Chengpeng Xia

University of Otago · Department of Computer Science

Deep Neural Networks (DNNs) have demonstrated great success in many fields such as image recognition and text analysis. However, the ever-increasing sizes of both DNN models and training datasets make deep leaning extremely computation- and memory-intensive. Recently, photonic computing has emerged as a promising technology for accelerating DNNs. W...

Multi-layer perceptron (MLP) is a class of Artificial Neural Networks widely used in regression, classification, and prediction. To accelerate the training of MLP, more cores can be used for parallel computing on many-core systems. However, with the increasing number of cores integrated into the chip, the communication bottleneck in the training of...

Blockchain has been applied in wide range of fields to guarantee security. However, it has been very challenging for blockchain to flourish in mobile environment with limited resources. Existing studies mainly assume that single mobile user can buy the whole resources from edge servers in mobile blockchain. This paper formulates the problem of maxi...

There are many influence factors and characterization indexes for the processing effect of laser shock peening (LSP) on metal materials, and the influence mechanism is complex. The FGH95 superalloy used for turbine disk manufacturing was taken as the research object in this paper. Taking the laser energy, beam diameter and the number of impacts as...

As a metal surface strengthening technology, oblique laser shock peening uses the force effect of pulsed laser beams to significantly improve the mechanical properties of materials and prolong service life. However, the processing of metal parts still requires a high cost for testing the quality of the finished product. At present, there is no syst...

Conventional electronic Artificial Neural Networks (ANNs) accelerators focus on architecture design and numerical computation optimization to improve the training speed. Optical technology with low energy consumption and high transmission speed are expected to play an important role in the next generation of computing architectures. To provide a be...

Conventional electronic Artificial Neural Networks (ANNs) accelerators focus on architecture design and numerical computation optimization to improve the training efficiency. However, these approaches have recently encountered bottlenecks in terms of energy efficiency and computing performance, which leads to an increase interest in photonic accele...

Blockchain has been widely applied in various fields, such as finance, Internet of Things, law, etc. However, it is a challenge to apply blockchain to mobile applications, as some mobile devices cannot afford computing resources required by the mining processes. Therefore, edge computing is introduced to provide computing resources for mobile devic...