A real-time GPU-accelerated parallelized image processor for large-scale multiplexed fluorescence microscopy data by Guolan Lu, Guolan Lu, Guolan Lu, Marc A. Baertsch, Marc A. Baertsch, Marc A. Baertsch, John W. Hickey, John W. Hickey, Yury Goltsev, Yury Goltsev, Andrew J. Rech, Andrew J. Rech, Lucas Mani, Erna Forgó, Christina Kong, Sizun Jiang, Garry P. Nolan, Garry P. Nolan, Eben L. Rosenthal, Eben L. Rosenthal

“…Incorporation of an open source CUDA-driven, GPU-assisted deconvolution produced results similar to fee-based commercial software. …”
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Highly efficient fluid-solid coupled incompressible SPH simulation method for atherosclerotic plaque generation(动脉粥样硬化斑块生成的高效流固耦合不可压缩SPH模拟方法)... by 汪飞(WANG Fei), 汪飞(WANG Fei), 汪飞(WANG Fei), 汪飞(WANG Fei), 汪飞(WANG Fei), 汪飞(WANG Fei)

“…为使模拟结果能够实时呈现，用统一计算设备架构（compute unified device architecture，CUDA）实现并行加速计算。方法实现了对血液中斑块生成的快速模拟，避免了用偏微分方程模型模拟带来的高计算量；同时能较真实地模拟斑块生成过程并体现血液与斑块的流固耦合作用；最后逼真展现了斑块模拟的渲染结果。…”
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High performance simulation of drug release model and mass transport model by using hybrid platform by Ali, Akhtar

“…Furthermore, the motivation for using GPU accelerators with CUDA is explained to handle computational complexities. …”
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Panicle-SEG: a robust image segmentation method for rice panicles in the field based on deep learning and superpixel optimization by Xiong Xiong, Lingfeng Duan, Lingbo Liu, Haifu Tu, Peng Yang, Dan Wu, Guoxing Chen, Lizhong Xiong, Wanneng Yang, Qian Liu

“…Meanwhile, the executing speed is also improved when combined with multithreading and CUDA parallel acceleration. Moreover, Panicle-SEG was demonstrated to be a robust segmentation algorithm, which can be expanded for different rice accessions, different field environments, different camera angles, different reproductive stages, and indoor rice images. …”
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Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision by Abu Raid, Fadi Imad Osman

“…These algorithms are then parallelized using Compute Unified Device Architecture CUDA C language to run on Graphics Processing Unit GPU for hardware acceleration. …”
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Model-based markerless human motion capture from multiple camera sequences by Zhang, Zheng.

“…The requirement of real-time processing motivates us to accelerate the tracking by implementing time-consuming steps on GPU using CUDA. Benefiting from the massive parallelism of GPU, our method is capable of tracking full body movements robustly and efficiently.…”
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Efficient agglomerative hierarchical clustering for biological sequence analysis by Nguyen, Thuy Diem

“…I have developed two OTU clustering pipelines for 454 pyrosequencing datasets called CRiSPy-Embed and CRiSPy-CUDA. A comprehensive evaluation benchmark using randomly simulated datasets and popular mock datasets has been designed to test the performance of these pipelines against existing tools. …”
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Multiple-Relaxation-Time Lattice Boltzmann Simulation of Soret and Dufour Effects on the Thermosolutal Natural Convection of a Nanofluid in a U-Shaped Porous Enclosure by Md. Mahadul Islam, Md Farhad Hasan, Md. Mamun Molla

“…The benchmark results thoroughly validate the graphics process unit (GPU) based in-house compute unified device architecture (CUDA) C/C++ code. Numeral simulations were performed for a variety of dimensionless variables, including the Rayleigh number, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>a</mi></mrow></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mn>10</mn><mn>4</mn></msup><mo>,</mo><msup><mn>10</mn><mn>5</mn></msup><mo>,</mo><msup><mn>10</mn><mn>6</mn></msup></mrow></semantics></math></inline-formula>), the Darcy number, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>D</mi><mi>a</mi></mrow></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mn>10</mn><mrow><mo>−</mo><mn>2</mn></mrow></msup><mo>,</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>3</mn></mrow></msup><mo>,</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>4</mn></mrow></msup></mrow></semantics></math></inline-formula>), the Soret number, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>S</mi><mi>r</mi></mrow></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.0</mn><mo>,</mo><mn>0.1</mn><mo>,</mo><mn>0.2</mn></mrow></semantics></math></inline-formula>), the Dufour number, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>D</mi><mi>f</mi></msub></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.0</mn><mo>,</mo><mn>0.1</mn><mo>,</mo><mn>0.2</mn></mrow></semantics></math></inline-formula>), the buoyancy ratio, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>−</mo><mn>2</mn><mo>≤</mo><mi>B</mi><mi>r</mi><mo>≤</mo><mn>2</mn></mrow></semantics></math></inline-formula>), the Lewis number, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>L</mi><mi>e</mi></mrow></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>,</mo><mn>3</mn><mo>,</mo><mn>5</mn></mrow></semantics></math></inline-formula>), the volume fraction, (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0</mn><mo>≤</mo><mi>ϕ</mi><mo>≤</mo><mn>0.04</mn></mrow></semantics></math></inline-formula>), and the porosity, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ϵ</mi></semantics></math></inline-formula> = (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.2</mn><mo>−</mo><mn>0.8</mn></mrow></semantics></math></inline-formula>), and the Prandtl number, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>r</mi></mrow></semantics></math></inline-formula> = <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>6.2</mn></mrow></semantics></math></inline-formula> (water) is fixed to represent the base fluid. …”
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