|
|
|
|
|
Chi Gao, Xiaofei Xu, Zhizou Yang, Liwei Lin and Jian Li
In recent decades, memory-intensive applications have experienced a boom, e.g., machine learning, natural language processing (NLP), and big data analytics. Such applications often experience out-of-memory (OOM) errors, which cause unexpected processes t...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jinnan Wang, Weiqin Tong and Xiaoli Zhi
Convolutional neural networks (CNNs) have made impressive achievements in image classification and object detection. For hardware with limited resources, it is not easy to achieve CNN inference with a large number of parameters without external storage. ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yongseok Lee, Jonghee Youn, Kevin Nam, Hyunyoung Oh and Yunheung Paek
This paper focuses on enhancing the performance of the Nth-degree truncated-polynomial ring units key encapsulation mechanism (NTRU-KEM) algorithm, which ensures post-quantum resistance in the field of key establishment cryptography. The NTRU-KEM, while ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Arghavan Asad, Rupinder Kaur and Farah Mohammadi
From self-driving cars to detecting cancer, the applications of modern artificial intelligence (AI) rely primarily on deep neural networks (DNNs). Given raw sensory data, DNNs are able to extract high-level features after the network has been trained usi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rakib Hossen, Md Whaiduzzaman, Mohammed Nasir Uddin, Md. Jahidul Islam, Nuruzzaman Faruqui, Alistair Barros, Mehdi Sookhak and Md. Julkar Nayeen Mahi
The Internet of Things (IoT) has seen a surge in mobile devices with the market and technical expansion. IoT networks provide end-to-end connectivity while keeping minimal latency. To reduce delays, efficient data delivery schemes are required for disper...
ver más
|
|
|
|
|
|
|
|
|
|
|
Iouliia Skliarova
This paper proposes a Field-Programmable Gate Array (FPGA)-based hardware accelerator for assisting the embedded MicroBlaze soft-core processor in calculating population count. The population count is frequently required to be executed in cyber-physical ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Seungtae Hong, Hyunwoo Cho and Jeong-Si Kim
As embedded systems, such as smartphones with limited resources, have become increasingly popular, active research has recently been conducted on performing on-device deep learning in such systems. Therefore, in this study, we propose a deep learning fra...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lilian Bossuet and El Mehdi Benhani
Cache attacks are widespread on microprocessors and multi-processor system-on-chips but have not yet spread to heterogeneous systems-on-chip such as SoC-FPGA that are found in increasing numbers of applications on servers or in the cloud. This type of So...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chuanglu Chen, Zhiqiang Li, Yitao Zhang, Shaolong Zhang, Jiena Hou and Haiying Zhang
In pulse waveform classification, the convolution neural network (CNN) shows excellent performance. However, due to its numerous parameters and intensive computation, it is challenging to deploy a CNN model to low-power devices. To solve this problem, we...
ver más
|
|
|
|
|
|
|
|
|
|
|
Grzegorz Korcyl,Piotr Korcyl
Pág. 56 - 63
In recent years, computational capacity of single Field Programmable Gate Array (FPGA) devices as well as their versatility have increased significantly. Adding to that fact, the High Level Synthesis frameworks allowing to program such processors in a hi...
ver más
|
|
|
|
|
|