400GE network cybersecurity test is a first, says Keysight

Data centre network equipment manufacturers (NEM) and operators can use Keysight Technologies’ eight-port 400GE quad small form factor pluggable double density (QSFP-DD) network cybersecurity test platform to validate products and services support hyperscale data volumes, encryption demands and security challenges.

The APS-M8400 modular network cybersecurity test platform delivers 400GE density with an 8 x 400GE QSFP-DD test interface.

It has been introduced for data centre operators and service providers which are facing exponential growth in encrypted traffic volumes and security threats driven by increases in video streaming, cloud computing, AI, machine learning (ML) and IoT devices. The introduction of 400GE places critical infrastructure under even greater demand as growing volumes of encrypted traffic are being delivered at unprecedented speed, said Keysight. To meet these requirements, data centre NEMs and operators need tools that can validate that their products and services support hyperscale loads, without compromising security and usability.

The APS-M8400 delivers a modular, 400GE network security test platform that aggregates compute and FPGA resources to deliver hyperscale application and cybersecurity test and validation.

The ability to test 8 x 400GE QSFP-DD supports industry moves from 100GE to 400GE without the need for additional switches or infrastructure. It also offers a centralised management of up to 16 compute nodes to reduce the management learning curve and simplify system upgrades and maintenance.

It also offers flexible aggregation of compute and FPGA resources to optimise the performance and scalability requirements for any simulated workload, using one or multiple 400GE test interfaces.

The APS-M8400 can drive hyperscale application and cybersecurity test performance, including encrypted traffic loads, to effectively emulate the rigorous demands put upon data centre and service provider infrastructure. It can generate up to 3Tbit per second of Layer 4 to Layer 7 traffic, more than five billion concurrent connections, 2.4Tbits per second of transport layer security (TLS) traffic, and 2.4 million TLS connections per second.

It is designed to be scalable with a “pay-as-you-grow” structure, allowing users the flexibility to add capacity as requirements change and budgets allow.

http://www.keysight.com

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Matter portfolio from NXP includes secure tri-radio wireless MCU

Two microcontrollers (MCUs) added to NXP’s portfolio of end-to-end Matter solutions, the RW612 and the K32W148, combine edge processing capabilities with integrated security. The result, said NXP is to streamline development, simplify designs and reduce costs for Matter-enabled smart home devices.

The recently launched Matter standard aims to enable devices from different brands and ecosystems to seamlessly, reliably and securely communicate and thereby free consumers from ecosystem restraints. This allows consumers to select devices based on desired features rather than complex or confusing connectivity requirements. Both the multi-protocol supporting NXP K32W148 and the tri-radio RW612 have native support for Matter, make it easier for developers to integrate the functionality into smart home devices.

The RW612 is believed to be the industry’s first tri-radio wireless MCU with concurrent, multi-protocol support for Wi-Fi 6, Bluetooth Low Energy 5.3 and 802.15.4 and capable of supporting Thread or Zigbee. It is targeted for smart home devices such as thermostats, garage door openers, door locks, IP cameras, robotic vacuums, as well as smart appliances.

The K32W148 wireless MCU offers multi-protocol enablement across Thread, Bluetooth Low Energy 5.3, and Zigbee for devices such as smart plugs, smart lighting and low-power smart devices and sensors. It can add Thread and Zigbee support to home routers, hubs and bridges. Being multi-protocol, it reduces costs and simplifies antenna design with a single antenna.

The RW612 leverages an integrated tri-radio and advanced edge processing capabilities from the EdgeVerse i.MX RT crossover MCU family. It features an Arm Cortex-M33 MCU subsystem with TrustZone-M and fully integrated Wi-Fi 6, Bluetooth LE 5.3 and 802.15.4, capable of supporting Thread or Zigbee. It also includes on-chip SRAM and high performance configurable peripherals, including Ethernet, LCD controller and five FlexComm modules to support a variety of serial protocols. 

The level of integration reduces design complexity, bill of materials costs and end product size, added NXP. The RW612 is supported by the unified MCUXpresso development environment to reduce time to market.

NXP also offers the RW610, part of the same family of devices, which are ready to support new features such as Bluetooth LE Audio and Auracast broadcast audio for audio-focused applications, including portable audio devices and speakers, home theatre systems and gaming controllers.

