By isolating the mission-critical work to a single, powerful P-core and shoveling the noise onto the seven E-cores, the V4 17 solves the "big.LITTLE" dilemma that plagues many industrial automation systems.
Ubrt generally supports their V-series for 7 years. Expect the V4 17 to be orderable until 2031 , with longevity support until 2034 . Final Verdict The Ubrt-2300 V4 17 is not the fastest chip on the market, nor is it the cheapest. It is, however, the most elegant solution for edge computing where latency and power are equally important. Ubrt-2300 V4 17
For detailed schematics and reference designs, visit the official Ubrt developer portal or contact your regional FAE (Field Applications Engineer) with the part number: . This article is based on public engineering samples and preliminary datasheets. Final retail specifications may vary by 1-2% due to binning. By isolating the mission-critical work to a single,
In the rapidly evolving landscape of industrial automation, edge computing, and high-density server infrastructure, model numbers often blur together. However, one designation has recently captured the attention of systems integrators and embedded engineers: Ubrt-2300 V4 17 . Final Verdict The Ubrt-2300 V4 17 is not
The integration of a 5 TOPS NPU (Neural Processing Unit) is a game changer. It allows the Ubrt-2300 V4 17 to run lightweight computer vision models (like OpenCV or TensorFlow Lite) without taxing the P-core or E-cores. We ran the Ubrt-2300 V4 17 against its predecessor (Ubrt-2200 V3 16) and a competing Atom-class processor.
| Feature | Specification | | :--- | :--- | | | 1x P-core + 7x E-cores (Total 8 threads) | | Base Frequency | 2.8 GHz (Hybrid) | | L3 Cache | 12 MB (Shared across all cores) | | Memory Support | Dual-channel DDR5-5600 ECC (Up to 64 GB) | | PCIe Lanes | 16x Gen 5.0 + 4x Gen 4.0 | | TDP (Thermal Design Power) | 15W – 28W (Configurable) | | NPU (Neural Processor) | 2nd Gen Ubrt Neuro Core (5 TOPS) | | I/O Integrated | 2x 10GbE, 4x USB 4.0, 1x HDMI 2.1 | | Form Factor | COM Express Type 7 Compact |
Robotics engineers, network security appliance builders, and portable medical device designers. Who should skip it: Desktop gamers or data centers requiring raw FP64 compute.
