Intel introduces socketed SoCs for edge and AI

12th gen Intel Core SoC processors have been announced. Intel announced the line-up of purpose built edge processors which can be used to enhance graphics, AI for the IoT edge.

According to Intel, the purpose-built edge SoC processors mark an industry first: a socketed SoC for high performance integrated graphics and media processing for visual compute workloads. They have a compact footprint and a wide operating thermal design power (TDP) for small form factor, fanless designs.

The SoC has been developed in response to the increased volume of data created at the edge which needs to be processed and analysed. Digital transformation at the edge requires increased processing power and AI inference performance to future-proof AI workloads, said the company. These 12th gen Intel Core SoC processors for IoT edge feature manageability capabilities including Intel vPro options for remote control and manageability which is required for managing and servicing systems deployed at the IoT edge.

The 12th gen Intel Core SoC processors deliver up to four times faster graphics, as measured by 3DMark, the benchmarking tool, and up to 6.6 times faster GPU image classification inference performance compared with 10th gen Intel Core desktop processors in a 12 to 65W design. 

The 12th gen Intel Core SoC processors for IOT edge include Intel Thread Director, which intelligently directs the operating system to assign the right workload to the right core. With up to 14 cores and 20 threads, the SoC processors also reach up to 1.32 times faster single-thread performance and up to 1.27 times faster multi-thread performance compared with 10th Gen Intel Core desktop processors, said Intel.

The SoC processors also support AI for inferencing and machine vision, with up to 96 graphics execution units for a high degree of parallelisation in AI workloads. AI acceleration on the CPU via Intel Deep Learning Boost provides additional inferencing. The processors also support Intel Distribution of OpenVINO toolkit optimisations and cross-architecture inferencing. The integrated graphics, enhanced visual compute, and AI capabilities may realise imaging and pattern recognition for healthcare or create new opportunities for point of sale retail, said Jeni Panhorst, vice president Data Platforms and general manager of the Network & Edge Platforms division.

Other market sectors likely to expand remote control and manageability of systems at the edge include banking, hospitality and education to respond to changing supply and demand. For industrial manufacturing, they can enhance industrial PCs, edge servers, advanced controllers, machine vision systems and virtualised control platforms, while in healthcare the processors can deliver enhanced ultrasound imaging, medical carts, endoscopy and clinical devices at the edge.

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Intel engineers Flex series GPUs for the intelligent visual cloud

The data centre (GPU) graphics processing codenamed Arctic Sound-M has been unveiled as the Flex series. The Flex series GPUs are designed to meet the requirements for intelligent visual cloud workloads, said Intel. The Flex 170 is designed for maximum peak performance while the Flex 140 is for maximum density.

The Flex series GPU are capable of processing up to 68 simultaneous cloud gaming streams and handle workloads without having to use separate, discrete solutions or rely on siloes or proprietary environments, said the company. This helps lower and optimise the total cost of ownership for diverse cloud workloads like media delivery, cloud gaming, AI, metaverse and other emerging visual cloud use cases.

“We are in the midst of a pixel explosion driven by more consumers, more applications and higher resolutions,” explained Jeff McVeigh, Intel vice president and general manager of the Super Compute Group, Intel. “Today’s data centre infrastructure is under intense pressure to compute, encode, decode, move, store and display visual information”.

The Flex series GPUs have what is claimed to be the first hardware-based AV1 encoder in a data centre GPU to provide five times the media transcode throughput performance and two times the decode throughput performance at half the power of the Nvidia A10 in the case of the Intel Flex series 140 GPU, for example. According to Intel, the series also delivers more than 30 per cent bandwidth improvement to save on the total cost of ownership and has broad support for popular media tools, APIs, frameworks and the latest codecs, including HEVC, AVC and VP9.

The GPUs are powered by Intel’s Xe-HPG architecture and can provide scaling of AI inference workloads from media analytics to smart cities to medical imaging between CPUs and GPUs without “locking developers into proprietary software”.

The video processing demands of video conferencing, streaming, and social media have transformed the compute resource requirements of the data centre. The increased media processing, media delivery, AI visual inference, cloud gaming and desktop virtualisation has presented a challenge for an industry largely dependent on proprietary, licensed coding models, like CUDA for GPU programming, said Intel.

The Flex series GPU software stack includes support for oneAPI and OpenVINO. Developers can use Intel’s oneAPI tools to deliver accelerated applications and services, including the Intel oneAPI Video Processing Library (oneVPL) and Intel VTune Profiler, for example. The open alternative to proprietary language lock-in enables the performance of the hardware and has a set of tools that complement existing languages and parallel models. This allows users to develop open, portable code that will take maximum advantage of various combinations across Intel CPUs and GPUs. It also means developers are not tied to proprietary programming models, which can be financially or technically restrictive, said Intel.

The Flex series GPU media architecture is powered by up to four Xe media engines, for streaming density and to deliver up to 36 streams 1080p60 transcode throughput per card. It is also capable of delivering eight streams 4K60 transcode throughput per card.

