MALOC: A fully pipelined FPGA accelerator for convolutional neural networks with all layers mapped on chip
Recently, field-programmable gate arrays (FPGAs) have been widely used in the
implementations of hardware accelerator for convolutional neural networks (CNNs) …
implementations of hardware accelerator for convolutional neural networks (CNNs) …
Key roles of plasmonics in wireless THz nanocommunications—A survey
E Lallas - Applied Sciences, 2019 - mdpi.com
Wireless data traffic has experienced an unprecedented boost in past years, and according
to data traffic forecasts, within a decade, it is expected to compete sufficiently with wired …
to data traffic forecasts, within a decade, it is expected to compete sufficiently with wired …
Self-optimizing and self-programming computing systems: A combined compiler, complex networks, and machine learning approach
There exists an urgent need for determining the right amount and type of specialization
while making a heterogeneous system as programmable and flexible as possible …
while making a heterogeneous system as programmable and flexible as possible …
Lithium-ion batteries state of charge prediction of electric vehicles using RNNs-CNNs neural networks
F Zhao, Y Li, X Wang, L Bai, T Liu - Ieee Access, 2020 - ieeexplore.ieee.org
In order to achieve the safe and efficient energy use in the electric vehicle, the continuous
and accurate monitoring of lithium-ion batteries (LIBs) has become a long-standing research …
and accurate monitoring of lithium-ion batteries (LIBs) has become a long-standing research …
Learning-based application-agnostic 3D NoC design for heterogeneous manycore systems
The rising use of deep learning and other big-data algorithms has led to an increasing
demand for hardware platforms that are computationally powerful, yet energy-efficient. Due …
demand for hardware platforms that are computationally powerful, yet energy-efficient. Due …
Energy-efficient networks-on-chip architectures: Design and run-time optimization
Abstract Networks-on-Chip (NoC) architectures have become the mainstream
communication backbone of high-end processors and systems-on-chip (SoCs) after their …
communication backbone of high-end processors and systems-on-chip (SoCs) after their …
Pattern separation network based on the hippocampus activity for handwritten recognition
N Modhej, A Bastanfard, M Teshnehlab… - IEEE …, 2020 - ieeexplore.ieee.org
Reaching high accuracy in handwritten character recognition is an essential challenge since
it is widely used in many fields such as signature analysis and forgery detection. Recently …
it is widely used in many fields such as signature analysis and forgery detection. Recently …
Fast and efficient convolutional accelerator for edge computing
Convolutional neural networks (CNNs) are a vital approach in machine learning. However,
their high complexity and energy consumption make them challenging to embed in mobile …
their high complexity and energy consumption make them challenging to embed in mobile …
Machine learning for design space exploration and optimization of manycore systems
In the emerging data-driven science paradigm, computing systems ranging from IoT and
mobile to manycores and datacenters play distinct roles. These systems need to be …
mobile to manycores and datacenters play distinct roles. These systems need to be …
Co-exploring neural architecture and network-on-chip design for real-time artificial intelligence
Hardware-aware Neural Architecture Search (NAS), which automatically finds an
architecture that works best on a given hardware design, has prevailed in response to the …
architecture that works best on a given hardware design, has prevailed in response to the …