sdk

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Yocto Project 5.0 “Scarthgap” released with Linux 6.6 and plenty of changes

Yocto Project 5.0 “Scarthgap” released with Linux 6.6 and plenty of changes

Yocto Project 5.0

The Yocto Project 5.0 codenamed “Scarthgap” has just been released with Linux 6.6, glibc 2.39, LLVM 18.1, and over 300 other recipe upgrades. As a result of the release, the developers have made it available for download (bz2 tarball). The Yocto Project, or Yocto for shorts, is a popular framework used to create custom embedded Linux distributions, and we’ve played with it over the year showing how to create a minimal image for the Raspberry Pi, and last year, we used it again when reviewing two industrial development boards, namely the VOIPAC IMX8M and ADLINK i-Pi SMARC 1200. Yocto is quite a powerful framework/build system with plenty of options that make it highly customizable, but the learning curve is fairly steep. Some other changes in Yocto Project 5.0 include: New variables: CVE_DB_INCR_UPDATE_AGE_THRES: Configure the maximum age of the internal CVE database for incremental update (instead of a full redownload). RPMBUILD_EXTRA_PARAMS: […]

Posted on by Debashis Das - No Comments on Synaptics Astra platform takes SL1620, SL1640, or SL1680 Arm CPU module for Edge AI applications

Synaptics Astra platform takes SL1620, SL1640, or SL1680 Arm CPU module for Edge AI applications

Astra Machina Foundation Series Dev Board

Synaptics has unveiled its new Astra platform with a range of SoC and a development kit for edge AI applications. These new processors and a supporting development kit are built to provide out-of-the-box AI capabilities for IoT devices, reducing reliance on cloud-based AI. This new Synaptics Astra Platform is built around three main SoCs. The SL1680 is built for multi-modal IoT applications and features a quad-core Arm Cortex-A73 CPU, dedicated 7.9 TOPS NPU, and 4K video. The SL1640 is a cost and power-optimized SoC with a quad-core Cortex-A55 CPU and 1.6+ TOPS NPU. Finally, the SL1620 is a graphics and AI accelerator with a quad-core Cortex-A55 CPU and dual-core Imagination BXE-2-32 GPU but does not feature an NPU. The development kit features a module design where the new swappable compute modules allow flexible configurations. The devkit will support open Yocto Linux distribution and Synaptics AI toolkit for quick AI integration. […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 6 Comments on Qualcomm RB3 Gen 2 Platform with Qualcomm QCS6490 AI SoC targets robotics, IoT and embedded applications

Qualcomm RB3 Gen 2 Platform with Qualcomm QCS6490 AI SoC targets robotics, IoT and embedded applications

Qualcomm RB3 Gen 2 Platform Vision Kit

Qualcomm had two main announcements at Embedded World 2024: the ultra-low-power Qualcomm QCC730 WiFi microcontroller for battery-powered IoT devices and the Qualcomm RB3 Gen 2 Platform hardware and software solution designed for IoT and embedded applications based on the Qualcomm QCS6490 processor that we’re going to cover today. The kit is comprised of a QCS6490 octa-core Cortex-A78/A55 system-on-module with 12 TOPS of AI performance, 6GB RAM, and 128GB UFS flash connected to the 96Boards-compliant Qualcomm RBx development mainboard through interposer, as well as optional cameras, microphone array, and sensors. Qualcomm QCS6490/QCM6490 IoT processor Specifications: CPU – Octa-core Kryo 670 with 1x Gold Plus core (Cortex-A78) @ 2.7 GHz, 3x Gold cores (Cortex-A78) @ 2.4 GHz, 4x Silver cores (Cortex-A55) @ up to 1.9 GHz GPU – Adreno 643L GPU @ 812 MHz with support for Open GL ES 3.2, Open CL 2.0, Vulkan 1.x, DX FL 12 DSP – Hexagon […]

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) - 6 Comments on AMD Ryzen Embedded 8000 Series processors target industrial AI with 16 TOPS NPU

