Microchip Advances Neural Network Implementation with VectorBlox™ 3.0 Accelerator SDK
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CHANDLER, Ariz., July 14, 2026 (GLOBE NEWSWIRE) -- Deploying AI inference in power‑constrained and mission‑critical environments such as aerospace and defense systems requires solutions that balance performance, efficiency, reliability and ease of development. To better manage these challenges, Microchip Technology (Nasdaq: MCHP) has released the VectorBlox™ 3.0 Accelerator Software Development Kit (SDK) to help simplify FPGA‑based AI implementation and speed time‑to‑market. Offered to developers free of charge, VectorBlox 3.0 SDK and associated CoreVectorBlox IP is designed as an integrated toolchain that streamlines optimization, compilation and deployment of convolutional neural network (CNN) models on PolarFire® FPGA and SoC-based platforms. Because the accelerator scales efficiently across model sizes and supports multiple AI workloads on a single device, customers can consolidate various vision or sensor‑based AI functions on a single low power FPGA. "As AI models continue to grow in complexity, compression is becoming essential for deploying intelligence at the edge," said Shakeel Peera, corporate vice president and GM of Microchip's FPGA business unit. "With VectorBlox 3.0, we're leveraging sparsity-based model compression from our Neuronix acquisition to reduce compute demands while preserving accuracy." With support for sparse neural networks, VectorBlox 3.0 helps...
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