15 papers · ranked by Valyu relevance
Gang Mei, Nengxiong Xu, Liangliang Xu
This paper presents an efficient parallel Adaptive Inverse Distance Weighting (AIDW) interpolation algorithm on modern Graphics Processing Unit (GPU). The presented algorithm is an improvement of our previous GPU-accelerated AIDW algorithm by adopting fast k-nearest neighbors (kNN) search. In AIDW, it needs to find…
Xuan Zuo, Hui-Yan Li, Shan Gao, Pu Zhang + 2 more
Adaptive gradient algorithms have been successfully used in deep learning. Previous work reveals that adaptive gradient algorithms mainly borrow the moving average idea of heavy ball acceleration to estimate the first- and second-order moments of the gradient for accelerating convergence. However, Nesterov acceleration…
Michael Muehlebach, Michael I. Jordan
We exploit analogies between first-order algorithms for constrained optimization and non-smooth dynamical systems to design a new class of accelerated first-order algorithms for constrained optimization. Unlike Frank-Wolfe or projected gradients, these algorithms avoid optimization over the entire feasible set at each…
Guoqing Lei, Yong Dou, Wen Wan, Fei Xia + 3 more
'Dan Zou'] Background Prediction of ribonucleic acid (RNA) secondary structure remains one of the most important research areas in bioinformatics. The Zuker algorithm is one of the most popular methods of free energy minimization for RNA secondary structure prediction. Thus far, few studies have been reported on the…
Yun-gang Luo, Ping Liu, Lin Shi, Yishan Luo + 6 more
'Jing Qin' 'Pheng-Ann Heng' 'Defeng Wang' 'Dzung Pham'] Neuroimage registration is crucial for brain morphometric analysis and treatment efficacy evaluation. However, existing advanced registration algorithms such as FLIRT and ANTs are not efficient enough for clinical use. In this paper, a GPU implementation of FLIRT…
Xin Wang, Bin Zhang, Xu Cao, Fei Liu + 2 more
Fluorescence molecular tomography (FMT) with early-photons can improve the spatial resolution and fidelity of the reconstructed results. However, its computing scale is always large which limits its applications. In this paper, we introduced an acceleration strategy for the early-photon FMT with graphics processing…
Bo Wei, Chuanlin He, Siyu Xing, Yi Zheng + 1 more
High-accuracy level underwater acoustical surveying plays an important role in ocean engineering applications, such as subaqueous tunnel construction, oil and gas exploration, and resources prospecting. This novel imaging method is eager to break through the existing theory to achieve a higher accuracy level of…
Pranay Reddy Kommera, Vinay Ramakrishnaiah, Christine Sweeney, Jeffrey Donatelli + 1 more
'Jeffrey Donatelli' 'Petrus H. Zwart'] The paper presents efforts to accelerate the multitiered iterative phasing (MTIP) algorithm on contemporary graphics processing units (GPUs). Application portability is demonstrated by accelerating the MTIP algorithm on NVIDIA and AMD GPUs using a single codebase.
Evert van Aart, Neda Sepasian, Andrei Jalba, Anna Vilanova
Diffusion Tensor Imaging (DTI) allows to noninvasively measure the diffusion of water in fibrous tissue. By reconstructing the fibers from DTI data using a fiber-tracking algorithm, we can deduce the structure of the tissue. In this paper, we outline an approach to accelerating such a fiber-tracking algorithm using a…
Balaji Venkatachalam, Dan Gusfield, Yelena Frid
Background The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n3) time using Nussinov’s dynamic programming algorithm. The Four-Russians method is a technique that reduces the running time for certain dynamic…
Hasan Erdem Yantır, Ahmed M. Eltawil, Khaled N. Salama
The traditional computer architectures severely suffer from the bottleneck between the processing elements and memory that is the biggest barrier in front of their scalability. Nevertheless, the amount of data that applications need to process is increasing rapidly, especially after the era of big data and artificial…
Diego González, Guillermo Botella, Uwe Meyer-Baese, Carlos García + 3 more
'Concepción Sanz' 'Manuel Prieto-Matías' 'Francisco Tirado'] This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching…
Daehyun Kim, Joshua Trzasko, Mikhail Smelyanskiy, Clifton Haider + 2 more
'Pradeep Dubey' 'Armando Manduca'] Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However…
Jonas Latt, Christophe Coreixas, Joël Beny, Fang-Bao Tian
We present a novel, hardware-agnostic implementation strategy for lattice Boltzmann (LB) simulations, which yields massive performance on homogeneous and heterogeneous many-core platforms. Based solely on C++17 Parallel Algorithms, our approach does not rely on any language extensions, external libraries…
Marco Bassoli, Valentina Bianchi, Ilaria De Munari
Recent research in wearable sensors have led to the development of an advanced platform capable of embedding complex algorithms such as machine learning algorithms, which are known to usually be resource-demanding. To address the need for high computational power, one solution is to design custom hardware platforms…