Zhehao Li

Learning Sparse Approximate Inverse Preconditioners for Conjugate Gradient Solvers on GPUs

Zhehao Li, Yixuan Li, Tao Du, Ligang Liu

The conjugate gradient solver (CG) is a prevalent method for solving symmetric and positive definite linear systems Ax=b, where effective preconditioners are crucial for fast convergence. Traditional preconditioners rely on prescribed algorithms to offer rigorous theoretical guarantees, while limiting their ability to …

Imaging deep seafloor structures with reflection data from a low-energy and short-streamer seismic survey in the South Atlantic Ocean

Zhehao Li, Hua‐Wei Zhou, Boming Wu, Zhongmin Tao et autres

Abstract The growth of seismic surveys using small airgun sources and short streamers has significantly reduced the costs and environmental impacts, but may limit the quality of reflection images. Using a 2D deep marine reflection survey in the South Atlantic with two …

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Characterization and phylogenetic implications of the mitochondrial genomes of the Phyllidiidae (Gastropoda, Nudibranchia) from the South China Sea

Gang Ni, Zhehao Li, Zhi Hao Chen, Chaojie Yang et autres

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A study on bubble suppression for deep marine reflection data acquired by a small airgun array

Zhehao Li, Hua‐Wei Zhou, Guangkai Ma, Dongdi Cai et autres

Abstract The oscillatory bubble pulses generated by airguns in seawater are known to produce artefacts in seismic images. Although such artefacts are suppressible by employing larger airgun arrays in acquisition, small airgun arrays are used more often now to minimize the environmental …

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The complete mitochondrial genome of sea slug phyllidia elegans bergh, 1869 (nudibranchia, phyllidiidae) from the South China sea

Zhehao Li, Xiaoqi Zeng, Gang Ni

In this study, the complete mitochondrial genome (mitogenome) sequence of sea slug, Phyllidia elegans Bergh, 1869 (Nudibranchia, Phyllidiidae), was sequenced and characterized. The assembled mitogenome was 14618 bp in length, including 13 protein-coding genes (PCGs), two ribosomal RNA genes, and 22 transfer …

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Separation of simultaneous source wavefields using convolutional neural network

Zhehao Li, Hua‐Wei Zhou, Kang Fu

Simultaneous source acquisition significantly reduces the acquisition time and cost in comparison with conventional single source acquisition. However, the blended data require deblending to separate them into that equivalent of the single source wavefield. In this work, we devise a denoising based …

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PerfEstimator: A Generic and Extensible Performance Estimator for Data Parallel DNN Training

Chengru Yang, Zhehao Li, Chaoyi Ruan, Guanbin Xu et autres

Understanding the performance of data parallel DNN training at large-scale is crucial for supporting efficient DNN cloud deployment as well as facilitating the design and optimization of scalable DNN systems. Existing works adopt analytical modeling, which may fall short in capturing the …

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Assessing the source radiation pattern (SRP) of onshore seismic data: Preliminary results

Hua‐Wei Zhou, Heng Zhou, Boming Wu, Zhehao Li

The source radiation pattern (SRP) in seismology defines the directional dependence of the magnitude of the seismic energy radiated from a seismic source. An SRP depends on the properties of both the exciting shot and the source volume (SV) upon which the …

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A scalable hybrid architecture for high performance data-parallel applications

Moucheng Yang, Jifang Jin, Zhehao Li, Xuegong Zhou et autres

This paper presents a scalable hybrid architecture for high performance data-parallel applications on tightly coupled shared-memory CPU-FPGA systems such as the Xilinx Zynq SoC. The aims of the proposed architecture are: 1)to simplify the development of hardware acceleration for dataparallel applications; 2)to …

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A moving object extraction and classification system based on Zynq and IBM SuperVessel

Zhehao Li, Jifang Jin, Lingli Wang, Ji Yang et autres

In this demonstration, we develop a moving object extraction and classification system based on a heterogeneous acceleration platform that consists of a local Zynq terminal and FPGA clusters on the IBM SuperVessel cloud. Extraction of the moving object from the streaming video …

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K-nearest neighbor algorithm implementation on FPGA using high level synthesis

Zhehao Li, Jifang Jin, Xuegong Zhou, Zhihua Feng

The K-Nearest Neighbor (K-NN) algorithm is one of the most common classification algorithms and widely used in pattern recognition and data mining. K-NN hardware acceleration is necessary for applications with massive high-dimensional data. High level synthesis (HLS) is an increasingly adopted technique …

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