AMD Ryzen Embedded 8000 Series processors target industrial AI with 16 TOPS NPU

AMD Ryzen Embedded 8000

AMD has recently “announced” the Ryzen Embedded 8000 Series processors in a community post with the latest AMD embedded devices combining a 16 TOPS NPU based on the AMD XDNA architecture with CPU and GPU elements for a total of 39 TOPS designed for industrial artificial intelligence. The Ryzen Embedded 8000 CPUs will be found in machine vision, robotics, and industrial automation applications to enhance the quality control and inspection processes, enable real-time, route-planning decisions on-device for minimal latency, and predictive maintenance, and autonomous control of industrial processes. AMD Ryzen Embedded 8000 key features and shared specifications: CPU – Up to 8 “Zen 4” cores, 16 threads Cache L1 Instruction Cache – 32 KB, L1 Data Cache = 32 KB (per core) L2 Cache – Up to 8 MB (total) L3 Cache-  Up to 16 MB unified Graphics – RDNA 3 graphics with up to 6 WGPs (Work Group processors) […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on DeGirum ORCA M.2 and USB Edge AI accelerators support Tensorflow Lite and ONNX model formats

DeGirum ORCA M.2 and USB Edge AI accelerators support Tensorflow Lite and ONNX model formats

Degirum ORCA M.2 PCIe module

I’ve just come across an Atom-based Edge AI server offered with a range of AI accelerator modules namely the Hailo-8, Blaize P1600, Degirum ORCA, and MemryX MX3. I had never heard about the last two, and we may cover the MemryX module a little later, but today, I’ll have a closer at the Degirum ORCA chip and M.2 PCIe module. The DeGirum ORCA is offered as an ASIC, an M.2 2242 or 2280 PCIe module, or (soon) a USB module and supports TensorFlow Lite and ONNX model formats and INT8 and Float32 ML precision. They were announced in September 2023, and have already been tested in a range of mini PCs and embedded box PCs from Intel (NUC), AAEON, GIGABYTE, BESSTAR, and Seeed Studio (reComputer). DeGirum ORCA specifications: Supported ML Model Formats – ONNX, TFLite Supported ML Model Precision – Float32, Int8 DRAM Interface – Optional 1GB, 2GB, or 4GB […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 7 Comments on Smartcam T1205 – An IP65-rated AI camera with NVIDIA Jetson Orin Nano 40 TOPS system-on-module

Smartcam T1205 – An IP65-rated AI camera with NVIDIA Jetson Orin Nano 40 TOPS system-on-module

NVIDIA Jetson Orin AI camera

SmartCow’s SmartCam T1025 is a powerful AI camera based on the NVIDIA Jetson Orin Nano 8GB system-on-module with 40 TOPS of AI performance. The camera features M12 connectors for gigabit Ethernet, power, and serial interface, and has been certified with an IP65 ingress protection rating for outdoor operation. The camera also comes with 256GB NVMe SSD for the OS (Jetpack 6.0) and data storage and supports 4G LTE and GPS connectivity through an M.2 module. The company also introduced the SmartCam T1023 model compatible with NVIDIA Jetson Nano and Jetson TX2 NX for applications that do not require as much processing power and/or memory as provided by the Jetson Orin Nano AI camera. SmartCam T1025 specifications: System-on-module – NVIDIA Jetson Orin Nano 8GB CPU – 6-core Arm Cortex-A78AE v8.2 64-bit CPU @ 1.5 GHz with 1.5 MB L2 + 4 MB L3 GPU – 1024-core NVIDIA Ampere GPU @ 625 […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 3 Comments on Doly – A cute little autonomous AI-powered robot based on Raspberry Pi CM4 module (Crowdfunding)

Doly – A cute little autonomous AI-powered robot based on Raspberry Pi CM4 module (Crowdfunding)

Doly Raspberry Pi CM4 robot

Limitbit Doly is a cute little autonomous robot with two continuous tracks, two small arms controlled by servos, two round color displays acting as the eyes, and various sensors, all controlled by a Raspberry Pi CM4 system-on-module. The robot can be used for STEM (Science, Technology, Engineering, and Mathematics) education or as a developer platform. AI workloads can also run on the Raspberry Pi CM4 module taking sensors, camera, and microphone inputs, with the robot interacting with the user through the built-in stereo speaker and two eyes. In practice, that means Doly supports features such as face recognition and smart audio with the robot capable of recognizing its owner and responding to voice commands. Doly specifications: System-on-Module – Raspberry Pi CM4 Lite model CM4101000 (1GB RAM, Wireless) by default, but also supports other CM4/CM Lite modules with wireless Storage – MicroSD card slot Display – 2x high-resolution color displays (the […]

UP 7000 x86 SBC