Electronic Design

Is Custom Silicon Coming for FPGA Prototyping, Too?

Today’s ultra-complex SoCs are pushing traditional FPGA prototyping to its limits. A new approach uses ASICs that are purpose ...
EDN

FPGA SDK enables sparse AI models

Version 3.0 of Microchip’s VectorBlox Accelerator SDK simplifies FPGA-based AI implementation by supporting sparse neural networks. Available free of charge, the VectorBlox SDK and associated ...

Microchip Advances Neural Network Implementation with VectorBlox™ 3.0 Accelerator SDK

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 ...
GitHub

Spiker: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge

This is the official repo of spiker, a comprehensive framework for generating efficient, low-power, and low-area customized Spiking Neural Networks (SNN) accelerators on FPGA for inference at the edge ...
note

Real-time AI and High-Speed Data Processing Powered by Reconfigurable Task-Specific FPGAs

When processing massive amounts of data instantly or running complex simulations at high speed, have you ever felt that "the CPU alone just can't keep up anymore"? In this video, we will explain in an ...
GitHub

SECDA-TFLite: A Toolkit for Efficient Development of FPGA-based DNN Accelerators for Edge Inference

The SECDA-TFLite toolkit leverages the TFLite delegate system to provide a robust and extensible set of utilities for integrating DNN accelerators for any DNN operation supported by TFLite. Ultimately ...