TY - JOUR
T1 - Marine bathymetry processing through GPGPU virtualization in high performance cloud computing
AU - Montella, Raffaele
AU - Marcellino, Livia
AU - Galletti, Ardelio
AU - Di Luccio, Diana
AU - Kosta, Sokol
AU - Laccetti, Giuliano
AU - Giunta, Giulio
N1 - doi: 10.1002/cpe.4895
PY - 2018/9/12
Y1 - 2018/9/12
N2 - Summary Fast technology development has influenced the widespread use of low-power devices in different scientific, environmental, and everyday life areas, giving birth to the Internet of Things. In this paper, we focus on the context of marine studies, addressing the problem of marine bathymetry data processing and analysis via pervasive and Internet-connected sensors and low-power distributed devices. Pervasive and Internet-connected low-power devices (as the components involved in the sensing and processing actions) made diverse and different ?things? as a worldwide-distributed system. Given the high complexity of the algorithms involved in these studies, which usually involve general-purpose graphic processing unit (GPGPU) computation, it is impossible for the limited devices to perform the required calculations. To overcome these limitations, in this paper, we propose and implement a vertical application of GVirtuS, the open-source GPGPU virtualization and remoting service, for achieving high performance geographical data interpolation in a high performance cloud computing scenario. We present an innovative implementation by comparing, in terms of performance and accuracy, the inverse distance weighting and kriging interpolation methods in their parallel implementations leveraging on CUDA-enabled GPGPUs. We present a real-world use case related to high-resolution bathymetry interpolation in a crowdsource data context in the Bay of Pozzuoli, Italy.
AB - Summary Fast technology development has influenced the widespread use of low-power devices in different scientific, environmental, and everyday life areas, giving birth to the Internet of Things. In this paper, we focus on the context of marine studies, addressing the problem of marine bathymetry data processing and analysis via pervasive and Internet-connected sensors and low-power distributed devices. Pervasive and Internet-connected low-power devices (as the components involved in the sensing and processing actions) made diverse and different ?things? as a worldwide-distributed system. Given the high complexity of the algorithms involved in these studies, which usually involve general-purpose graphic processing unit (GPGPU) computation, it is impossible for the limited devices to perform the required calculations. To overcome these limitations, in this paper, we propose and implement a vertical application of GVirtuS, the open-source GPGPU virtualization and remoting service, for achieving high performance geographical data interpolation in a high performance cloud computing scenario. We present an innovative implementation by comparing, in terms of performance and accuracy, the inverse distance weighting and kriging interpolation methods in their parallel implementations leveraging on CUDA-enabled GPGPUs. We present a real-world use case related to high-resolution bathymetry interpolation in a crowdsource data context in the Bay of Pozzuoli, Italy.
KW - geographic data interpolation
KW - GPGPU virtualization
KW - high performance computing
KW - IDW
KW - kriging
UR - http://www.scopus.com/inward/record.url?scp=85053404209&partnerID=8YFLogxK
U2 - 10.1002/cpe.4895
DO - 10.1002/cpe.4895
M3 - Journal article
SN - 1532-0626
VL - 30
JO - Concurrency and Computation: Practice & Experience
JF - Concurrency and Computation: Practice & Experience
IS - 24
M1 - e4895
ER -