Efinix Titanium Ti375 SoC combines high-density, low-power Quantum compute fabric with a quad-core hardened 32-bit RISC-V block and features a LPDDR4 DRAM controller, a MIPI D-PHY for displays or cameras, and 16 Gbps transceivers enabling PCIe Gen 4 and 10GbE interfaces. The Titanium Ti375 also comes with 370K logic elements, 1.344 DSP blocks, 2,688 10-Kbit SRAM blocks, and 27,53 Mbits embedded memory, as well as DSP blocks optimized for computing and AI workloads, and XLR (eXchangeable Logic and Routing) cells for logic and routing. Efinix Titanium Ti375 specifications: FPGA compute fabric 370,137 logic elements (LEs) 362,880 eXchangeable Logic and Routing (XLR) cells 27,53 Mbits embedded memory 2,688 10-Kbit SRAM blocks 1,344 embedded DSP blocks for multiplication, addition, subtraction, accumulation, and up to 15-bit variable-right-shifting Memory – 10-kbit high-speed, embedded SRAM, configurable as single-port RAM, simple dual-port RAM, true dual-port RAM, or ROM FPGA interface blocks 32-bit quad-core hardened RISC-V block […]
Smartcam T1205 – An IP65-rated AI camera with NVIDIA Jetson Orin Nano 40 TOPS system-on-module
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 […]
Sipeed MaixBox M4N AI Box with 43.2 TOPS AXera AX650N SoC can decode/encode up to 32 videos
Sipeed MaixBox M4N is an AI box for video analytics and computer vision equipped with an AXera-Pi Pro (AX650N) octa-core Cortex-A55 SoC with a 43.2 TOPS (INT4) or 10.8 TOPS (INT8) AI accelerator and an H.265/H2.64 video encoder/decoder supporting up to 32 1080p30 videos. The AI box is based on the Sipeed Maix-IV motherboard, an upgrade to the Maix-III devkit with an AX620A quad-core Cortex-A7 SoC with a 14.4 TOPS AI accelerator (INT4). It comes with 8GB RAM shared for Linux and the AI accelerator, 32GB eMMC flash and an M.2 SATA socket for storage, two HDMI outputs, two gigabit Ethernet ports, optional WiFi or 4G LTE mini PCIe module, a few USB ports, and RS232 and RS485 interfaces. Sipeed MaixBox M4N specifications: SoC – AXera AX650N CPU – Octa-core Arm Cortex-A55 @ 1.7 GHz with NEON support NPU – 43.2 TOPS @ INT4, 10.8 TOPS @ INT8 with support […]
Arducam KingKong – A Raspberry Pi CM4-based Edge AI camera with global shutter sensor, Myriad X AI accelerator
ArduCam KingKong is a Smart Edge AI camera based on the Raspberry Pi CM4 and system-on-module based on Intel Myriad X AI accelerator that follows the Raspberry Pi 5-powered Arducam PiINSIGHT camera introduced at the beginning of the year. The new product launch aims to provide a complete Raspberry Pi-based camera rather than an accessory for the Raspberry Pi 4/5. Smart cameras built around the Raspberry Pi CM4 are not new as we previously covered the EDATEC ED-AIC2020 IP67-rated industrial AI Edge camera and the StereoPi v2 stereoscopic camera used to create 3D video and 3D depth maps. The ArduCam KingKong adds another option suitable for computer vision applications with an AR0234 global shutter module, PoE support, and a CNC metal enclosure. ArduCam KingKong specifications: SoM – Raspberry Pi Compute Module 4 (CM4) by default CM4104000 Wireless 4GB RAM Lite (0GB eMMC). AI accelerator – Luxonis OAK SOM BW1099 based on Intel […]
WeAct STM32H743 Arm Cortex-M7 board ships with a 0.96-inch LCD and a choice of camera sensors
