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Mounting base kit simplifies electronic prototyping tasks

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Digi-Key Electronics announced that it has expanded its product portfolio to include Phase Dock Inc.’s WorkBench project development kit. This distribution partnership is part of Digi-Key’s Marketplace initiative to broaden the product offerings now available for customers, making Digi-Key more of a one-stop-shop than ever before.

Phase Dock offers a unique project development kit series, the Phase Dock WorkBench, that helps engineers, makers, and students turbocharge prototyping and accelerate projects built with evaluation boards and breadboards. The kits improve productivity by speeding time to completion, greatly reducing work area clutter, and minimizing project setup time. The WorkBench can be used with many development boards, sensors, and actuators carried by Digi-Key.

The Phase Dock WorkBench eliminates many problems common to prototyping. It saves time previously lost constructing an ad hoc platform from cardboard, plywood, etc. It provides portability and protection to fragile hardware that otherwise might be loosely wired together on the desktop. And it allows engineers and hobbyists to dive into the heart of their projects more quickly, easily reconfigure working prototypes, and maintain an orderly work area at the same time.

For more information about Phase Dock and to order from their product portfolio, please visit the Digi-Key website.

Graphic controller ICs optimized for large-format HMIs

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Bridgetek has made further announcements relating to its multi-award-winning embedded video engine (EVE) platform. The BT817 and BT818 represent the company’s fourth generation of EVE products and follow the already established mantra of helping those with little or no relevant prior experience to build advanced HMIs with high degrees of differentiation.

These new functionally-superior graphic controller ICs are intended for use in retail, digital signage, and office management systems, as well as public information units, vending machines, domestic appliances, store/mall direction finding systems, training/educational equipment, and interactive exhibits. They are able to address the requirements of HMIs rendered on much larger format displays and offer greater resolution levels too.

Suitable for use with 1Mpixel displays, the BT817 and BT818 support resolution numerous options – such as 1920×480, 1440×540, 1280×800, 1024×600, 800×600, 800×480, 480×272, etc. Each has a 1Mbyte embedded graphics RAM, and this can be supplemented by attaching an external NOR flash memory through the QSPI interface. Thanks to the object-oriented approach pioneered by EVE, there is no need for a frame buffer to be incorporated into the HMI system. In addition, by leveraging adaptive scalable texture compression (ASTC), it is possible to lower the system’s graphics processing overhead. This also means better use can be made of the available data storage capacity, so that bigger items can be accessed and more compelling HMI content delivered.

The BT818 is optimized for use with 4-wire resistive touchscreens, while the BT817 has been designed to accompany capacitive touchscreens (with multi-touch functionality allowing detection of up to 5 different touchpoints). Touchpoint movement can be accurately tracked and there is the scope to assign 255 different touch tags. The ability to adjust both the horizontal and vertical sync timing means that a much wider array of different display units can be accommodated. Power mode control ensures that electricity consumption is reigned in. Other notable features include video playback, enhanced sketch processing, and a built-in sound synthesizer.

The Bridgetek BT817 and BT818 are supplied in compact 9mm x 9mm 64-pin VQFN packages. An extended -40°C to 85°C operational temperature range allows them to be deployed within industrial environments.

4U GPU system delivers 6x AI training performance, 7x inference workload capacity

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Super Micro Computer, Inc., announced the doubling of GPU capabilities with a new 4U server supporting eight NVIDIA HGX A100 GPUs. Supermicro offers the industry’s broadest portfolio of GPU systems spanning 1U, 2U, 4U, and 10U GPU servers and SuperBlade servers over a wide range of customizable configurations.

Supermicro now offers the industry’s widest and deepest selection of GPU systems with the new NVIDIA HGX A100 8-GPU server to power applications from the Edge to the cloud.  The entire portfolio includes 1U, 2U, 4U, and 10U rackmount GPU systems; Ultra, BigTwin, and embedded solutions powered by both AMD EPYC and Intel  Xeon processors with Intel Deep Learning Boost technology.

