Convolutional layers remain one of the main computational bottlenecks in deep neural networks, motivating specialized hardware accelerators for efficient inference. Winogradbased FPGA accelerators reduce the cost of $3 \times 3$ convolutions, but their efficiency depends heavily on how transformed activations and weigh...
Thomas Henrique Schmitz, Lorenzo Picinin, P. Pereira et al.· Symposium on Integrated Circ...· 0 citations
The growth of Convolutional Neural Networks (CNNs) in applications such as image classification and real-time object detection is limited by high computational and energy costs, especially for resource-constrained embedded systems. To address this challenge, this paper presents a fully open-source and flexible hardware...
Fabricio Lorenzon, P. Pereira, M. Grellert· Symposium on Integrated Circ...· 0 citations
This project integrates two 32-point Fast FourierTransform (FFT) accelerators into the RS5 RISC-V processor, afour-stage pipeline architecture supporting custom instructions.We evaluate two FFT accelerator designs (one with parallelinput/output and another with serial input/output), comparingtheir performance against a...
Bruno Soares Zimmer, P. Pereira, Sergio Bampi et al.· Journal of Integrated Circui...· 0 citations
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