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AAEON Synthesizes High-Speed Computing Power and Groundbreaking Graphics with the new PICO-V2K4

Posted on 4 June, 20224 June, 2022 by mixos

AAEON introduces the PICO-V2K4, bringing the power of the V2000 processor to the smallest form factor on the market.

With the release of the PICO-V2K4, AAEON has gone one step further in pushing the boundaries of innovation. By creating the smallest embedded single board computer to be powered by the AMD RYZEN™ V2000 embedded processor family, featuring up to 8 cores, AAEON has further reiterated why it is an industry leader in embedded solutions. The PICO-V2K4 also hosts high-performance AMD Radeon™ graphics and 7nm processing technology, all on a 3.94″ x 2.84″ form factor, opening the door to a broader and more sophisticated range of application uses.

The PICO-V2K4 retains the characteristic versatility that AAEON’s PICO-ITX board range is known for, but its unprecedented high-speed computing power, groundbreaking graphic capability and targeted I/O introduce a new level of refinement to the edge. Such elements will give users everything from unprecedented CPU performance to rugged deployment capabilities, all without sacrificing graphic sophistication.

With exceptional CPU performance courtesy of the V2000 embedded processor family, the PICO-V2K4 has the power to facilitate automated industrial applications, while maintaining longevity and consistency throughout its lifecycle with a thermal design point range of 10~25W. Tying this together is up to 64GB NVMe onboard storage and an M.2 2280 M key port, which will enable expansion modules to suit different application types.

For example, it is easy to see the PICO-V2K4 making a very significant contribution to diagnostic imaging, as an ancillary application to enhance the accuracy and efficiency of x-ray and MRI scan analysis. The PICO-V2K4’s chipset features AMD Radeon Graphics with up to 7 Compute Units, which has the capability to provide 4K resolution graphics to enhance medical imaging, coupled with AI inferencing models to assist with object detection, aiding diagnosis in radiology.

The PICO-V2K4 offers developers a wider audience of potential users, with ultra-high frame rates, faster frequency and clocking, and support for 4 simultaneous 4K displays being not only useful in medical technology but also in gaming. To emphasize this, the PICO-V2K4’s 64GB NVMe storage and M.2 2280 M-key expansion slot provide greater processing speed and improve overall gaming experiences for end users.

Whether it is for gaming, diagnostic imaging, or industrial automation, the PICO-V2K4 offers superior computing power, enhanced graphics, and the dense I/O needed to produce elite applications across any vertical market, all while maintaining a compact form factor and flexible expansion options.

To find out more about the PICO-V2K4, please visit our product page.

Kria™ KR260 Robotics Starter Kit

Posted on 30 May, 202230 May, 2022 by mixos

KR260 kit from AMD-Xilinx is a Kria SOM-based development platform for robotics and factory automation applications

The KR260 robotics starter kit from AMD-Xilinx integrates high-performance industrial interfaces and features native ROS 2 support. It enables roboticists and industrial developers without FPGA expertise to develop hardware accelerated applications for robotics, machine vision, and industrial communication and control. The KR260 is the fastest way to develop intelligent factory solutions for production volume deployment with the K26 SOM.

Features

Optimized for Kria K26 SOM
- 2x 240-pin connectors
- All SOM I/O available for sensor and network connectivity
High performance industrial vision
- SLVS-EC Rx
- 4x USB 3.0 for camera interfaces
- DisplayPort™ 1.2a
Real-time networking interfaces
- 2x 240-pin connectors
- All SOM I/O available for sensor and network connectivity
Expansion with Pmod™ and Raspberry Pi headers
- Extend to any sensor or interface
- Broad Pmod ecosystem
- For example, Wi-Fi adapters and RS485

more information: https://www.xilinx.com/products/som/kria/kr260-robotics-starter-kit.html

Wireless power transfer compatible charger IC for Li-ion batteries XC6810 Series

Posted on 30 May, 202230 May, 2022 by mixos

Torex Semiconductor has launched XC6810 series, a multifunctional compact charging IC for lithium-ion batteries that supports wireless power transfer.