Leveraging Supermicro’s advanced thermal design, including custom heatsinks and optional liquid cooling, the latest high-density 2U and 4U servers feature NVIDIA HGX A100 4-GPU 8-GPU baseboards, along with a new 4U server supporting eight NVIDIA A100 PCI-E GPUs. The Supermicro’s Advanced I/O Module (AIOM) form factor further enhances networking communication with high flexibility. The AIOM can be coupled with the latest high-speed, low latency PCI-E 4.0 storage and networking devices that support NVIDIA GPUDirect RDMA and GPUDirect Storage with NVME over Fabrics (NVMe-oF) on NVIDIA Mellanox InfiniBand that feeds the expandable multi-GPU system with a continuous stream of data flow without bottlenecks. In addition, Supermicro’s Titanium Level power supplies keep the system green to realize even greater cost savings with the industry’s highest efficiency rating of 96%, while allowing redundant support for the GPUs.

This 2U system features the NVIDIA HGX A100 4-GPU baseboard with Supermicro’s advanced thermal heatsink design to maintain the optimum system temperature under full load, all in a compact form factor. The system enables high GPU peer-to-peer communication via NVIDIA NVLink, up to 8TB of DDR4 3200Mhz system memory, five PCI-E 4.0 I/O slots supporting GPUDirect RDMA as well as allowing four hot-swappable NVMe with GPUDirect Storage capability.

The new 4U GPU system features the NVIDIA HGX A100 8-GPU baseboard, up to six NVMe U.2 and two NVMe M.2, ten PCI-E 4.0 x16 slots, with  Supermicro’s unique AIOM support invigorating the 8-GPU communication and data flow between systems through the latest technology stacks such as GPUDirect RDMA, GPUDirect Storage, and NVMe-oF on InfiniBand. The system uses NVIDIA NVLink and NVSwitch technology. It is ideal for large-scale deep learning training, neural network model applications for research or national laboratories, supercomputing clusters, and HPC cloud services.

The industry’s highest density GPU blade server can support up to 20 nodes and 40 GPUs with two single-width GPUs per node, or one NVIDIA Tensor Core A100 PCI-E GPU per node in Supermicro’s 8U SuperBlade enclosure. The 20 NVIDIA A100 GPUs in 8U elevates the density of computing power in a smaller footprint allowing customers to save on TCO. To support the GPU-optimized configuration and sustain the top performance and throughput needed for demanding AI applications, the SuperBlade provides a 100% non-blocking HDR 200Gb/s InfiniBand networking infrastructure to accelerate deep learning and enable real-time analysis and decision making.  High density, reliability, and upgradeability make the SuperBlade a perfect building block for enterprise applications to deliver AI-powered services.

Supermicro continues its support of NVIDIA’s advanced GPUs in various form factors, optimized for customers’ unique use case scenarios and requirements. The 1U GPU systems contain up to four NVIDIA GPUs with NVLink, including NEBS Level 3 certified, 5G/Edge-ready SYS- 1029GQ. Supermicro’s 2U GPU systems, such as SYS- 2029GP-TR, can support up to six NVIDIA V100 GPUs with dual PCI-E Root complex capability in one system. And finally, the 10U GPU servers, such as SYS- 9029GP-TNVRT, supports 16 V100 SXM3 GPU expansions with to Dual Intel Xeon Scalable processors with built-in AI acceleration.

The flexible range of solutions powered by NVIDIA GPUs and GPU software from the NVIDIA NGC ecosystem provides the right building blocks for diverse tasks for organizations addressing various verticals — from AI inferencing on developed models to HPC to high-end training.

Rugged GPGPU AI supercomputer handles harsh conditions in mobile, remote, military, autonomous apps

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Aitech Systems has released an upgraded, qualified version of its high performance, compact A178. Designed for intense data processing in extreme environments, the rugged GPGPU AI supercomputer reliably operates in the harsh conditions found throughout mobile, remote, military, and autonomous platforms. The A178 system is ideal for applications such as training simulation, situational awareness, AI computing, image and video processing, moving maps, and much more.

