Publications by Jana Giceva

×

Status message

The Publications site is currently under construction, as a result some publications might be missing.

2017

Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 2017
@inproceedings{abc,
	author = {Darko Makreshanski and Jana Giceva and Claude Barthels and Gustavo Alonso},
	booktitle = {Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA},
	title = {BatchDB: Efficient Isolated Execution of Hybrid OLTP+OLAP Workloads for Interactive Applications.},
	url = {http://doi.acm.org/10.1145/3035918.3035959},
	year = {2017}
}
Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017, Chicago, IL, USA, May 2017
Implementing parallel operators in multi-core machines often involves a data partitioning step that divides the data into cache-size blocks and arranges them so to allow concurrent threads to process them in parallel. Data partitioning is expensive, in some cases up to 90% of the cost of, e.g., a parallel hash join. In this paper we explore the use of an FPGA to accelerate data partitioning. We do so in the context of new hybrid architectures where the FPGA is located as a co-processor residing on a socket and with coherent access to the same memory as the CPU residing on the other socket. Such an architecture reduces data transfer overheads between the CPU and the FPGA, enabling hybrid operator execution where the partitioning happens on the FPGA and the build and probe phases of a join happen on the CPU. Our experiments demonstrate that FPGA-based partitioning is significantly faster and more robust than CPU-based partitioning. The results open interesting options as FPGAs are gradually integrated tighter with the CPU.
@inproceedings{abc,
	abstract = {Implementing parallel operators in multi-core machines often involves a data partitioning step that divides the data into cache-size blocks and arranges them so to allow concurrent threads to process them in parallel. Data partitioning is expensive, in some cases up to 90\% of the cost of, e.g., a parallel hash join. In this paper we explore the use of an FPGA to accelerate data partitioning. We do so in the context of new hybrid architectures where the FPGA is located as a co-processor residing on a socket and with coherent access to the same memory as the CPU residing on the other socket. Such an architecture reduces data transfer overheads between the CPU and the FPGA, enabling hybrid operator execution where the partitioning happens on the FPGA and the build and probe phases of a join happen on the CPU. Our experiments demonstrate that FPGA-based partitioning is significantly faster and more robust than CPU-based partitioning. The results open interesting options as FPGAs are gradually integrated tighter with the CPU.},
	author = {Kaan Kara and Jana Giceva and Gustavo Alonso},
	booktitle = {Proceedings of the 2017 ACM International Conference on Management of Data, SIGMOD Conference 2017},
	title = {FPGA-based Data Partitioning.},
	url = {http://doi.acm.org/10.1145/3035918.3035946},
	venue = {Chicago, IL, USA},
	year = {2017}
}

2016

Proceedings of the 12th International Workshop on Data Management on New Hardware, DaMoN 2016, San Francisco, CA, USA, June 2016
@inproceedings{abc,
	author = {Jana Giceva and Gerd Zellweger and Gustavo Alonso and Timothy Roscoe},
	booktitle = {Proceedings of the 12th International Workshop on Data Management on New Hardware, DaMoN 2016, San Francisco, CA, USA},
	title = {Customized OS support for data-processing.},
	url = {http://doi.acm.org/10.1145/2933349.2933351},
	year = {2016}
}

2015

15th Workshop on Hot Topics in Operating Systems, HotOS XV, Kartause Ittingen, Switzerland, May 2015
@inproceedings{abc,
	author = {Ionel Gog and Jana Giceva and Malte Schwarzkopf and Kapil Vaswani and Dimitrios Vytiniotis and G. Ramalingam and Manuel Costa and Derek Gordon Murray and Steven Hand and Michael Isard},
	booktitle = {15th Workshop on Hot Topics in Operating Systems, HotOS XV, Kartause Ittingen, Switzerland},
	title = {Broom: Sweeping Out Garbage Collection from Big Data Systems.},
	url = {https://www.usenix.org/conference/hotos15/workshop-program/presentation/gog},
	year = {2015}
}

2014

PVLDB, November 2014
@inproceedings{abc,
	author = {Jana Giceva and Gustavo Alonso and Timothy Roscoe and Timothy L. Harris},
	booktitle = {PVLDB},
	title = {Deployment of Query Plans on Multicores.},
	url = {http://www.vldb.org/pvldb/vol8/p233-giceva.pdf},
	year = {2014}
}

2013

CIDR 2013, Sixth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 2013
@inproceedings{abc,
	author = {Jana Giceva and Tudor-Ioan Salomie and Adrian Sch{\"u}pbach and Gustavo Alonso and Timothy Roscoe},
	booktitle = {CIDR 2013, Sixth Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA},
	title = {COD: Database / Operating System Co-Design.},
	url = {http://www.cidrdb.org/cidr2013/Papers/CIDR13_Paper71.pdf},
	year = {2013}
}

2012

Proceedings of the 2nd workshop on Systems for Future Multi-core Architectures (SFMA'12), Bern, Switzerland, January 2012
@inproceedings{abc,
	author = {Jana Giceva and Adrian Sch{\"u}pbach and Gustavo Alonso and Timothy Roscoe},
	booktitle = {Proceedings of the 2nd workshop on Systems for Future Multi-core Architectures (SFMA{\textquoteright}12), Bern, Switzerland},
	title = {Towards Database / Operating System Co-Design},
	year = {2012}
}

2011

Systems Group Master's Thesis, no. 8; Department of Computer Science, May 2011
Supervised by: Prof. Gustavo Alonso
@mastersthesis{abc,
	author = {Jana Giceva},
	school = {8},
	title = {Database-Operating System Co-Design},
	year = {2011}
}
European Conference on Computer Systems, Proceedings of the Sixth European conference on Computer systems, EuroSys 2011, Salzburg, Austria, European Conference on Computer Systems, Proceedings of the Sixth European conference on Computer systems, EuroSys 2011 (pg. 17-30), Salzburg, Austria - April 10-13, 2011., January 2011
@inproceedings{abc,
	author = {Tudor-Ioan Salomie and Ionut Emanuel Subasu and Jana Giceva and Gustavo Alonso},
	booktitle = {European Conference on Computer Systems, Proceedings of the Sixth European conference on Computer systems, EuroSys 2011, Salzburg, Austria},
	title = {Database Engines on Multicores, Why Parallelize When You Can Distribute?},
	url = {http://doi.acm.org/10.1145/1966445.1966448},
	venue = {European Conference on Computer Systems, Proceedings of the Sixth European conference on Computer systems, EuroSys 2011 (pg. 17-30), Salzburg, Austria - April 10-13, 2011.},
	year = {2011}
}