Improving the performance of GPU-accelerated spatial joins
Abstract: Data collisions have been widely studied by various fields of science and industry. Combing CPU and GPU for processing spatial joins has been broadly accepted due to the increased speed of computations. This should redirect efforts in GPGPU research from straightforward porting of applications to establishing principles and strategies that allow efficient mapping of computation to graphics hardware. As threads are executing instructions while using hardware resources that are available, impact of different thread organizations and their effect on spatial join performance is analyzed and examined in this report.Having new perspectives and solutions to the problem of thread organization and warp scheduling may contribute more to encourage others to program on the GPU side. The aim with this project is to examine the impact of different thread organizations in spatial join processes. The relationship between the items inside datasets are examined by counting the number of collisions their join produce in order to understand how different approaches may have an influence on performance. Performance benchmarking, analysis and measuring of different approaches in thread organization are investigated and analyzed in this report in order to find the most time efficient solution which is the purpose of the conducted work.This report shows the obtained results for the utilization of different thread techniques in order to optimize the computational speeds of the spatial join algorithms. There are two algorithms on the GPU, one implementing thread techniques and the other non-optimizing solution. The GPU times are compared with the execution times on the CPU and the GPU implementations are verified by observing the collision counters that are matching with all of the collision counters from the CPU counterpart.In the analysis part of this report the the implementations are discussed and compared to each other. It has shown that the difference between algorithm implementing thread techniques and the non-optimizing one lies around 80% in favour of the algorithm implementing thread techniques and it is also around 56 times faster then the spatial joins on the CPU.
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