user experience. This is achieved through updates to JobScheduler and Foreground Services, optimized broadcasts most of which are internal to Android 14, and a new “Exact alarms” permission since it consumes more resources. Android 14 also introduced some user-facing changes with bigger fonts up to 200% with […]

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