CPU-accelerator co-scheduling for CNN acceleration at the edge
Convolutional neural networks (CNNs) are widely deployed for many artificial intelligence
(AI) applications, such as object detection and image classification. Due to the burgeoning …
(AI) applications, such as object detection and image classification. Due to the burgeoning …
A systematic evaluation of recurrent neural network models for edge intelligence and human activity recognition applications
VS Lalapura, VR Bhimavarapu, J Amudha… - Algorithms, 2024 - mdpi.com
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning
algorithms. Complex tasks like speech recognition, machine translation, sentiment …
algorithms. Complex tasks like speech recognition, machine translation, sentiment …
Flydeling: Streamlined performance models for hardware acceleration of CNNs through system identification
W Carballo-Hernández, M Pelcat… - ACM Transactions on …, 2023 - dl.acm.org
The introduction of deep learning algorithms, such as Convolutional Neural Networks
(CNNs) in many near-sensor embedded systems, opens new challenges in terms of energy …
(CNNs) in many near-sensor embedded systems, opens new challenges in terms of energy …
The effects of partitioning strategies on energy consumption in distributed cnn inference at the edge
E Tang, X Guo, T Stefanov - arXiv preprint arXiv:2210.08392, 2022 - arxiv.org
Nowadays, many AI applications utilizing resource-constrained edge devices (eg, small
mobile robots, tiny IoT devices, etc.) require Convolutional Neural Network (CNN) inference …
mobile robots, tiny IoT devices, etc.) require Convolutional Neural Network (CNN) inference …
Automatic CNN Model Partitioning for GPU/FPGA-based Embedded Heterogeneous Accelerators using Geometric Programming
Abstract Graphics Processing Unit (GPU), dedicated Application Specific Integrated Circuit
(ASIC) and Field Programmable Gate Array (FPGA) accelerators are currently platforms of …
(ASIC) and Field Programmable Gate Array (FPGA) accelerators are currently platforms of …
Deep Learning Process Integration on Heterogeneous GPU/FPGA Embedded Platforms
WC Hernandez - 2022 - theses.hal.science
Deep Learning (DL) algorithm deployment on edge devices, such as Convolutional Neural
Network (CNN) inference, has established a high computing demand on devices with limited …
Network (CNN) inference, has established a high computing demand on devices with limited …