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Convolutional neural networks (CNNs) have been widely applied for image recognition, face detection, and video analysis because of their ability to achieve accuracy close to or even better than human level perception. However, different features of convolution layers and fully connected layers have brought many challenges to the implementation of CNN on FPGA platforms, because different accelerator...
The Intrusion Detection Systems (IDS) is becoming important and quite timing/space consuming due to the increasing volume of explosive data flood. During the past decades, there have been plenty of studies proposing software mechanisms to exploit the temporal locality in the IDS systems. However, it requires considerable memory blocks to store the redundancy table, therefore, the performance as well...
As a traditional algorithm, the string match meets a challenge with the development of the massive volume of data be-cause of gene sequencing. Surveys show that there will be a huge amount of short read segments during the process of gene sequencing and the need for a highly efficient is urgent. The BWA is an effective algorithm to deal with the short read mapping. Compared with other short read mapping...
It has been a new research hot topic to speed up the inference process of deep neural networks (DNNs) by hardware accelerators based on field programmable gate arrays (FPGAs). Because of the layer-wise structure and data dependency between layers, previous studies commonly focus on the inherent parallelism of a single layer to reduce the computation time but neglect the parallelism between layers...
String matching has become essential and widely applied in modern computer applications, especially with explosive data scale. As a classic fast and exact single pattern matching algorithm, Knuth-Morris-Pratt (KMP) algorithm has been demonstrated in network security and computational biology. However, with the increasing amount of data in the modern society, it becomes increasing important and essential...
Neighborhood-based Collaborative Filtering (CF) is a kind of techniques in the field of recommendation algorithms and has been widely used in lots of personalized recommender systems. In the big data era, the increasing data amounts make these CF recommendation algorithms become time-consuming and energy-wasted. At present, Cloud computing and Graphic Processing Unit (GPU) are the two major platforms...
Recently, machine learning is widely used in applications and cloud services. And as the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. To give users better experience, high performance implementations of deep learning applications seem very important. As a common means to accelerate algorithms, FPGA has high performance, low power consumption,...
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