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Today, artificial neural networks (ANNs) are widely used in a variety of applications, including speech recognition, face detection, disease diagnosis, etc. And as the emerging field of ANNs, Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) which contains complex computational logic. To achieve high accuracy, researchers always build large-scale LSTM networks which are time-consuming...
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...
The next generation genome sequencing problem with short (long) reads is an emerging field in numerous scientific and big data research domains. However, data sizes and ease of access for scientific researchers are growing and most current methodologies rely on one acceleration approach and so cannot meet the requirements imposed by explosive data scales and complexities. In this paper, we propose...
Phase detection and behavior analysis have been major concerned to improve the performance as well as the system throughputs. However, for the distributed acceleration engines, the execution among different phases is much more difficult to be analyzed, especially for the loop based programs. With respect to the tasks in different iterations, how to efficiently detect the phases belonging to the same...
The developing semiconductor technology enables the reconfigurable hardware such as FPGA. Distributed reconfigurable system is a FPGA-based hardware accelerated system with network. Applications can be accelerated as hardware module by FPGA in a distributed system. There are few works about application mapping on distributed reconfigurable system. In this paper an application mapping scheme for reconfigurable...
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