When scaled to 10 cards in a 4U server configuration, it can support up to 360 streams HEVC-HEVC 1080p60 transcode throughput.

Leveraging the Intel Deep Link Hyper Encode feature, the GPU Flex series 140 with two devices on a single card can meet the industry’s one-second delay requirement while providing 8K60 real-time transcode, reported Intel. This capability is available for AV1 and HEVC HDR formats.

To meet the growth in Android cloud gaming, the GPUs are validated on nearly 90 of the most popular Google Play Android game titles. A single Flex series 170 GPU can achieve up to 68 streams of 720p30 while a single Flex series 140 GPU can achieve up to 46 streams of 720p30 (measured on select game titles).

When scaled with six Flex Series 140 GPU cards, it can achieve up to 216 streams of 720p30.

Systems featuring Flex series GPUs will be available from providers including Dell Technologies, HPE, H3C, Inspur, Lenovo and Supermicro. Solutions with the Flex series GPU will ramp over the coming months, starting with media delivery and Android cloud gaming workloads, followed by Windows cloud gaming, AI and VDI workloads.

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Mouser adds Texas Instruments sensor evaluation module

Described as easy to use, the IWR6843LEVM is a 60GHz mmWave sensor evaluation platform for the IWR6843 with an FR4-based antenna. Available from distributor, Mouser Electronics, the IWR6843LEVM may be used to evaluate both the IWR6843 and IWR6443 sensors. 

This evaluation module enables access to point cloud data and power over USB interfaces. The IWR6843LEVM supports direct connectivity to the MMWAVEICBOOST and DCA1000EVM development kits. IWR6843LEVM contains everything required to develop software for on-chip C67x digital signal processor (DSP) cores, hardware accelerators (HWAs), and low-power Arm Cortex-R4F controllers, confirmed Mouser.

Texas Instruments’ IWR6832LEVM is supported by mmWave tools and software, namely mmWave studio (MMWAVE-STUDIO) and the mmWave software development kit (MMWAVE-SDK). Additional boards may be used to enable additional functionality. For example, DCA1000EVM allows access to the sensor’s raw data via a low-voltage differential signalling (LVDS) interface. The MMWAVEICBOOST development kit allows software development and trace capabilities via Code Composer Studio (CCSTUDIO). IWR6843LEVM paired with MMWAVEICBOOST can interface with the MCU LaunchPad development kit ecosystem.

The sensor evaluation module has four receive (4RX) three transmit (3TX) antenna with 120 degrees azimuth field of view (FoV) and 80 degree elevation FoV.

Discrete DC/DC power management includes onboard capability for power-consumption monitoring. 

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Dev kit evaluates multi-connectivity indoor-outdoor tracking

To support engineers building proof of concept for asset tracking systems, STMicroelctronics offers the STEVAL-ASTRA1B multi-connectivity evaluation kit. It is battery powered, has a small form factor and includes firmware to simplify development targeted applications such as livestock monitoring, fleet management, and logistics.

The kit helps users evaluate ST’s short- and long-range STM32 wireless SoCs. The STM32WL55JC sub-GHz SoC is for long-range connectivity or low power wide area networks (LPWAN) and implements the LoRaWAN (long range WAN) protocol. It provides LoRa, (G)FSK, (G)MSK, and BPSK modulations. 

The second wireless SoC is the STM32WB5MMG module for 2.4GHz Bluetooth Low Energy and Zigbee connectivity. Each SoC has an Arm Cortex-M4 core for application processing with a dedicated Cortex-M0+ to manage the radio.

The development kit also includes an ST25DV64K near field communication (NFC) contactless chip for secure pairing and communication and an STSAFE-A110 secure element for privacy and protection against hacking.

There is also a Teseo-LIV3F miniature GNSS module which provides outdoor positioning. Sensors from the company provide data for monitoring asset condition and environment. Sensors available include an STTS22H low voltage, low power temperature sensor with ±0.5 degrees C accuracy, HTS221 digital humidity and temperature sensor, the LPS22HH barometric pressure sensor, and LIS2DTW12 low power three-axis accelerometer. Also available is the LSM6DSO32X always-on inertial module, which contains a3D accelerometer and 3D gyroscope with machine-learning core.

The STEVAL-ASTRA1B has a smart power and battery management architecture that helps developers maximise application runtime, said ST. It also includes the ST1PS02 nano-quiescent synchronous step-down converter, STBC03 Li-ion battery charging controller, and TCPP01-M12 USB-C port-protection IC.

The ecosystem available for evaluating applications in development include software and tools from ST. The choice includes the FP-ATR-ASTRA1 STM32Cube software function pack with firmware libraries and typical application examples. There is also ST’s asset-tracking mobile app, available on Apple Store and Google Play. The DSH-Assetracking cloud dashboard is also available, free of charge to demonstrate an end-to-end proof of concept.

The STEVAL-ASTRA1B evaluation kit is available to order now through ST’s eStore.

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