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    Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

    Source: Journal of Computing and Information Science in Engineering:;2013:;volume( 013 ):;issue: 003::page 31002
    Author:
    Bista, Sujal
    ,
    Chowdhury, Sagar
    ,
    Gupta, Satyandra K.
    ,
    Varshney, Amitabh
    DOI: 10.1115/1.4023862
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Laser beams can be used to create optical traps that can hold and transport small particles. Optical trapping has been used in a number of applications ranging from prototyping at the microscale to biological cell manipulation. Successfully using optical tweezers requires predicting optical forces on the particle being trapped and transported. Reasonably accurate theory and computational models exist for predicting optical forces on a single particle in the close vicinity of a Gaussian laser beam. However, in practice the workspace includes multiple particles that are manipulated using individual optical traps. It has been experimentally shown that the presence of a particle can cast a shadow on a nearby particle and hence affect the optical forces acting on it. Computing optical forces in the presence of shadows in realtime is not feasible on CPUs. In this paper, we introduce a raytracingbased application optimized for GPUs to calculate forces exerted by the laser beams on microparticle ensembles in an optical tweezers system. When evaluating the force exerted by a laser beam on 32 interacting particles, our GPUbased approach is able to get a 66fold speed up compared to a single core CPU implementation of traditional Ashkin's approach and a 10fold speedup over the single core CPUbased implementation of our approach.
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      Using GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles

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    http://yetl.yabesh.ir/yetl1/handle/yetl/151227
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    contributor authorBista, Sujal
    contributor authorChowdhury, Sagar
    contributor authorGupta, Satyandra K.
    contributor authorVarshney, Amitabh
    date accessioned2017-05-09T00:57:10Z
    date available2017-05-09T00:57:10Z
    date issued2013
    identifier issn1530-9827
    identifier otherjcis_13_3_031002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/151227
    description abstractLaser beams can be used to create optical traps that can hold and transport small particles. Optical trapping has been used in a number of applications ranging from prototyping at the microscale to biological cell manipulation. Successfully using optical tweezers requires predicting optical forces on the particle being trapped and transported. Reasonably accurate theory and computational models exist for predicting optical forces on a single particle in the close vicinity of a Gaussian laser beam. However, in practice the workspace includes multiple particles that are manipulated using individual optical traps. It has been experimentally shown that the presence of a particle can cast a shadow on a nearby particle and hence affect the optical forces acting on it. Computing optical forces in the presence of shadows in realtime is not feasible on CPUs. In this paper, we introduce a raytracingbased application optimized for GPUs to calculate forces exerted by the laser beams on microparticle ensembles in an optical tweezers system. When evaluating the force exerted by a laser beam on 32 interacting particles, our GPUbased approach is able to get a 66fold speed up compared to a single core CPU implementation of traditional Ashkin's approach and a 10fold speedup over the single core CPUbased implementation of our approach.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleUsing GPUs for Realtime Prediction of Optical Forces on Microsphere Ensembles
    typeJournal Paper
    journal volume13
    journal issue3
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4023862
    journal fristpage31002
    journal lastpage31002
    identifier eissn1530-9827
    treeJournal of Computing and Information Science in Engineering:;2013:;volume( 013 ):;issue: 003
    contenttypeFulltext
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