The XC6810 series are small charging ICs for Li-ion batteries, suitable for wearables, hearables, or IoT devices. It has various functions such as charge and discharge control and wireless power supply support. The charging current is 1mA ~ 25mA, suitable for small lithium-ion batteries, and it can provide a wide range of charging voltage of 3.8V ~ 4.4V.The XC6810 series are equipped with shutdown function to suppress battery discharge when stored or not in use, and wake-up function using an external push button, extending the life of batteries and devices.

In addition to the conventional LED-driven display, CSO terminal which indicates the charging status has a type that indicates charging level by frequency, and supports charging monitoring using a microcontroller. The product is equipped with a battery voltage monitoring function, which can directly monitor the battery voltage through a microcontroller, or a low battery voltage notification function.

The wide input voltage range from 3.5V ~ 28V supports wireless power and energy harvester charging such as solar. For contact-type charging using a cradle, a type is available in which the CSO terminal modulates the power supply line and the charging status can be notified by two-wire communication. The charging status and charging control can be displayed through the cradle.

more information: https://www.torexsemi.com/file/xc6810/XC6810.pdf

Monolithic Power Systems (MPS) MP4315 Synchronous Step-Down Converters

Posted on 30 May, 202230 May, 2022 by mixos

Monolithic Power Systems (MPS) MP4315 Synchronous Step-Down Converters offer a configurable frequency and an integrated internal high-side MOSFET (HS-FET) and low-side MOSFET (LS-FET). The MP4315 delivers up to 5A of highly efficient output with current mode control for fast loop response. The device accommodates a wide 3.3V to 45V input voltage range ideal for various step-down applications in automotive input environments.

The MPS MP4315 Synchronous Step-Down Converter provides a low 1.7μA shutdown mode quiescent current designed for battery-powered applications. High power conversion efficiency across a wide load range is achieved by scaling down the switching frequency under light-load conditions to reduce the switching and gate driver losses.

Additionally, the MP4315 converter’s open-drain power good signal indicates whether the output is within 93% to 106% of its nominal voltage. Frequency foldback helps prevent inductor current runaway during start-up. Meanwhile, thermal shutdown delivers reliable, fault-tolerant operation. High-duty cycle and low-dropout mode are supplied for the automotive cold crank conditions.

The MP4315 is housed in a QFN-20 (4mm x 4mm) wettable flank package.

Features

Wide 3.3V to 45V operating voltage range
5A Continuous output current
1.7μA Low shutdown supply current
18μA Sleep mode quiescent current
Internal 48mΩ high-side MOSFET and 20mΩ low-side MOSFET
350kHz to 1000kHz Configurable switching frequency for car battery applications
Can be synchronized to an external clock
Out-of-phase synchronized clock output
Frequency Spread Spectrum (FSS) for low EMI
Symmetric V_IN for low EMI
Power good output
External soft start
100ns Minimum on time
Selectable Advanced Asynchronous Mode (AAM) or Forced Continuous Conduction Mode (FCCM)
Low-dropout mode
Hiccup over-current protection
Available in a QFN-20 (4mm x 4mm) package
Available in a wettable flank package

Typical Application

more information: https://www.monolithicpower.com/en/mp4315.html

Eight-Core Mixtile Blade 3 is a High-performance Pico-ITX Single-Board Computer

Posted on 30 May, 2022 by Saumitra Jagdale

The Internet of Things (IoT) hardware specialist Mixtile, has been preparing to launch a crowdfunding campaign for its compact computer Blade 3. Mixtile’s Blade 3 is a stackable, affordable single-board computer powered by the 8nm Rockchip RK3588 processor. The leading-edge technology, Blade 3 offers powerful, energy-efficient computational support for a wide variety of applications. It is perfect for rapid development, AI-application prototyping, and edge computing.

It has high-performance computing for advanced computer vision and multimedia connectivity through the dynamic integration of hardware and software. This single-board computer was designed with a focus on cluster operation. Blade 3 can be connected in a cluster configuration through its onboard PCIe Gen3 edge connectors that enable it to integrate several high-performance hardware platforms in a small form factor. It targets everything from a single-unit deployment to a high-density clustering and allows you to cluster multiple Mixtile Blade 3 SBCs to scale your deployment.

