Imagination launches the APXM-6200 RISC-V “Catapult” CPU for cost-sensitive consumer and industrial applications

APXM-6200 RISC-V CPU

Imagination has expanded its Catapult product portfolio to include a new RISC-V core, the Imagination APXM-6200 CPU. The APXM-6200 is a 64-bit, in-order application processor with an 11-stage, dual-issue pipeline. There isn’t much information on the new Imagination RISC-V core on the product page but we know it offers “best-in-class” performance density, a minimal silicon footprint, and industry-standard security features. The CPU is targeted at intelligent consumer and industrial applications and delivers a 2.5x improvement in performance density and a 65% improvement in normalized performance over comparable Arm Cortex-A53 and other cores on the market. It’s also faster than the Cortex-A510 Armv9 core in SpecINT2k6. Imagination claims that combining the APXM-6200 CPU with their GPUs will ensure a 2x increase in bus utilization and a 2x reduction in memory traffic. It also comes with RISC-V vector extensions, and AI compute libraries and supports fast data coupling with AI accelerators for […]

Arm Ethos-U85 NPU delivers up to 4 TOPS for Edge AI applications in Cortex-M7 to Cortex-A520 SoCs

Arm Ethos-U85 NPU

Arm has just Introduced its third-generation NPU for edge AI with the Arm Ethos-U85 that scales from 256 GOPS to 4 TOPS or up to four times the maximum performance of the previous generation Ethos-U65 microNPU, while also delivering 20% higher power efficiency. While previous Arm microNPUs were paired with Cortex-M microcontroller-class cores potentially embedded into a Cortex-A application processor, the new Ethos-U85 can be married with Cortex-M microcontrollers and Cortex-A application processors up to the Cortex-A510/A520 Armv9 cores. Arm expects the Ethos-U85 to find its way into SoC designed for factory automation and commercial or smart home cameras with support for the new Transformer Networks and the more traditional Convolutional Neural Networks (CNNs). The Arm Ethos-U85 supports 128 to 2,048 MACs with performance ranging from 256 GOPS to 4 TOPS at 1 GHz, embeds 29 to 267KB RAM, offers SRAM, DRAM, and flash interface for external memory, and up […]

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 […]

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, […]

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

digi connectcore mp25 module

Digi International, an American Industrial IoT solutions provider, has announced its latest system-on-module, the Digi ConnectCore MP25 SoM, 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 @ […]

Toradex Aquila AM69 SoM features TI AM69A octa-core Cortex-A72 AI SoC, rugged 400 pin board-to-board connector

Toradex Aquila AM69

Toradex Aquila AM69 is the first system-on-module (SoM) from the company’s Aquila family with a small form factor and a rugged ~400-pin board-to-board connector targetting demanding edge AI applications in medical, industrial, and robotics fields with Arm platforms that deliver x86 level of performance at low power. The Aquila AM69 SoM is powered by a Texas Instruments AM69A octa-core Arm Cortex-A72 SoC with four accelerators delivering 32 TOPS of AI performance, up to 32GB LPDDR4, 128GB eMMC flash, built-in WiFi 6E and Bluetooth 5.3 module, and a board-to-board connector for display, camera, and audio interfaces, as well as dual gigabit Ethernet, multiple PCIe Gen3 and SerDes interfaces. All that in a form factor that’s only slightly bigger (86x60mm) than a business card or a Raspberry Pi 5. Toradex Aquila AM69 specifications: SoC  – Texas Instruments AM69A Application processor – Up to 8x Arm Cortex-A72 cores at up to 2.0 GHz […]

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) […]

Hailo-10 M.2 Key-M module brings Generative AI to the edge with up to 40 TOPS of performance

Hailo-10 M.2 module generative AI for the edge

Hailo-10 is a new M.2 Key-M module that brings Generative AI  capabilities to the edge with up to 40 TOPS of performance at low power. It targets AI PCs supporting only the Windows 11 operating system on x86 or Aarch64 targets at this time. Hailo claims the Hailo-10 is faster and more energy efficient than integrated neural processing unit (NPU) solutions found in Intel SoCs and delivers at least twice the performance at half the power of Intel’s Core Ultra “AI Boost” NPU. Hailo-10 module specifications: AI accelerator – Hailo-10H System Memory – 8GB LPDDR4 on module Host interface – 4-lane PCIe Gen 3 Power consumption – Less than 3.5W (typical) for the chip Form factor – M.2 Key M 2242 / 2280 Supported AI frameworks – TensorFlow, TensorFlow Lite, Keras, PyTorch & ONNX The Hailo-10 can run Llama2-7B with up to 10 tokens per second (TPS) at under 5W […]