Title:
Acceleration and execution of relational queries using general purpose graphics processing unit (GPGPU)
Acceleration and execution of relational queries using general purpose graphics processing unit (GPGPU)
| dc.contributor.advisor | Yalamanchili, Sudhakar | |
| dc.contributor.author | Wu, Haicheng | |
| dc.contributor.committeeMember | Kim, Hyesoon | |
| dc.contributor.committeeMember | Wills, Linda | |
| dc.contributor.committeeMember | Vuduc, Richard | |
| dc.contributor.committeeMember | Pande, Santosh | |
| dc.contributor.department | Electrical and Computer Engineering | |
| dc.date.accessioned | 2016-01-07T17:36:04Z | |
| dc.date.available | 2016-01-07T17:36:04Z | |
| dc.date.created | 2015-12 | |
| dc.date.issued | 2015-11-16 | |
| dc.date.submitted | December 2015 | |
| dc.date.updated | 2016-01-07T17:36:04Z | |
| dc.description.abstract | This thesis first maps the relational computation onto Graphics Processing Units (GPU)s by designing a series of tools and then explores the different opportunities of reducing the limitation brought by the memory hierarchy across the CPU and GPU system. First, a complete end-to-end compiler and runtime infrastructure, Red Fox, is proposed. The evaluation on the full set of industry standard TPC-H queries on a single node GPU shows on average Red Fox is 11.20x faster compared with a commercial database system on a state of art CPU machine. Second, a new compiler technique called kernel fusion is designed to fuse the code bodies of several relational operators to reduce data movement. Third, a multi-predicate join algorithm is designed for GPUs which can provide much better performance and be used with more flexibility compared with kernel fusion. Fourth, the GPU optimized multi-predicate join is integrated into a multi-threaded CPU database runtime system that supports out-of-core data set to solve real world problem. This thesis presents key insights, lessons learned, measurements from the implementations, and opportunities for further improvements. | |
| dc.description.degree | Ph.D. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/54405 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Database | |
| dc.subject | GPU | |
| dc.title | Acceleration and execution of relational queries using general purpose graphics processing unit (GPGPU) | |
| dc.type | Text | |
| dc.type.genre | Dissertation | |
| dspace.entity.type | Publication | |
| local.contributor.corporatename | School of Electrical and Computer Engineering | |
| local.contributor.corporatename | College of Engineering | |
| relation.isOrgUnitOfPublication | 5b7adef2-447c-4270-b9fc-846bd76f80f2 | |
| relation.isOrgUnitOfPublication | 7c022d60-21d5-497c-b552-95e489a06569 | |
| thesis.degree.level | Doctoral |