Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Axelera Metis PCIe Arm AI evaluation kit combines Firefly ITX-3588J mini-ITX motherboard with 214 TOPS Metis AIPU PCIe card

Axelera Metis PCIe Arm AI evaluation kit combines Firefly ITX-3588J mini-ITX motherboard with 214 TOPS Metis AIPU PCIe card

Metis PCIe Arm Evaluation Kit

Axelera has announced the general availability of several Metis PCIe AI Evaluation Kits that combine the company’s 214 TOPS Metis AIPU PCIe card with x86 platforms such as Dell 3460XE workstation and Lenovo ThinkStation P360 Ultra computers, Advantech MIC-770v3 or ARC-3534 industrial PCs, or the Firefly ITX-3588J mini-ITX motherboard powered by a Rockchip RK3588 octa-core Cortex-A76/A55 SoC. We’ll look into detail about the latter in this post. When Axelera introduced the Metis Axelera M.2 AI accelerator module in January 2023 I was both impressed and doubtful of the performance claims of the company since packing a 214 TOPS Metis AIPU in a power-limited M.2 module seemed like a challenge. But it was hard to check independently since the devkits were not available yet although the company only started their early-access program in August last year. Now, anybody with an 899 Euros and up budget can try out their larger Metis […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Silicon Labs MG26, BG26, and PG26 Cortex-M33 AI microcontrollers offer up to 3200KB flash, 512KB RAM, 64 GPIO’s

Silicon Labs MG26, BG26, and PG26 Cortex-M33 AI microcontrollers offer up to 3200KB flash, 512KB RAM, 64 GPIO’s

Silicon Labs MG26 BG26 P26 Cortex M33 microcontrollers

Silicon Labs has announced the xG26 family of Cortex-M33 wireless SoCs and MCUs that consists of the multiprotocol MG26 SoC, the Bluetooth LE BG26 SoC, and the PG26 general-purpose MCU without wireless connectivity, and features double the flash and RAM of the Silicon Labs xG24 devices. The xG26 family also comes with double the number of general-purpose input/output (GPIO) pins as the xG24 to enable engineers to build more complex devices in combination with the larger flash and memory reaching up to 3200 KB and 512KB respectively and also integrates a Matrix Vector Processor (MVP) for AI/ML hardware acceleration and Math functions. Silicon Labs MG26 and BG26 wireless SoCs MG26 and BG26 key features and specifications: MCU core – Arm Cortex-M33 @ 78 MHz AI/ML accelerator – Matrix Vector Processor that is 8x faster and 6x lower power than Cortex-M33 processing, and supports an MVP Math Library for non-ML workloads […]

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Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Intel Agilex 5 SoC FPGA embedded SoM targets 5G equipment, 100GbE networking, Edge AI/ML applications

Intel Agilex 5 SoC FPGA embedded SoM targets 5G equipment, 100GbE networking, Edge AI/ML applications

Hitex eSOM5C-Ex

Hitek Systems eSOM5C-Ex is a compact embedded System-on-Module (SOM) based on the mid-range Intel Agilex 5 SoC FPGA E-Series and a pin-to-pin compatible with the company’s earlier eSOM7C-xF based on the Agilex 7 FPGA F-Series. The module exposes all I/Os, including up to 24 transceivers, through the same 400-pin high-density connector found in the Agilex 7 FPGA-powered eSOM7-xF and the upcoming Agilex 5 FPGA D-Series SOM that will allow flexibility from 100K to 2.7 million logic elements (LEs) for the whole product range. Hitek eSOM5C-Ex specifications: SoC FPGA – Intel Agilex 5 E-series group A and Group B FPGAs in B32 package Supported variants: A5E065A/B, A5E043A/B and A5E043A/B Hard Processing System (HPS) – Dual-core Cortex-A76 and dual-core Cortex-A55 FPGA Up to 656,080 Logic elements 24 x transceivers up to 28Gbps System Memory Up to 2x 8GB LPDDR4 for FPGA 2 or 4GB DDR4 for HPS Storage – 32GB eMMC flash, […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on ADLINK OSM-IMX93 is an OSM Size-L module based on NXP i.MX 93 SoC

ADLINK OSM-IMX93 is an OSM Size-L module based on NXP i.MX 93 SoC

ADLINK OSM-IMX93

ADLINK OSM-IMX93 is an OSM r1.1 Size-L module based on NXP i.MX 93 Arm Cortex-A55 & Cortex-M33 AI processor, and the first from the company to comply with the Open Standard Module (OSM) standard. The 45x45mm module is fitted with up to 2GB LPDDR4L, 128GB eMMC flash, an optional WiFi/Bluetooth module, and its 662 contacts provide a range of interfaces that include LVDS and DSI graphics output, 2x GbE (including 1x TSN capable), 2x CAN bus, I2S audio codec interface, USB2 interfaces, and more. ADLINK OSM-IMX93 specifications: SoC – NXP i.MX 93 CPU 2x Arm Cortex-A55 up to 1.7 GHz 2x Arm Cortex-M33 up to 250 MHz GPU – PXP 2D GPU with blending/composition, resize, color space conversion NPU – Arm Ethos-U65 NPU @ 1 GHz up to 0.5 TOPS Memory – 640 KB OCRAM w/ ECC Security – EdgeLock Secure Enclave System Memory – 1 or 2GB LPDDR4L Storage […]

