Toward automatic parallelization of spatial computation for computing clusters
Baoqiang Yan, Philip J. Rhodes · 2008
High performance parallel computing infrastructures, such as computing clusters, have recently become freely available for scientific researchers to solve problems of unprecedented scale through data parallelization. However scientists are not necessarily skilled in writing efficient parallel code, especially when dealing with spatial datasets. Two important performance issues involved are the heavy I/O costs and the communication overhead. To address this issue, we are developing an scheme that helps scientists realize I/O friendly and scalable data parallelization for spatial computation.