The main component of this board is Rockchip’s RK3588, which is an eight-core processor with four high-power Arm Cortex-A76 cores running at 2.4GHz and four lower-power Cortex-A55 cores running at 1.8GHz. This SBC also contains an onboard neural processing unit (NPU) to enhance the edge AI workloads while offering up to 6 TOPS peak compute performance, and configurations offering up to 32GB of LPDDR4 RAM and up to 256GB of eMMC storage with an option to expand using the microSD expansion slot.

Mixitile Blade 3 Technical Specifications

CPU: Rockchip RK3588 Octa-core processor Cortex-A76/A55
NPU: Up to 6 TOPS
Memory: Up to 32 GB LPDDR4 memory
Storage: Up to 256 GB eMMC storage
Storage expansion: 4-lane PCIe Gen 3 in U.2 port, SATA 3.0 in U.2 port, Micro-SD 3.0 flash socket
HDMI interface: HDMI 2.1 output (8K at 60 FPS or 4K at120 FPS), HDMI 2.0 input (4K at 60 FPS)
Video encoder: H.264/H.265 video encoder up to 8K at 30 FPS
Video decoder: H.265/H.264/VP9 video decoder up to 8K at 60 FPS
Display: 4-lane MIPI-DSI
USB: Dual USB 3.2 Gen 1 Type-C ports with DisplayPort 1.4 A
PCIe expansion: Mini-PCIe socket with PCIe Gen 2.1
Ethernet expansion: Dual 2.5 gigabit Ethernet ports
GPIOs: 40-pin GPIO socket that can be used as Digital I/O, I²C, USB 2.0, TTL UART, SPI, I²S
Software support: Preload customized Debian 11, Linux distributions and Android 12
Power: 12 V DC standard SATA power
Dimensions: 2.5-inch Pico-ITX form factor, 100 x 72 mm
Operating temperature: 0 to +80° C

The Blade 3 board is powered by a SATA power connector as a 12V input. It offers connectivity including HDMI 2.1 output at 8k60 and an HDMI 2.0 input at 4k60. There is also a general-purpose input/output (GPIO) header that offers I2C, USB 2.0, UART, SPI, I2S, and CAN connectivity for hardware expansion.

Mixtile Blade 3’s hardware, functioning together, gives a network speed of up to 20 Gb/s and a memory bandwidth of up to 136 GB/s. A cluster of Mixtile Blade 3, in a 19-inch 2U chassis, can provide up to 600 processor cores with 1320 GHz of computing power while using less than 1500 W of power. Meanwhile, on the software side, the board is designed to run both Linux and Android. It runs a hybrid Android and Linux distribution that operates Android 12 within a Linux container because of its plenty of driver support, making the software development process easy.

To learn more about the board, head over to the crowd supply page of Mixtile Blade 3

Sense is a Universal Sensor Board Featuring Multiple Applications

Posted on 30 May, 202230 May, 2022 by Saumitra Jagdale

Sense is a multipurpose sensor development board designed by Zack Seifert, an electronics enthusiast. He developed Sense to be a universal sensor board that would be a great addition to provide environmental data and it can be used in any electronics project. Sense is basically a wide variety of sensors all combined into one tiny, compact board. Sense incorporates three sensors, a real-time clock, and a micro SD card holder. With the help of these components, it provides its users with the ability to measure over 20 variables including temperature, air quality, humidity, altitude, RGB colors, sound, light, time, proximity, gestures, etc.

Sense is one of the most efficient devices as it provides its users with ease of development. Instead of connecting multiple different sensors separately we can simply connect the multipurpose Sense board and work seamlessly and efficiently. It is compatible with thousands of microcontrollers including Raspberry Pi, Arduino, and ESP32. With the help of its two onboard Qwiic connectors, there is no soldering or wires required in order to use the I2C sensors. Sense gives its users a full analysis of the environment and allows them to take action and control the environment.