Posted on by Debashis Das - No Comments on BCM ECM-ADLN-N97 – A 3.5-inch Intel N97 SBC with DDR5 RAM and dual 2.5Gbps Ethernet

BCM ECM-ADLN-N97 – A 3.5-inch Intel N97 SBC with DDR5 RAM and dual 2.5Gbps Ethernet

BCM ECM ADLN N97 SBC with Intel Alder Lake N Processor

BCM Advanced Research recently introduced the ECM-ADLN-N97, a 3.5-inch SBC built around the Intel Processor N97 Alder Lake-N SoC. This N97 quad-core CPU  can be clocked up to 3.6 GHz and features six MB of cache, Intel UHD Graphics, and 24 Execution Units while maintaining a low power consumption with a TDP of just 12 Watts. Additionally, there is the option to utilize Intel Atom or Pentium processors, which have a TDP of 15 Watts. The BCM ECM-ADLN-N97 SBC also has support for DDR5 memory, M.2 E-Key and B-Key slots, 32GB of onboard eMMC, dual 2.5GbE, and multi-display functionality all while maintaining a slim fanless form factor. In one of our previous posts, we wrote about the Cincoze DA-1200 and we also reviewed the Blackview MP80 mini PC both are based on the Intel Processor N97. BCM’s ECM-ADLN-N97 SBC Specification SoC Intel Alder Lake-N Platform; Intel Processor N97, 6M Cache, […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 6 Comments on Kodi 21.0 Omega released with FFmpeg 6, LG webOS support, and more

Kodi 21.0 Omega released with FFmpeg 6, LG webOS support, and more

Kodi 21.0 Omega

Kodi 21.0 “Omega” has just been released with the latest version of the open-source media center adding 3,750 commits since the release of Kodi 20.0 “Nexus” on January 15th, 2023 that notably added AV1 hardware decoding in Android and x86. The new Kodi 21.0 version updates FFmpeg to version 6, adds native support for LG webOS televisions after some reverse-engineering, and implements new features such as Dolby Vision on-the-fly profile conversion in Android, native windowing in macOS that does not rely on the SDL library, and an in-game player viewer to view which game port each player’s controller is currently connected to. Most of the changes were not user-facing and instead, were under-the-hood improvements to the stability, performance, and security of Kodi. You’ll find more changes in the Kodi 21.0 Alpha/Beta/RC pre-release announcements and the complete list of changes on GitHub.  That also means Kodi v22 “P*” development has started. […]

Rockchip RK3568/RK3588 and Intel x86 SBCs
Posted on by Tomisin Olujinmi - No Comments on u-blox ALMA-B1 and NORA-B2, Bluetooth 5.4 LE modules are based on Nordic nRF54H20 and nRF54L15 SoCs

u-blox ALMA-B1 and NORA-B2, Bluetooth 5.4 LE modules are based on Nordic nRF54H20 and nRF54L15 SoCs

u-blox ALMA-B1 and NORA-B2 modules

Wireless communication solutions provider, u-blox has added two new modules to its Bluetooth LE portfolio with the ALMA-B1 and NORA-B2 modules built upon the latest low-power wireless nRF54 chips from Nordic Semiconductor.  Both modules come in a portable, power-efficient layout and support Bluetooth 5.4 and 802.15.4 (Thread, Matter, Zigbee). The ALMA-B1 and NORA-B2 BLE modules are powered by the low-power nRF54H20 and nRF54L15 SoCs, respectively. This enables them to provide IoT devices with sufficient processing power for edge computing and machine learning without the need for external components. u-blox claims that the ALMA-B1 module provides “more than twice the processing power of previous Bluetooth LE modules” and can replace general-purpose microcontrollers in compact solutions. Also, the NORA-B2 reportedly “consumes up to 50% less current compared to previous generations of Bluetooth LE modules,” leading to longer battery life or smaller batteries in end products. Both modules are classified as open CPU […]

Posted on by Tomisin Olujinmi - 1 Comment on Digi ConnectCore MP25 SoM targets Edge AI and computer vision applications with STM32MP25 MPU

Digi ConnectCore MP25 SoM targets Edge AI and computer vision applications with STM32MP25 MPU

digi connectcore mp25 module

Digi International has announced its latest system-on-module (SoM), the Digi ConnectCore MP25 SoM, based on STM32MP25 MPU at Embedded World 2024 in Nuremberg, Germany. The Digi ConnectCore MP25 SoM is built upon STMicroelectronics’ STM32MP25 microprocessor. It supports artificial intelligence and machine learning functionality through an integrated neural processing unit (NPU) capable of 1.35 tera operations per second (TOPS) and an image signal processor (ISP). It is powered by two 64-bit Arm Cortex-A35 cores running at 1.5GHz, supported by a 32-bit Cortex-M33 core operating at 400MHz and a 32-bit Cortex-M0+core running at 200MHz. With its machine learning capabilities, support for time-sensitive networking, and versatile connectivity features, the ConnectCore MP25 module is suitable for edge AI, computer vision, and smart manufacturing applications in various sectors, including medical, energy, and transportation. Digi ConnectCore MP25 specifications: SoC – STMicroelectronics STM32MP257F CPU – 2x 64-bit Arm Cortex-A35 @ 1.5 GHz; MCU 1x Cortex-M33 @ 400 […]

Boardcon Rockchip and Allwinner SoM and SBC products