TY - GEN
T1 - Distributed in-GPU data cache for document-oriented data store via PCIe over 10 Gbit ethernet
AU - Morishima, Shin
AU - Matsutani, Hiroki
N1 - Funding Information:
This work was partially supported by Grant-in-Aid for JSPS Research Fellow. H. Matsutani was supported in part by JST PRESTO.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - As one of NOSQL data stores, a document-oriented data store manages data as documents in a scheme-less manner. Various string match queries, such as a perfect match, begins-with (prefix) match, partial match, and regular expression based match, are performed for the documents. To accelerate such string match queries, we propose DistGPU Cache (Distributed In-GPU Data Cache), in which data store server and GPU devices are connected via a PCI-Express (PCIe) over 10 Gbit Ethernet (10 GbE), so that GPU devices that store and search documents can be added and removed dynamically. We also propose a partitioning method that distributes ranges of cached documents to GPU devices based on a hash function. The distributed cache over GPU devices can be dynamically divided and merged when the GPU devices are added and removed, respectively. We evaluate the proposed DistGPU Cache in terms of regular expression match query throughput with up to three NVIDIA GeForce GTX 980 devices connected to a host via PCIe over 10 GbE. We demonstrate that the communication overhead of remote GPU devices is small and can be compensated by a great flexibility to add more GPU devices via a network. We also show that DistGPU Cache with the remote GPU devices significantly outperforms the original data store.
AB - As one of NOSQL data stores, a document-oriented data store manages data as documents in a scheme-less manner. Various string match queries, such as a perfect match, begins-with (prefix) match, partial match, and regular expression based match, are performed for the documents. To accelerate such string match queries, we propose DistGPU Cache (Distributed In-GPU Data Cache), in which data store server and GPU devices are connected via a PCI-Express (PCIe) over 10 Gbit Ethernet (10 GbE), so that GPU devices that store and search documents can be added and removed dynamically. We also propose a partitioning method that distributes ranges of cached documents to GPU devices based on a hash function. The distributed cache over GPU devices can be dynamically divided and merged when the GPU devices are added and removed, respectively. We evaluate the proposed DistGPU Cache in terms of regular expression match query throughput with up to three NVIDIA GeForce GTX 980 devices connected to a host via PCIe over 10 GbE. We demonstrate that the communication overhead of remote GPU devices is small and can be compensated by a great flexibility to add more GPU devices via a network. We also show that DistGPU Cache with the remote GPU devices significantly outperforms the original data store.
UR - http://www.scopus.com/inward/record.url?scp=85020405798&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020405798&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-58943-5_4
DO - 10.1007/978-3-319-58943-5_4
M3 - Conference contribution
AN - SCOPUS:85020405798
SN - 9783319589428
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 41
EP - 55
BT - Euro-Par 2016
A2 - Dutot, Pierre-Francois
A2 - Desprez, Frederic
PB - Springer Verlag
T2 - 22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016
Y2 - 24 August 2016 through 26 August 2016
ER -