RISC-V open architecture allows designers to implement their own instructions, and some of those may become an official RISC-V extension. But the process to approve a new extension may have been suboptimal, so RISC-V International has just unveiled the Fast Track Architecture Extension Process, or Fast Track for short, that streamlines the ratification of small architecture extensions, as well as ZiHintPause, the first extension to be ratified under the new Fast Track process. The process is designed for simpler extensions that are uncontentious and offer value to the RISC-V community at large, so it’s not suitable for more complex extensions. An extension that has been submitted for consideration will undergo an internal review before entering a 45-day public review process. You can read detailed rules for the new extension ratified process here. The ZiHintPause extension went through this 45-day review process on Google Group, and was very recently ratified. The […]
Arduino MKR inspired MKR Windy board is equipped with STM32WL LoRa SoC
We recently wrote about MKR SharkyPro BLE, Zigbee, OpenThread development board based on STM32WB55 MCU and following Arduino MKR form factor, but it turns out Midatronics has also launched a similar-looking board with LoRa connectivity. MKR Windy board features the company’s Windy STM32WL module with an uFL connector and following the same Arduino MKR layout. MKR Windy specifications: Wireless Module – Windy module (MDX-STWLU-R01) Wireless MCU – STMicro STM32WLE5JX/STM32WL55JX Arm Cortex-M4 MCU @ 48 MHz with up to 256KB flash, 64KB SRAM Connectivity Semtech SX126x sub-GHz radio with LoRa, (G)FSK, (G)MSK, and BPSK modulation, 150 MHz to 960 MHz frequency range RX Sensitivity: –123 dBm for 2-FSK, -148 dBm for LoRa Antenna – uFL connector for external antenna Supply Voltage – 1.8 V to 3.6 V Dimensions : 16 x 26 mm Temperature Range – 40°C to + 85 °C USB – 1x Micro USB port for power and programming […]
Intel Jasper Lake N-Series launched with 6W Celeron and 10W Pentium Silver processors
Intel has finally announced the Gemini Lake processor family successor at CES 2021 together with other processors. The Jasper Lake family currently comes with six different Celeron and Pentium Silver parts with respectively 6W and 10 TDP. The company positions those for the education market, but I’d expect them to also be found in various mini PCs, single board computers, and systems-on-module. The processors are manufactured with the company’s 10nm process, and are said to deliver up to 35% better overall application performance and up to 78% better graphics performance compared to Gemini Lake Refresh processors. The new parts listed on Ark are not really new for CNX Software readers as we published the list of Jasper Lake processors in September following a leak. But we know have more details, so let’s compare the top parts of both Gemini Lake Refresh (Pentium Silver J5040) and Jasper Lake (Pentium Silver N6005) […]
MKR SharkyPro BLE, Zigbee, OpenThread development board follows Arduino MKR form factor
Just a few days ago, we mentioned STMicro launched STM32WB5MMG wireless module to simplify Bluetooth LE, Zigbee, OpenThread connectivity by allowing 2-layer baseboards for the module. It turns out there’s also such a module from a third-party with namely Midatronics SharkyPro module based on STM32WB55, and the company also launched MKR SharkyPro I & II development boards following Arduino MKR form factor. MKR SharkyPro specifications: Wireless Module – SharkyPro module Wireless MCU – STMicro STM32WB55CG/CE dual-core Arm Cortex-M4 core at 64 MHz (application processor) and Arm Cortex-M0+ core at 32 MHz (network processor) with 512KB flash, 256KB SRAM Connectivity – Bluetooth 5.0 LE, Bluetooth Mesh 1.0, OpenThread, Zigbee, and other IEEE 802.15.4 proprietary protocols Antenna – Onboard chip antenna (SharkyPro I) or SMA antenna connector (SharkyPro I) Power 3.3V supply voltage Consumption – 13 nA in shutdown mode, 600 nA in Standby mode + RTC + 32 KB RAM Dimensions […]
DBM10 AI SoC is optimized for battery-powered voice and sensor processing
DSP Group announced DBM10 a low-power AI/ML-enabled dual-core SoC. The SoC is equipped with a DSP (Digital Signal Processor) and a dedicated nNetLite NN (Neural Network) processor that improves voice and sensor processing and ensures low-power consumption when working with sufficient-sized neural networks. Key Specifications of NN Processor Form factor: ~4 mm2 Ultra-low-power inference consumption – ~500 µW (typical) for voice NN algorithms Runs Hello Edge 30-word detection model @ 1 MHz (125 MHz available) Allows porting of large models (10s of megabytes) without significant accuracy loss using model optimization and compression. DBM10 AI SoC uses the combined functioning of machine learning, voice, and sensor parameters. This includes voice trigger (VT), voice authentication (VA), voice command (VC), noise reduction (NR), acoustic echo cancellation (AEC), sound event detection (SED), proximity and gesture detection, sensor data processing, and equalization. The DBM10 is suitable for battery-operated devices like smartphones, tablets, and wearables. It […]
STM32WB5MMG Wireless Module simplifies Bluetooth LE, Zigbee, OpenThread connectivity
The STM32WB5MMG (STM32) is a wireless microcontroller module by STMicroelectronics. It is a compact ultra-low-power module that allows customers to design 2-layer PCBs and integrates everything up to the antenna, including an IPD (integrated passive device) for reliable antenna matching in order to reduce the overall costs. The STM32 wireless module is compatible with BLE (Bluetooth Low Energy) 5.0, OpenThread, Zigbee 3.0, dynamic and static concurrent modes, and 802.15.4 proprietary protocols. It also supports simultaneous dual-protocol mode that allows IEEE 802.15.4 radio-based protocols like Zigbee 3.0 and OpenThread for direct connection with any BLE device. Overview of STM32 Wireless Module The STM32 wireless module is a SiP-LGA86 package (System in Package Land Grid Array) with various external components including: STMicro STM32WB55 Cortex-M4/M0+ wireless MCU LSE crystal HSE crystal Passive components for SMPS Antenna matching and antenna IPD for RF matching and harmonics rejection Key Features of STM32 Wireless Module Dedicated […]
BHI260AP is an AI smart sensor with built-in IMU by Bosch Sensortec
BHI260AP AI smart sensor integrates a 6-axis IMU, a 32-bit customizable programmable microcontroller, and various software functionalities. The AI smart sensor has embedded AI with on-sensor applications such as fitness tracking, navigation, machine learning analytics, and orientation estimation. The dimensions of the miniaturized AI smart sensor are 4.1mm x 3.6mm x 0.83 mm. Hardware Features of BHI260AP AI Smart Sensor ARC EM4 CPU includes ARCv2 16/32 bit instruction set working up to a frequency of 3.6 MHz. The core also integrates Floating Point Unit (FPU) and Memory Protection Unit (MPU) with 4 channel micro DMA controller. CPU has two modes of AI functioning at 25Hz and 50Hz with 249µA and 386µA of current consumption respectively. Integrated sensor (6-DoF IMU) includes 16-bit 3 axis accelerometer and 16-bit 3 axis gyroscope. The sensor works at an operating voltage of 1.8 V with a standby current value of 8µA, hence the power consumption […]
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 […]