Sense Hardware Components

BME688 (I2C): It measures temperature with ±1.0 °C accuracy, humidity with ±3% accuracy, barometric pressure with ±1 hPa absolute accuracy, and altitude with ±1 meter accuracy. It can detect gasses and alcohols such as Ethanol, Alcohol, and Carbon Monoxide, and perform air quality measurements.
APDS9960 (I2C): It detects simple gestures (left to right, right to left, up to down, down to up). It can also return amounts of red, blue, green, and clear light. Additionally, it can tell how close an object is to the sensor.
SPK0641HT4H (PDM): It has microphone pulse density and modulation output. To use this feature the processors must have a PDM (Pulse-density modulation) interface.
PCF8523 (I2C): It is a real-time clock and can provide year, month, day, weekday, hours, minutes, seconds, and 100th seconds based on a 32.768 kHz quartz crystal.
Micro SD Card Holder (SPI): It can log data onto the micro SD card through this feature. It also supports SPI and SDIO interfaces.

Getting Started with Sense

We can begin using Sense in three simple steps:

Step 1: Connect SENSE to a Microcontroller

The first and foremost step would be connecting the Sense board to the user’s desired Microcontroller. If the developers plan on using the I2C sensors, they can connect a Qwiic cable or wire up an I2C bus. If they plan on using the microphone, they can wire up an I2S bus. And lastly, if they are required to use the micro SD card holder, they can wire up an SPI or SDIO bus.

Step 2: Downloading the Code Libraries

The next step in working with Sense is to download and install the code libraries for the respective microcontroller that the developers are using. For example, the Arduino, Raspberry Pi and Circuit Python Libraries. For further help, the developers can refer to the detailed user guide and Github repositories.

Step 3: Upload Code and Start Creating

The last step includes uploading the respective code onto the microcontroller and you are ready to use Sense.

Sense can be used for a multitude of applications including an IoT weather station, home automation using a clap switch, motion-activated smart faucet, volume control using hand gestures, etc. To learn more about Sense, you can head over to the product page.

Intel’s Habana Labs designs next-gen AI processors – Gaudi2 and Greco

Posted on 29 May, 202230 May, 2022 by Abhishek Jadhav

Intel’s data center focused, Habana Labs, has announced its second-generation deep learning processors for training and inference deployment in the data center– Habana Gaudi 2 and Habana Greco. The new design is meant to reduce entry barriers for companies of all sizes leveraging high performance, high efficiency deep learning to compute choices for training AI models and deploying them in data centers.

These purpose-built AI deep learning processors use 7nm process technology and are manufactured on Habana’s high-efficiency architecture. The team demonstrated Habana Gaudi 2’s training performance for the ResNet-50 computer vision model and BERT natural language processing model to deliver twice the training throughput that of NVIDIA A100-80GB GPU. The shift from 16nm to 7nm on Habana Gaudi 2 brings a significant boost to its computing power, memory, and networking capability. The AI processor introduces an integrated media processing engine and also triples the in-package memory capacity from 32GB to 96GB of HBM2E at 2.45TB/s bandwidth.

“The launch of Habana’s new deep learning processors is a prime example of Intel executing its AI strategy to give customers a wide array of solution choices – from cloud to edge – addressing the growing number and complex nature of AI workloads. Gaudi2 can help Intel customers train increasingly large and complex deep learning workloads with speed and efficiency, and we’re anticipating the inference efficiencies that Greco will bring,” said Sandra Rivera, Intel executive vice president and general manager of the Datacenter and AI Group.

Another new entry to the AI inference market is the Habana Greco inference processor to provide performance and power efficiency on the 7nm process technology. The processor integrates media encoding and processing on-chip to support various media formats including HEVC, H.264, JPEG, and P-JPEG. The chipset will be made available in a new form factor– a single-slot PCIe Gen 4×8 form factor. The performance parameters show a significant reduction in power consumption from 200W TDP Goya to 75W TDP which in turn lowers the cost of operator for inference deployment.

The Habana Greco will be sent for mass production in Q1 2023 with customer sampling starting in the second half of this year, 2022. On the other hand, the Habana Gaudi 2 processor is now available for Habana customers. The manufacturer has also partnered with Supermicro to bring the Supermicro Gaudi 2 Training Server to market this year. Additionally, Habana provides customers with an HLS-Gaudi2 server that features 8x Gaudi2 processors and dual-socket Intel Xeon Ice Lake CPUs.

