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Published in 2020 at "Multibody System Dynamics"
DOI: 10.1007/s11044-020-09738-w
Abstract: New products in the automotive and aerospace industries must provide increased energy efficiency and exceed previous performance, safety and reliability. To meet these expectations, the role of simulation continues to grow. Within this context, simulation…
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Keywords:
hardware acceleration;
real time;
time;
embedded applications ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3149505
Abstract: The hardware acceleration of Deep Neural Networks (DNN) is a highly effective and viable solution for running them on mobile devices. The power of DNNs is now available at the edge in a compact and…
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Keywords:
convolution;
spp2d;
hardware acceleration;
bold bold ... See more keywords
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Published in 2019 at "IEEE Journal on Emerging and Selected Topics in Circuits and Systems"
DOI: 10.1109/jetcas.2019.2910864
Abstract: Neural networks have proven to be extremely powerful tools for modern artificial intelligence applications, but computational and storage complexity remain limiting factors. This paper presents two compatible contributions towards reducing the time, energy, computational, and…
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Keywords:
defined sparse;
hardware acceleration;
pre defined;
neural networks ... See more keywords
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Published in 2018 at "IEEE Micro"
DOI: 10.1109/mm.2018.2880169
Abstract: After two terms and a four-year stint, this issue is my last as Editor-in-Chief of IEEE MICRO. It has been an amazing and rewarding experience with 24 issues in total. A couple theme issues are…
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Keywords:
hardware acceleration;
acceleration grateful;
grateful goodbye;
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Published in 2022 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2022.3197512
Abstract: Spiking neural networks (SNNs) compute in an event-based manner to achieve a more efficient computation than standard neural networks. In SNNs, neuronal outputs are not encoded as real-valued activations but as sequences of binary spikes.…
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Keywords:
neural networks;
spiking neural;
efficient hardware;
sparsely active ... See more keywords
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Published in 2023 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2022.3209550
Abstract: Satisfiability modulo theories (SMTs), an extension of Boolean satisfiability (SAT) problem, is widely used in many application domains because of its rich expressiveness. Thus, there are many works trying to speedup the process of SAT/SMT…
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Keywords:
smt solver;
hardware;
smt;
solver hardware ... See more keywords
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Published in 2022 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2022.3162303
Abstract: Multiple Signal Classification (MUSIC) is a high-performance Direction of Arrival (DOA) estimation algorithm, which has been widely used. The algorithm needs to calculate the covariance matrix, eigenvalue decomposition and spectral peak search. In the paper,…
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Keywords:
music algorithm;
algorithm;
acceleration music;
uniform linear ... See more keywords