WeAct STM32H743 is a small MCU development board powered by a 480 MHz STMicro STM32H743VIT6 Cortex-M7 microcontroller and equipped with a small LCD and a camera connector taking OV2640, OV5640-AF, OV7670, or OV7725 camera sensors. The board comes with 2048KB flash and 1MB RAM built into the STM32H7 microcontroller, 8MB SPI flash, 8MB QSPI flash, a microSD for data storage, USB-C port for power and programming, a few buttons, and plenty of I/Os accessible through two 44-pin headers. WeAct STM32H743 specifications: MCU – STMicro STM32H743VIT6 Arm Cortex-M7 microcontroller at 480MHz with FPU, DSP, and MPU, 2048KB flash, 1MB RAM Storage – 8MB SPI Flash, 8MB QSPI Flash (bootable), microSD card socket Display – 0.96-inch TFT LCD based on ST7735 SPI display driver Camera 8-bit Digital Camera Interface (DCMI) with autofocus support OV2640 (1600×1200), OV5640-AF (2592×1944 with autofocus), OV7670 (640×480), or OV7725 (640×480) camera sensors are supported USB – 1x USB-C […]
Kaki Pi is a Raspberry Pi-inspired Renesas RZ/V2H AI SBC with four camera connectors, a PCIe 3.0 interface
Japanese company Yuridenki-Shokai Co. Ltd will soon launch the Kaki Pi single board computer [update Aug 2024: now called Kakip] based on the just-announced Renesas RZ/V2H Arm microprocessor with a powerful 80 TOPS AI accelerator, with Raspberry Pi-inspired form factor and features such as the 40-pin GPIO header, the same PCIe 3.0 connector as found in the Raspberry Pi 5, and four 22-pin MIPI CSI connectors that look to be compatible with the Raspberry Pi cameras. The board also comes with up to 8GB LPDDR4, a microSD card for the OS, a 22-pin MIPI DSI connector for a display, a gigabit Ethernet port, two USB 3.0 ports, two CAN Bus connectors, and other interfaces that make it suitable for robotics applications such as Autonomous Mobile Robots (AMR) and HSR (Human Support Robots) as well as IoT projects. Kaki Pi specifications: SoC – Renesas RZ/V2H CPU/MCU cores Quad-core Arm Cortex-A55 processor […]
Renesas RZ/V2H Cortex-A55/R8/M33 MPU comes with 80 TOPS AI accelerator for robotics and autonomous applications
The RZ/V2H is the latest addition to the Reneasas family of 32-bit and 64-bit microprocessors. Renesas RZ/V2H microprocessor features four Arm Cortex-A55 application processing cores, dual Arm Cortex-R8 real-time processing cores, and one Cortex-M33 core for system management, as well as an AI accelerator with up to 80 TOPS (sparse) of performance. The RZ/V2H MPU includes the third generation of Renesas’ dynamically reconfigurable processor for AI (DRP-AI3) accelerator, a staple of the RZ/V series. The DRP-AI accelerator can run complex image AI models at a power efficiency of 10 TOPS per watt (TOPS/W), as much as 10 times higher than conventional microprocessors. Additionally, the RZ/V2H has another DRP that can be used in image processing and robotics applications. The board also comes with PCIe Gen3, USB 3.2, and Gigabit Ethernet for high-speed applications such as autonomous robotics and factory automation machine vision. It offers a performance boost over previous products […]
Testing AI and LLM on Rockchip RK3588 using Mixtile Blade 3 SBC with 32GB RAM
We were interested in testing artificial intelligence (AI) and specifically large language models (LLM) on Rockchip RK3588 to see how the GPU and NPU could be leveraged to accelerate those and what kind of performance to expect. We had read that LLMs may be computing and memory-intensive, so we looked for a Rockchip RK3588 SBC with 32GB of RAM, and Mixtile – a company that develops hardware solutions for various applications including IoT, AI, and industrial gateways – kindly offered us a sample of their Mixtile Blade 3 pico-ITX SBC with 32 GB of RAM for this purpose. While the review focuses on using the RKNPU2 SDK with computer vision samples running on the 6 TOPS NPU, and a GPU-accelerated LLM test (since the NPU implementation is not ready yet), we also went through an unboxing to check out the hardware and a quick guide showing how to get started […]