Publication
Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 2017
Taking advantage of recently released hybrid multicore architectures, such as the Intel Xeon+FPGA machine, where the FPGA has coherent access to the main memory through the QPI bus, we explore the benefits of specializing operators to hardware. We focus on two commonly used SQL operators for strings: LIKE, and REGEXP_LIKE, and provide a novel and efficient implementation of these operators in reconfigurable hardware. We integrate the hardware accelerator into MonetDB, a main-memory column store, and demonstrate a significant improvement in response time and throughput. Our Hardware User Defined Function (HUDF) can speed up complex pattern matching by an order of magnitude in comparison to the database running on a 10-core CPU. The insights gained from integrating hardware based string operators into MonetDB should also be useful for future designs combining hardware specialization and databases.
@inproceedings{abc, abstract = {Taking advantage of recently released hybrid multicore architectures, such as the Intel Xeon+FPGA machine, where the FPGA has coherent access to the main memory through the QPI bus, we explore the benefits of specializing operators to hardware. We focus on two commonly used SQL operators for strings: LIKE, and REGEXP_LIKE, and provide a novel and efficient implementation of these operators in reconfigurable hardware. We integrate the hardware accelerator into MonetDB, a main-memory column store, and demonstrate a significant improvement in response time and throughput. Our Hardware User Defined Function (HUDF) can speed up complex pattern matching by an order of magnitude in comparison to the database running on a 10-core CPU. The insights gained from integrating hardware based string operators into MonetDB should also be useful for future designs combining hardware specialization and databases.}, author = {David Sidler and Zsolt Istv{\'a}n and Muhsen Owaida and Gustavo Alonso}, booktitle = {Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017}, title = {Accelerating Pattern Matching Queries in Hybrid CPU-FPGA Architectures.}, url = {http://doi.acm.org/10.1145/3035918.3035954}, venue = {Chicago, IL, USA}, year = {2017} }