OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures
Driven by the rapid hardware development of parallel CPU/GPU architectures, we have witnessed emerging relational query processing techniques and implemen- tations on those parallel architectures. However, most of those implementations are not portable across di erent architectures, because...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/10356/55094 |
| _version_ | 1826118809583353856 |
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| author | Zhang, Shuhao |
| author2 | He Bingsheng |
| author_facet | He Bingsheng Zhang, Shuhao |
| author_sort | Zhang, Shuhao |
| collection | NTU |
| description | Driven by the rapid hardware development of parallel CPU/GPU architectures,
we have witnessed emerging relational query processing techniques and implemen-
tations on those parallel architectures. However, most of those implementations
are not portable across di erent architectures, because they are usually devel-
oped from scratch and target at a speci c architecture. This project proposes a
kernel-adapter based design (OmniDB), a portable yet e cient query processor
on parallel CPU/GPU architectures. OmniDB attempts to develop an extensible
query processing kernel (qKernel) based on an abstract model for parallel archi-
tectures, and to leverage an architecture-speci c layer (adapter) to make qKernel
be aware of the target architecture. The goal of OmniDB is to maximize the com-
mon functionality in qKernel so that the development and maintenance e orts for
adapters are minimized across di erent architectures. In this project, we demon-
strate our initial e orts in implementing OmniDB, and present the preliminary
results on the portability and e ciency. |
| first_indexed | 2024-10-01T04:49:34Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/55094 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:49:34Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/550942023-03-03T20:33:27Z OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures Zhang, Shuhao He Bingsheng School of Computer Engineering Parallel and Distributed Computing Centre DRNTU::Engineering::Computer science and engineering Driven by the rapid hardware development of parallel CPU/GPU architectures, we have witnessed emerging relational query processing techniques and implemen- tations on those parallel architectures. However, most of those implementations are not portable across di erent architectures, because they are usually devel- oped from scratch and target at a speci c architecture. This project proposes a kernel-adapter based design (OmniDB), a portable yet e cient query processor on parallel CPU/GPU architectures. OmniDB attempts to develop an extensible query processing kernel (qKernel) based on an abstract model for parallel archi- tectures, and to leverage an architecture-speci c layer (adapter) to make qKernel be aware of the target architecture. The goal of OmniDB is to maximize the com- mon functionality in qKernel so that the development and maintenance e orts for adapters are minimized across di erent architectures. In this project, we demon- strate our initial e orts in implementing OmniDB, and present the preliminary results on the portability and e ciency. Bachelor of Engineering (Computer Engineering) 2013-12-12T06:41:56Z 2013-12-12T06:41:56Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/55094 en Nanyang Technological University 34 p. application/pdf application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Zhang, Shuhao OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title | OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title_full | OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title_fullStr | OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title_full_unstemmed | OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title_short | OMNIDB towards portable and efficient query processing on parallel CPU/GPU architectures |
| title_sort | omnidb towards portable and efficient query processing on parallel cpu gpu architectures |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/55094 |
| work_keys_str_mv | AT zhangshuhao omnidbtowardsportableandefficientqueryprocessingonparallelcpugpuarchitectures |