Already one of the smallest of Aitech’s extensive AI SFF systems, the new A178 packs even more performance into a compact, rugged form factor. It uses the NVIDIA Jetson AGX Xavier System-on-Module that features the Volta GPU with 512 CUDA cores and 64 Tensor cores to reach 32 TOPS INT8 and 11 TFLOPS FP16.

The upgrades to the A178 were designed to help meet the demand for standalone, compact, GPGPU-based small form factor (SFF) systems that are both rugged and SWaP-C-optimized. The low power unit offers a high level of energy efficiency while providing all the power necessary for AI-based local processing right where it’s needed, next to the sensors.

The advanced computation abilities of the new system include two dedicated NVDLA (NVIDIA Deep-Learning Accelerator) engines that provide an interface for deep learning applications, making it ideally suited for distributed systems. The system can accommodate up to three expansion modules, such as an HD-SDI frame grabber, composite frame grabber or NVMe SSD. A variety of expansion modules are available upon request.

Four high definition HD-SDI inputs and eight composite inputs handle multiple streams of video and data simultaneously at full frame rates. Interfaces include Gigabit and 10GB Ethernet, DisplayPort output handling 4K resolution, USB 3.0 & 2.0 as well as DVI/HDMI output, UART serial, and CANbus, among others.

Silicon design kit optimized for high-bandwidth memory/PCIe/ethernet connectivity

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Synopsys, Inc. announced its collaboration with GLOBALFOUNDRIES to develop a broad portfolio of DesignWare IP for GF’s 12LP+ FinFET solution, including USB4/3.2/DPTX/3.0/2.0, PCIe 5.0/4.0/2.1, die-to-die HBI and 112G USR/XSR, 112G Ethernet, DDR5/4, LPDDR5/4/4X, MIPI M-PHY, Analog-to-Digital Converter, and one-time programmable (OTP) non-volatile memory (NVM) IP. The DesignWare IP is optimized to meet the high-bandwidth memory throughput and reliable, high-performance connectivity demands of cloud computing and AI chips implemented on GF’s 12LP+ solution. This recent collaboration marks another significant milestone of the continuous, successful collaboration between the two companies.

GF’s most advanced FinFET solution, 12LP+ builds upon GF’s established 14nm/12LP platform, of which GF has shipped more than one million wafers. Driving the enhanced performance of 12LP+ are features including a 20-percent SoC-level logic performance boost over 12LP, and a 10-percent improvement in logic area scaling.

Availability

About DesignWare IP
Synopsys is a leading provider of high-quality, silicon-proven IP solutions for SoC designs. The broad DesignWare IP portfolio includes logic libraries, embedded memories, embedded test, analog IP, wired and wireless interface IP, security IP, embedded processors, and subsystems. To accelerate prototyping, software development, and integration of IP into SoCs, Synopsys’ IP Accelerated initiative offers IP prototyping kits, IP software development kits, and IP subsystems. Synopsys’ extensive investment in IP quality, comprehensive technical support, and robust IP development methodology enables designers to reduce integration risk and accelerate time-to-market.

Free ebook covers Raspberry Pi essentials

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Raspberry Pi essentialsIn celebration of Pi Day, the element14 community has published a new eBook: “Essential Raspberry Pi Tips”.  In recent years, the Raspberry Pi has transitioned from a tool for students and hobbyists to a viable option for many types of engineering project.

The element14 community’s eBook seeks to support users in their search for perfection,  and help them overcome challenges they might face as they get started, and develop projects with the Raspberry Pi focussing on topics such as storage, power supplies, and the humble LED.

Cabe Atwell, element14 Contributor, who authored the eBook says: “If you’re considering the Raspberry Pi because you are curious about electronics and coding, or even if you are a practicing engineer, just go for it! The size of the community and the sheer number of publically available forums, tutorials, and projects means that you will be in good company as you explore and experiment.”

element14 community members can download the full eBook for free at https://www.element14.com/community/community/publications/ebooks

Training courses teach functional safety/security standards for critical software apps

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LDRA tool suite Training Course LDRA  has announced that the company is bringing its popular three-day software-development public training courses to multiple US locations. The LDRA tool suite Training Course is scheduled for June 18–20 in San Jose, Calif., and June 25-27 in Huntsville, Ala. Additional locations are being added on-demand, with the next courses planned for Boston, Mass., and Dallas, Texas. The training courses support the requirements of software development and verification teams by teaching best practices and use of the LDRA tool suite for delivering safe and secure applications under functional safety and security standards in critical software markets.

