Variscite, a leading worldwide System on Module (SoM) designer, developer and manufacturer, will demonstrate its newest SoMs for the first time at Embedded World 2023 at stand 3A-135, from March 14-16 at Messezentrum Nuremberg in Germany.
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“We look forward to presenting show attendees the module’s capabilities.”
Variscite’s VAR-SOM-MX93 is ideal for energy-efficient machine learning edge devices, with a rich set of features for markets like industrial, IoT, and smart devices at an attractive price point, starting at only $39. Powered by 1.7GHz Dual Cortex-A55 NXP i.MX 93 processor, the industry’s first implementation of the Arm neural processing unit (NPU), Ethos-U65 microNPU, VAR-SOM-MX93 accelerates ML workloads and offers an energy-flex architecture for efficient processing. The SoM offers an additional 250MHz Cortex-M33 real-time co-processor, AI/ML capabilities, built-in security and a wide range of industrial features.
Starting at only $33, the VAR-SOM-AM62, powered by Texas Instruments’ AM62x features an ideal platform for cost-sensitive embedded products that require low power, high performance and a GPU. The VAR-SOM-AM62 runs on 1.4 GHz Quad-core Cortex-A53 AM625x with 400MHz Cortex-M4F and additional 333 MHz PRU real-time co-processors. It offers rich connectivity options like a camera interface, dual LVDS display, certified dual-band Wi-Fi, BT/BLE 5.2, 3x CAN bus, dual USB, and dual GbE.
The company unveils real world machine learning performance benchmarks for the latest addition to its SoM portfolio. For this performance benchmark, Variscite compared 3 modules with different CPU performance, pricing, power efficiency level and ML options.
In internal benchmarking, running video-based object classification tests, the VAR-SOM-MX93 utilizing the Ethos-U65 NPU performed with an average inference time of 4.9 ms and an average video throughput of 30 fps on a 640×480 input video. Running the same tests on the VAR-SOM-MX8M-NANO with no NPU demonstrated an average inference time of 300 ms and average video throughput of 1 fps. Finally, the VAR-SOM-MX8M-PLUS utilizing its NPU yields an average inference time of 2.9 ms and an average video throughput of 30 fps.
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“Our newest modules represent the next generation of Variscite’s technology and provide state-of-the-art platforms for robust, reliable, power efficient and cost-effective embedded computing devices,” said Ofer Austerlitz, VP Business Development and Sales of Variscite. “We look forward to presenting show attendees the module’s capabilities.”
Both SoMs are compatible with the VAR-SOM Pin2Pin product family, allowing Variscite’s customers to easily scale at any point of the product lifecycle while using the same carrier board for all platforms. The Pin2Pin family provides an extended lifespan, reduced development time, costs, and risks as well as advanced scalability options from entry-level to high-performance modules.
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