“We are excited to bring our next-generation AI deep learning server to market, featuring high-performance Gaudi2 accelerators enabling our customers to achieve faster time-to-train, efficient scaling with industry-standard Ethernet connectivity and improved TCO,” said Charles Liang, president and CEO of Supermicro. “We are committed to collaborating with Intel and Habana to deliver leadership AI solutions optimized for deep-learning in the cloud and data center.”

MediaTek releases its Genio 1200 AIoT Chip for designers and OEMs

Posted on 29 May, 202229 May, 2022 by Abhishek Jadhav

MediaTek is popular in designing chipsets for mobile phones and wearable devices, but over the past couple of years, the manufacturer has set its footprint in the AIoT market, serving customers across a variety of industries. On May 10, 2022, MediaTek unveiled another Genio AIoT platform with its newly designed Genio 1200 chipset, adding to the long list of Genio family of devices. As a full-stack AIoT platform, the chipset delivers high performance and comes with open platform SDKs.

The all-new Genio 1200 is a “premium” AIoT system-on-chip that provides “best-in-class” CPU, graphics, and AI performance while supporting the latest multimedia standards and multiple 4K displays. Manufactured using 6nm processing technology, the system-on-chip aims to be integrated into advanced smart home appliances, human-machine interfaces, 4K multi-display video and audio applications, industrial automation, and robotics.

As the industry enters the next era of innovation, MediaTek’s Genio platform delivers flexibility, scalability and development support brands need to cater to the latest market demands, said Jerry Yu, MediaTek Corporate Senior Vice President and General Manager of MediaTek’s Computing, Connectivity and Metaverse Business Group.

For edge AI applications, the Genio 1200 AIoT chip is built around a high-performance octa-core processor that can be clocked up to a frequency of 2.2GHz. The CPU comes in a combination of 4x Arm Cortex-A78 and 4x Arm Cortex-A55 processors.

The onboard graphics processor is from Arm Mali-G57 MC5 with an additional MediaTek AI processor and HiFi 4 Audio DSP. The CPU also supports five core graphics engine that is capable of advanced 3D graphics. Along with multiple 4K displays, the module can also receive and process ultra-high-definition display and camera inputs.

On the software side, the Genio 1200 AIoT chip operates on the latest Open Linux operating system. Also, there is a wide range of operating systems support such as Andriod, Yocto Linux, Ubuntu, and NeuroPilot SDK. When it comes to wireless connectivity, the hardware platform incorporates the option for an add-on module for MediaTek Wi-Fi 6 and Bluetooth 5.2 in combination with MediaTek 5G.

We look forward to seeing the new user experience brands bring to life with Genio 1200 and its powerful AI capabilities, support for 4K displays and advanced imaging features, Yu further added.

The MediaTek Genio 1200 AIoT chip will be available starting in the second half of 2022, but no details on the pricing.

BrainChip and Edge Impulse collaborate for better edge AI product offerings

Posted on 29 May, 202229 May, 2022 by Abhishek Jadhav

Two well-known edge AI solutions providers, BrainChip and Edge Impulse, have partnered to evolve an edge ecosystem that aims to accelerate AI/ML deployment in a variety of applications. The combination of BrainChip’s Akida technology with Edge Impulse’s platform will allow developers and enterprises to achieve improved machine learning performance with a fast and efficient development period. This collaboration is seen to provide faster time to market and attain a competitive advantage over other edge AI market leaders.

We recently covered BrainChip’s announcement of the availability of Mini PCIe boards that integrate the Akida technology-powered AKD1000 AIoT chipset. AKD1000 delivers unparalleled performance and efficiency with ultra-low latency to run multiple networks simultaneously. Designed for OEMs and car manufacturers, the edge AI processor is capable of early detection through real-time analysis of incoming sensor data. Leveraging real-time capabilities, the AKD1000 chip reduces existing problems with privacy, latency, and bandwidth constraints.