Through the company’s growing education portfolio, LDRA aims to provide software, quality, and test engineers with a thorough understanding of advanced testing methodologies and the requirements and constraints associated with developing applications for compliance with industry-specific standards such as DO-178C and DO-278 in avionics, ISO 26262 in automotive, IEC 61508 in industrial safety, and IEC 62304 in medical devices.

“LDRA supports the enforcement of rigorous software standards that ensure the safety and security of software-based electronics systems,” said Ian Hennell, Operations Director, LDRA. “We are offering these three-day intensive, hands-on training courses to help companies and their project teams throughout the entire software development cycle. Attendees will learn to effectively use the LDRA tool suite to design high-performing, critical systems that are safe, secure, and threat resistant.”

The LDRA tool suite Training Course includes instruction on:

  • Code Review – Apply static analysis to source code, e.g., MISRA C/C++ and Custom Coding Rules.
  • Quality Review – Analyze source code complexity, testability, maintainability, and clarity.
  • Design Review – Analyze as-built designs using control and data flow analysis.
  • Test Verification – Perform dynamic analysis and measure code coverage in accordance with industry-specific standards compliance (e.g., DO-178C, ISO 26262, IEC 61508, and IEC 62304).
  • Unit Testing – Create and run unit tests, regress tests; automate stub creation; cope with code changes; run a white box test; maintain and document unit tests.
  • Deployment on host and target systems

For more information and to register for an upcoming LDRA tool suite Training Course, visit: https://ldra.com/events-training/  

AI stack upgrade provides 10x boost in performance with <1 W power consumption

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Lattice Semiconductor Corporation announced major performance and design flow enhancements for its award-winning Lattice sensAI solutions stack. The Lattice sensAI stack provides a comprehensive hardware and software solution for implementing low power (1mW-1W), always-on artificial intelligence (AI) functionality in smart devices operating at the edge. Additionally, enhancements to the stack’s memory schemes address a key bottleneck for AI designs.

senseAIIHS forecasts 40 billion devices will be operating at the network Edge by 2025. For reasons including latency, network bandwidth limitations, and data privacy, OEMs designing always-on Edge devices want to minimize sending data to the Cloud for analytics. Lattice sensAI enables such OEMs to seamlessly update their existing designs with low power AI inferencing optimized for their application requirements. Incorporating such local intelligence also lowers expenses related to Cloud-based analytics by only sending relevant data for further processing.

“At Pixcellence, our expertise is in developing image processing and computer vision solutions with industry-first features like color night vision. Interest in the IoT is fueling demand for smart cameras that support AI applications like presence detection or facial recognition,” said Seton P. Kasmir, CEO, Pixcellence, Inc. “However, smart cameras have strict power consumption and cost requirements that make it a challenge to use off-the-shelf ASSPs. The Lattice sensAI solutions stack lets us easily add low power, flexible AI inference support to our existing and new camera designs, and get our value-added products to market faster.”

“There is a desire to enable AI-functionality in always-on applications involving presence detection and object counting in smart home control, industrial, and retail store cameras, for instance, that are also moving AI to the edge” says Boppana, Sr. Director of Segment & Solutions Marketing, at Lattice Semiconductor, “and because we have always focused on low power as a company, our FPGAs are also a good fit for these applications where every milliwatt counts, small form-factors are a must, and users require the flexibility to easily adapt to the evolving AI space.”