The multi-protocol K32W148 wireless MCU has separated radio and security execution environments to free the main Arm Cortex-M33 core and memory for the customer’s application. The multi-protocol radio supports Matter, Thread, Bluetooth LE 5.3 and Zigbee. It also includes dual-PAN capability to simplify the co-existence of multiple IEEE 802.15.4 networks, such as Thread and Zigbee. 

It is also supported by the unified MCUXpresso development environment.

Both the K32W148 and the RW61x wireless MCUs are part of NXP’s EdgeLock Assurance program, which follows a secure-by-design approach, including protection against remote and local software attacks, as well as support for secure boot, secure debug and secure over-the-air firmware updates, with an immutable root-of-trust, hardware accelerated cryptography, and lifecycle management. 

The RW612, RW610 and K32W148 are currently sampling. 

http://www.nxp.com

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Low power LTE IoT modem includes terrestrial positioning support

The Qualcomm QCX216 LTE IoT modem is a Cat1.bis IoT-optimised LTE-modem which has integrated positioning support, claimed to enhance connectivity, location, and compute processing capabilities both on device and at the edge.

The Qualcomm QCX216 LTE IoT modem enables users to track assets and provide additional computing capabilities for IoT devices that need to process data. 

The Qualcomm QCX216 LTE IoT modem is a cost-optimized Cat.1bis modem that can work globally and seamlessly on existing LTE cellular infrastructure. The modem supports multi technology scanning capability used in conjunction with features supported by the Qualcomm Terrestrial Positioning Service to enable customers to develop low-power applications for a variety of industries. It will also enable OEMs to build affordable IoT devices in smaller form factor.

It delivers IoT-optimised speeds without excessively impacting battery life, said Qualcomm. Battery life is critical for expanding IoT applications such as smart utility meters, trackers, e-mobility, parking meters, home automation and security, and other location-based applications.

“The Qualcomm QCX216 LTE IoT modem being a highly integrated and low-power LTE Cat1.bis chip is going to pave the way for massive IoT device deployments and will help device manufacturers to easily migrate from 2G to 4G network at a lower total cost of manufacture,” said John Mathew, chief executive officer, Cavli Wireless. “4G availability being worldwide and no roaming restrictions is also going to boost the penetration for use cases that require global cellular access,” he added.

Qualcomm has a technology roadmap which allows it to efficiently scale the technologies that launched the mobile revolution – including advanced connectivity, high-performance, low-power compute, on-device intelligence and more – to the next generation of connected smart devices across industries. The company says it, and its family of Snapdragon platforms, contribute to enabling cloud-edge convergence, transforming industries and accelerating the digital economy.

https://www.qualcomm.com

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Nvidia adds pre-trained models to TAO toolkit to boost AI development  

The latest version of Nvidia’s TAO toolkit boosts developer productivity with the addition of AutoML capability, integration with third-party MLOPs (machine learning operations) services and new pre-trained vision AI models. The enterprise version now includes access to the full source code and model weights for pretrained models.

The toolkit is designed for efficient model training for vision and conversational AI. By simplifying complex AI models and deep learning frameworks, Nvidia said even developers without AI expertise can use the toolkit to produce AI models. Users can optimise model inference throughput with AI expertise or large training datasets using transfer learning to fine-tune Nvidia pre-trained models with developer’s own data. Models can be trained without the hassle of manually fine-tuning hundreds of parameters.

Other enhancements are access to virtual models from leading cloud providers and Kubernetes services like Amazon EKS or Azure AKS. It is also possible to simplify infrastructure management and scaling on cloud machine learning services such as Google Colab, Google Vertex AI, and Microsoft Azure Machine Learning.

Nvidia also announced new cloud integrations and third-party MLOps services, such as W&B and ClearML, to provide developers and enterprises with an optimised AI workflow. It is possible to build a new AI service or integrate into an existing one with REST APIs.

Developers can also create custom production-ready models optimised for specific environments and scenarios with TAO. Transformer-based pre-trained models (CitySemSegformer, Peoplenet Transformer) and retail-specific pre-trained models (RetailObjectDetection, RetailObjectRecognition, and ReIdentificationNet) can be accessed.

Nvidia highlighted a new feature which helps developers build object detection models without massive amounts of data. The use cases include detecting assembly line defects, translating particular phrases across languages, or managing city traffic.

http://www.nvidia.com

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