Partnering with Edge Impulse creates a unique market solution that brings their powerful and easy to use AI/ML application design platform unparalleled performance with BrainChip’s silicon-proven on-chip learning and ultra-low power IP, said Jerome Nadel, BrainChip CMO.

On the other hand, Edge Impulse has always been a go-to platform for any developer to build edge AI applications. The easy-to-use platform reduces the entry requirements and enables a newbie to get started with little knowledge. Recently, an article showed how image classification on ESP32-CAM was developed through Edge Impulse Studio and demonstrated the market capture for edge AI implementation. The software side for building AI applications has always been a tough task, but with Edge Impulse, the revolution in development platforms has taken place.

By integrating solutions, such as deploying BrainChip’s neuromorphic IP with our ML platform, developers and enterprise customers are empowered to build advanced machine learning solutions quickly and efficiently so that they are well-positioned as leaders within their respective markets, said Zach Shelby, CEO and co-founder at Edge Impulse.

The partnership marks a major breakthrough for the edge ecosystem, enabling customers to develop complex and advanced edge AI applications with ease. You can get started with Edge Impulse studio, and to get your hands on the $499 BrainChip PCIe board, the company has started to take pre-orders.

e-con Systems™ launches a Time of Flight (ToF) camera for accurate 3D depth measurement

Posted on 26 May, 2022 by mixos

Depth & RGB in single frame | 640×480 depth map | Frame rate – 30 fps | USB 3.1 Gen 1| Low light

e-con Systems™, a leading embedded camera company, launches DepthVista – a Time of Flight (ToF) camera that comes with a combination of a ToF depth sensor for depth measurement and the AR0234 color global shutter sensor from Onsemi for object identification.

DepthVista is a high-resolution depth camera that is capable of capturing 640×480 depth maps at a frame rate of 30 fps. This allows autonomous mobile robots and guided vehicles to perceive their environment and navigate safely. One of the notable features of DepthVista is that it does not require ambient illumination for optimal performance, making it suitable for systems operating in low light or even complete darkness. Furthermore, the depth calculation is performed in the camera itself, eliminating the need for it to be performed on the application side. This reduces computational load and provides a ready-to-use frame with the necessary depth information.

“Depth sensing is an important attribute for the next generation devices to see and understand the world in 3-dimensional perspective. Having depth data in addition to regular 2-dimensional RGB image throws up lot of opportunities in not only new age applications of robotic arms, autonomous mobile robots etc but also in traditional applications of patient/people monitoring or biometric authentication, where the additional depth attribute solves the hitherto unresolved problems and throws up lot of exciting new disruptive use cases. Having launched our first depth sensing camera in 2012, e-con has been committed with 3d cameras and DepthVista is our first iTOF( indirect Time-of-Flight) depth camera that offers 3d depth information, IR image and corresponding RGB image, all in a single compact form-factor. DepthVista will be the right camera for all applications requiring 3d sensing and our customers can benefit from our customization capabilities to customize the Depth/IR/RGB imaging from a single device based on their application requirements.” said Ashok babu, President at e-con Systems™.

Key features of DepthVista:

Depth and RGB stream in a single frame: Allow for object recognition as well as depth measurement in a single frame.
No need for ambient lighting: Suitable for systems that operate in low light or even total darkness
Depth calculation within camera: Eliminating the need to perform it on the application side, which reduces computational overhead.
Depth with high resolution: Capturing a 640×480 depth map at 30 fps allows autonomous vehicles and robots to accurately perceive their surroundings for navigation and object recognition.
Far mode and close-range mode: Offers a maximum and minimum range of 6 meters and 0.2 meter respectively.

Video

A combination of the features mentioned above makes DepthVista suitable for applications such as

Autonomous mobile robots like warehouse robots, and service robots
Robotic arms
Autonomous guided vehicles
People counting in Retail Analytics
Face recognition based anti-spoofing devices
Patient care/Patient monitoring

Availability

Customers interested in evaluating DepthVista – can purchase the product from e-con Systems’ online store. Please visit the DepthVista product page and click the buy now button to navigate to the webstore and purchase the product.