New enhancements to the Lattice sensAI solution stack include:

  • 10x performance boost over previous version – driven by an updated CNN IP and neural network compiler with features like 8-bit activation quantization, smart layer merging and a dual-DSP engine
  • Seamless user experience – accelerates the design cycle with several new features including:
    • Expanding neural network and ML frameworks support including Keras
    • Support for quantization and fraction setting schemes for neural network training eliminates iterative post-processing
    • Simple neural network debugging via USB
    • New customizable reference designs accelerate time to market for popular use cases like object counting and presence detection
  • A growing design service partner ecosystem including full product design capability from partners such as Pixcellence makes it easier for customers to get to market faster.

Customers with prior experience in machine learning and AI can access the customizable reference designs that allow them to change the training data to optimize their applications without worrying about which neural network to choose.

Free LoRaWAN educational modules accelerate IoT applications

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LoRaWAN educational modulesSemtech Corporation has announced the open registration of the LoRaWAN Academy for everyone, from large enterprises to individual developers. The LoRaWAN Academy provides comprehensive, free educational modules for students, engineers, developers, and enterprises to develop Internet of Things applications using LoRa-based technologies.

“Developers are the most important part of any modern technology platform, and the LoRaWAN Academy is there to help them get up to speed on one of the fastest growing IoT-enabling technologies out there today, Semtech’s LoRa devices and wireless radio frequency technology (LoRa Technology). The LoRaWAN Academy will enable developers to get their LoRa-based solutions to market faster as well as simplify development,” said Steven Hegenderfer, Senior Director of the Developer Ecosystem in Semtech’s Wireless Sensing and Products Group. “We are working with the LoRaWAN-based ecosystem to develop and drive material that is beneficial to the community. Providing completely free modules focused on building LoRa-based applications gives students, engineers, developers, and enterprises the jump-start they need to build robust, innovative IoT applications.”

The LoRaWAN Academy was first launched in late 2017 and targeted to universities. Since its initial inception, several universities from around the world implemented LoRaWAN Academy curriculum to prepare students for the IoT job market by training their students on developing LoRa-based solutions and the open LoRaWAN™ protocol. The program will now be available to anyone who is interested in building LoRa-based applications. The LoRaWAN Academy includes 10 modules of self-paced online classes that includes video lectures, supplemental reading materials and hands-on assignments.

To learn more about the LoRaWAN Academy, visit Semtech’s LoRa Developer Portal.

New study benchmarks Zigbee, Thread, and Bluetooth network protocols

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Zigbee, Thread, and Bluetooth Silicon Labs has released the industry’s first comprehensive network performance results based on large-scale, multicast testing of Zigbee, Thread , nd Bluetooth mesh software. Each mesh networking protocol presents unique characteristics and advantages, depending on the use case and end application. All testing was conducted at Silicon Labs’ Boston design center using the company’s Wireless Gecko SoC platform to eliminate the device itself as a variable in testing the mesh protocols.

 “Understanding the inner workings of mesh technologies helps developers assess how these network protocols perform in the key areas of power consumption, throughput, security and large network scalability,” said Daniel Cooley, Senior Vice President and General Manager of Silicon Labs’ IoT Products. “Zigbee, Thread and Bluetooth mesh are designed differently from the ground up, and we’re sharing our performance benchmark results to help developers select the right mesh connectivity option for their IoT designs.”

 The mesh network benchmark results can be used by system designers to define expected behavior for Zigbee, Thread and Bluetooth mesh in the 2.4 GHz frequency band. With the growing number of mesh networks available for IoT applications, it is important for developers to understand how these networks differ in terms of use cases and expected performance. The testing focused on device behavior and impact on battery life, network throughput and latency, and the impact of network size on scalability and reliability.

 Silicon Labs’ mesh network performance results are available as a series of application notes that define the methodology for performing the benchmark tests, enabling developers to replicate and run similar tests. These results provide guidance on mesh network design best practices and principles as well as expected field performance results. With 15 years of experience in mesh networking and more than 150 million deployed nodes, Silicon Labs is at the forefront of bringing advanced, multiprotocol wireless mesh technology to market.

 Silicon Labs’ mesh networking performance test results are available free of charge to developers at www.silabs.com/mesh-performance.