i.MX 93 applications processor enhances security at the edge, says NXP

Believed to be the industry’s first implementation of the Arm Ethos-U65 microNPU, the i.MX 93 applications processors are the first in NXP’s i.MX 9 series.

The applications processors are designed for automotive, smart home, smart building and smart factory applications, which use edge machine learning to anticipate user needs. They combine the Arm Ethos-U65 microNPU with a high level of security and integration to deliver efficient, fast, secure machine learning at the edge, for example in voice-assisted smart home and building systems. They can also be used in low power industrial gateways and automotive driver monitoring systems. 

The i.MX 93 family has a heterogenous multi-core architecture, including up to two 1.7GHz Arm Cortex-A55 applications processors and a real-time Cortex-M33 microcontroller subsystem with access to all SoC peripherals, including the 256 MACs / cycles Arm Ethos-U65 microNPU. This architecture delivers power-efficient machine learning across a variety of applications, including compact, battery-powered IoT devices, says NXP. 

The i.MX 93 family supports a variety of industrial and automotive connectivity interface protocols, in addition to broad multi-media interfaces. This also reduces the need for external hardware components and additional design work, to reduce the time to market as well as overall systems costs. 

Ron Martino, executive vice president and general manager, ege processing for NXP Semiconductors, believes: “The highly integrated i.MX 93 applications processors will help open an entirely new range of use cases at the edge, where you need to have that close tie-in to the sensor data to make fast decisions. This will enable a new generation of secured, efficient, intelligent devices across IoT, industrial IoT and automotive applications.”

NXP’s EdgeLock secure enclave is a standard on-die feature across the i.MX 9 series. It is a pre-configured, self-managed and autonomous security subsystem. It is particularly useful for developers without deep security expertise.

“We’re making it easier for developers to create, connect, and maintain innovative IoT devices by providing a comprehensive platform actively supported by the scale and expertise of Microsoft software, cloud and security experts,” said Halina McMaster, partner group program manager, Microsoft Azure Sphere. “Together with NXP, we are delivering a variety of Microsoft Azure Sphere-certified edge processors that provide a secured environment for customer applications, critical over-the-air update infrastructure, and more than 10 years of ongoing security improvements for every Azure Sphere chip,” she said. 

i.MX 93-CS processors with Azure Sphere are built with Microsoft Pluton enabled on the EdgeLock secure enclave. Pluton on EdgeLock secure enclave is the dependable hardware root of trust which is built into the silicon and enables the Azure Sphere security stack.

Machine learning application development on the i.MX 93 family will be enabled by the eIQ software development environment, including the eIQ Toolkit workflow tools, the GUI-based eIQ Portal development environment and eIQ inference engine options that will include the Arm Ethos-U65 microNPU as an inference target. 

The i.MX 93 applications processors implement NXP’s innovative Energy Flex architecture, enabling developers to optimize energy usage for each operating mode to create portable devices with longer battery life. 

http://www.nxp.com

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Bluefield-3 DPU accelerates virtual clouds, says Nvidia

With 400Gb/s Ethernet or NDR 400Gbits per second InfiniBand network connectivity, BlueField-3 DPU (data processing unit) offloads, accelerates, and isolates software-defined networking, storage, security, and management functions to improve data centre performance, efficiency and security, says Nvidia. 

The third-generation Bluefield infrastructure on a chip enables organisations to build software-defined, hardware-accelerated IT infrastructures from cloud to core data centre to edge, says the company. In addition to powerful computing and a range of programmable acceleration engines in the I/O path, BlueField-3 is addresses the infrastructure needs of the most demanding applications and software backwards compatibility through the Nvidia DOCA software framework. 

BlueField-3 DPUs transform traditional computing environments into secure and accelerated virtual private clouds, allowing organisations to run application workloads in secure, multi-tenant environments. It decouples data centre infrastructure from business applications and is claimed to deliver optimal bare-metal performance and native support for multi-node tenant isolation. 

BlueField-3 DPU features video streaming Storage NVMe over Fabrics (NVMe-oF), NVMe/ TCP, hyper converged infrastructure (HCI), encryption, data integrity, data de-duplication, decompression, erasure coding/RAID Security Distributed firewall, IDS/ IPS, root of trust and microsegmentation.

The portfolio includes one, two or four ports with up to 400Gbits per second connectivity, 16Gbyte on-board DDR5 memory. There is also a 1GbE out-of-band management port,  single port InfiniBand or dual ports of NDR200 / HDR (200Gbits per second), 32 lanes of PCIe Gen 5.0 and non-transparent bridging.

