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New Low-Density PolarFire® FPGAs


With their ultra-low power consumption, our latest low-density PolarFire FPGAs (MPF050T) and PolarFire SoC (MPFS025T) additions exceed the performance/power metrics of any low-density FPGA or SoC FPGA alternatives in the market. They deliver fast FPGA fabric and signal processing capabilities, the most capable transceivers and the industry’s only hardened application class RISC-V® architecture-based processor.

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Microchip’s VectorBlox™ Accelerator


We offer a VectorBlox Accelerator Software Development Kit and neural networking IP, making it easy for you to program a trained neural network without prior FPGA experience. Make neural network algorithm development easy while leveraging low-power FPGAs and Smart Embedded Vision solutions.

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Accelerate Smart Embedded Vision at the Edge


Supporting 4K resolutions with low-power 12.7 Gbps SerDes, PolarFire® FPGA Smart Embedded Vision solutions include video, imaging, machine learning IP and tools for accelerating designs that require high performance in low-power, small form-factors across the industrial, medical, broadcast, automotive, aerospace and defense markets.

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Say Hello to FPGAs


The Hello FPGA kit is a low-cost, compact-sized, entry-level platform targeted towards end users with low to medium FPGA knowledge. The kit supports powerful demos in image processing, signal processing and Artificial Intelligence (AI).

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Smart High Level Synthesis (HLS) Tool Suite

The need to combine performance with low power consumption in edge compute applications has driven demand for Field Programmable Gate Arrays (FPGAs) to be used as power-efficient accelerators while also providing flexibility and speeding time to market. However, a large majority of edge compute, computer vision and industrial control algorithms are developed natively in C++ by developers with little or no knowledge of underlying FPGA hardware. To empower this important development community, we've added an HLS design workflow called SmartHLS to our PolarFire FPGA families that greatly enhances productivity and ease of design by allowing C++ algorithms to be directly translated to FPGA-optimized Register Transfer Level (RTL) code.

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