Mitchell Nelson's Paper Presented at Computing Conference
CISC student Mitchell Nelson's paper was recently presented at the IEEE ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2019) by co-author and CISC Assistant Professor Dr. Joe Myre. The paper detailed joint research conducted by Mitchell Nelson and Dr. Joe Myre, as well as CISC alumn Zachary Sorenson, CISC Associate Professor Dr. Jason Sawin, and Associate Professior of Computer Science at the University of Puget Sound Dr. David Chiu.
This paper, available here, was also nominated for best paper at the conference.
Title and abstract are below:
GPU Acceleration of Range Queries over Large Data Sets
Data management systems commonly use bitmap indices to increase the efficiency of querying scientific data. Bitmaps are usually highly compressible and can be queried directly using fast hardware-supported bitwise logical operations. The processing of bitmap queries is inherently parallel in structure, which suggests they could benefit from concurrent computer systems. In particular, bitmap-range queries offer a highly parallel computational problem, and the hardware features of graphics processing units (GPUs) offer an alluring platform for accelerating their execution. In this paper, we present three GPU algorithms and one CPU based algorithm for the parallel execution of bitmap-range queries. We show that in 95% of our tests, using real and synthetic data, the GPU algorithms greatly outperform the parallel CPU algorithm. For these tests, the GPU algorithms provide up to 87.7× speedup and an average speedup of 30.22× over the parallel CPU algorithm. In addition to enhancing performance, augmenting traditional bitmap query systems with GPUs to offload bitmap query processing allows the CPU to process other requests