The ample memory consists of up to 16 Armv8.2+ A78 Hercules cores (64-bit), 8Mbyte L2 cache and 16Mbyte LLC system cache. There is also a programmable datapath accelerator, DDR DIMM support, including dual DDR5 5600Mtransfers per second DRAM controllers and ECC protection. 

For security, there is secure boot with public key accelerator (PKA) root-of-trust, secure firmware update and Flash encryption, MACsec / IPsec / TLS data-in-motion encryption, an AES-GCM 128 / 256-bit key, AES-XTS 256 / 512-bit data-at-rest encryption, connection tracking for stateful firewall and true random number generator (TRNG) storage.

 https://www.nvidia.com/

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SoM powers AI-enabled cameras

A system on module (SoM) by Smart Wireless Computing, the Inforce 6403, is based on Qualcomm’s QCS610. It enables advanced visual computing for AI-enabled surveillance camera and edge appliances, connected body cameras, smart displays, and other IoT wireless network edge devices, says the company. 

Engineers can use the Inforce 6403 SoM to bring on-device AI and machine learning (ML) to cameras and displays, while enabling multiple connectivity options for critical data transfer. 

It supports 4K UltraHD (HEVC) video capture and playback to enable video analytics applications integrated into smart cameras, such as face detection and object tracking. High-bandwidth connectivity options include Ethernet RGMIII, 802.11nac Wi-Fi, Bluetooth 5.x, USB-C, and LTE Cat 4 via a carrier board.

The compact LGA package measures just 43 x 32.5mm (1.69 x 1.28 inches), allowing it to integrate into camera housings and systems, particularly in applications where a soldered connection is required for a rugged end-product.

The module comes with a software package that includes integration with Google Firebase and a sample application to upload or stream videos in real time. Google Firebase is a unified backend-as-a-service (BaaS) platform for mobile and web developers that integrates with other Google services.

The Qualcomm QCS610 SoC integrates a Qualcomm Kryo 460 CPU with independent efficiency and power clusters. There are also dual 14-bit Qualcomm Spectra 230 image signal processors which support up to 24Mpixels for simultaneous concurrent cameras capturing sharp images.

The Qualcomm Adreno 612 GPU provides efficient rendering of advanced 3D graphics.

The SoC also leverages Qualcomm Hexagon Vector eXtensions (HVX) on Hexagon 685 DSP enable accelerated machine learning through deep neural network models and with advanced Qualcomm neural processing engine SDK support and TensorFlow Lite.

A secure processing unit enables secure boot, DRM and content protection for a secure environment for the camera system.

The Inforce 6403 SoM incorporates enhanced EMI shielding for RF noise protection, while also improving heat dissipation to improve performance.

A reference design based on the SoM is available.

https://www.inforcecomputing.com

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NFC Type 2 tag IC has permanent write locks and configurable kill mode

Consumer engagement, production information and brand protection are offered with the ST25TN512 and ST25TN01K NFC Forum Type 2 tag ICs by STMicroelectronics. They can also be used for access control.

The ST25TN512 and ST25TN01K NFC tag ICs support multiple user-protection and privacy mechanisms including a 7-bit unique chip-identifier code, TruST25 digital signature, NFC Forum T2T permanent write locks at block level, and a configurable kill mode that permanently deactivates the tag.

The two ICs are certified to NFC Forum Type 2 specifications and leverage ISO 14443 standards. They can be used with NFC-compatible mobiles or a dedicated short-range reader. The embedded device memory includes up to 208 bytes (1664 bits) dedicated to user content.

There is also support for messages in NFC data exchange format (NDEF) which triggers native actions on a smartphone without needing a dedicated app, such as launching a web browser or starting Bluetooth pairing. Augmented NDEF (ANDEF) enables reading dynamic information such as custom messages and unique tap codes without explicitly updating the EEPROM.

The ST25TN512 and ST25TN01K are produced by a new in-house manufacturing process. Both NFC tag ICs contain an internal tuning capacitance of 50pF, which allows plug-and-play integration by inlay manufacturers. The tags harvest energy from the 13.56MHz RF transmitter field and require only an antenna to complete the design.

They also have a long data retention and operate over a wide temperature range of -40 to +85 degrees C. The ICs can be supplied in sawn and bumped wafer format or housed in a DFN5 package.

Both the ST25TN512 and ST25TN01K are available in volume production.

http://www.st.com

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