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Vector Extensions for Decision Support DBMS Acceleration

Timothy Hayes, Oscar Palomar, Osman Unsal, Adrian Cristal, Mateo Valero
2012 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture  
This work takes a top-down approach to accelerating decision support systems (DSS) on x86-64 microprocessors using vector ISA extensions.  ...  We discuss why the existing multimedia SIMD extensions (SSE/AVX) are not suitable for capturing this parallelism and propose a complementary instruction set reminiscent of classical vector architectures  ...  Acknowledgements The authors would like to thank Peter Boncz, MarcinŻukowski and Paul Rosenfeld for their helpful advice and feedback.  ... 
doi:10.1109/micro.2012.24 dblp:conf/micro/HayesPUCV12 fatcat:u2fwqzsjejc5zbjfg4crxrynou

Database systems research on data mining

Carlos Ordonez, Javier García-García
2010 Proceedings of the 2010 international conference on Management of data - SIGMOD '10  
We pay particular attention to SQL and MapReduce as two competing technologies for large scale processing. We conclude with a summary of solved major problems and open research issues.  ...  Column stores can accelerate data mining, especially for high dimensional models. From the mathematical side, the list is extensive.  ...  Sampling has been key to accelerate clustering, decision trees and association rules.  ... 
doi:10.1145/1807167.1807335 dblp:conf/sigmod/OrdonezG10 fatcat:ppgnhhnzorhkpbrpqz7etrz6j4

Can we analyze big data inside a DBMS?

Carlos Ordonez
2013 Proceedings of the sixteenth international workshop on Data warehousing and OLAP - DOLAP '13  
On the other hand, for data analytics in a broad sense, there are plenty of non-DBMS tools including statistical languages, matrix packages, generic data mining programs and largescale parallel systems  ...  , being the main technology for big data analytics.  ...  Acknowledgments This research work was partially supported by National Science Foundation grant IIS 0914861. REFERENCES  ... 
doi:10.1145/2513190.2513198 dblp:conf/dolap/Ordonez13 fatcat:ejuvzywvqrd5jig6bfcmixc66m

Workload Optimization by Horizontal Aggregation in SQL for Data Mining Analysis

Prasanna M. Rathod, Prof. Dr. Anjali B. Raut
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Decision making; 4. Data migration. The decision phase is triggered when the load imbalance is detected to calculate optimal data redistribution.  ...  For query optimization the distance computation and nearest cluster in the k-means are based on SQL.  ...  Basically, a horizontal aggregation returns a set of numbers instead of a single number for each group, resembling a multi-dimensional vector. ➢ We proposed an abstract, but minimal, extension to SQL standard  ... 
doi:10.32628/cseit217263 fatcat:i6swnr4qibbvbhtpdilqj7cdmy

Statistical Model Computation with UDFs

Carlos Ordonez
2010 IEEE Transactions on Knowledge and Data Engineering  
Statistical models are generally computed outside a DBMS due to their mathematical complexity.  ...  We introduce techniques to efficiently compute fundamental statistical models inside a DBMS exploiting User-Defined-Functions (UDFs).  ...  Acknowledgments This research work was supported by US National Science Foundation grants CCF 0937562 and IIS 0914861.  ... 
doi:10.1109/tkde.2010.44 fatcat:mhmmyoie3zczhchbnvai4dm3ri

GPU-Accelerated Database Systems: Survey and Open Challenges [chapter]

Sebastian Breß, Max Heimel, Norbert Siegmund, Ladjel Bellatreche, Gunter Saake
2014 Lecture Notes in Computer Science  
Unsurprisingly, the database research community identified GPUs as effective co-processors for data processing several years ago.  ...  The vast amount of processing power and memory bandwidth provided by modern graphics cards make them an interesting platform for data-intensive applications.  ...  We discuss eight GPU-accelerated DBMSs (GDBMSs) to review the stateof-the-art, collect prominent findings, and complement our discussion on a GPU-aware DBMS architecture. 2.  ... 
doi:10.1007/978-3-662-45761-0_1 fatcat:rpwqxejbkjh6dhzp27ppiawzsu

doppioDB 1.0: Machine Learning inside a Relational Engine

Gustavo Alonso, Zsolt István, Kaan Kara, Muhsen Owaida, David Sidler
2019 IEEE Data Engineering Bulletin  
This first version of doppioDB provides a platform for extending traditional relational processing with customizable hardware to support stochastic gradient descent and decision tree ensembles.  ...  In this paper we present doppioDB 1.0, an FPGA-enabled database engine incorporating FPGA-based machine learning operators into a main memory, columnar DBMS (MonetDB).  ...  Acknowledgements We like to thank Intel for the generous donation of the Xeon+FPGA v2 prototype.  ... 
dblp:journals/debu/AlonsoIKOS19 fatcat:6vxbetufyrddxpy7tidsltuov4

AxleDB: A novel programmable query processing platform on FPGA

Behzad Salami, Gorker Alp Malazgirt, Oriol Arcas-Abella, Arda Yurdakul, Nehir Sonmez
2017 Microprocessors and microsystems  
To minimize the amount of SSD I/O operations required, AxleDB also supports hardware MinMax indexing for databases.  ...  DBMS, i.e., PostgreSQL and MonetDB.  ...  DBMS Software Extensions for AxleDB.  ... 
doi:10.1016/j.micpro.2017.04.018 fatcat:iwsyzrtoifhivn552ywwqk3ude

Conceptual design and implementation of spatial data warehouses integrating regular grids of points

Sandro Bimonte, Mehdi Zaamoune, Philippe Beaune
2016 International Journal of Digital Earth  
Motivated by the need for a conceptual design tool and ROLAP implementation, we propose a UML profile for SDWs that integrates a regular grid of points and supports continuity and multiresolutions.  ...  In the last decade, the conceptual design and implementation of SDWs that integrate spatial data, which are represented using the vector model, have been extensively investigated.  ...  PostGIS is an extension of the DBMS PostgreSQL for spatial data. The SOLAP server is GeoMondrian (GeoMondrian, 2015) .  ... 
doi:10.1080/17538947.2016.1266040 fatcat:jjaoh5bjrjd65iqbhmpzrmckzm

Evaluating Lightweight Integer Compression Algorithms in Column-Oriented In-Memory DBMS

Linus Heinzl, Ben Hurdelhey, Martin Boissier, Michael Perscheid, Hasso Plattner
2021 International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures  
Our evaluation suggests that random access performance is often more relevant than vectorization capabilities for sequential accesses.  ...  In recent years, various integer compression techniques have been proposed that focus on sequential encoding and decoding and exploit modern CPUs' vectorization capabilities.  ...  ACKNOWLEDGMENTS We thank Tobias Pape and the HPI Data Engineering Lab for supporting us with the cache miss analyses and providing access to the evaluated hardware platforms.  ... 
dblp:conf/adms/HeinzlH0PP21 fatcat:ez25osprcjeolbwlre4h3erkw4

Data parallel acceleration of decision support queries using Cell/BE and GPUs

Pedro Trancoso, Despo Othonos, Artemakis Artemiou
2009 Proceedings of the 6th ACM conference on Computing frontiers - CF '09  
Decision Support System (DSS) workloads are known to be one of the most time-consuming database workloads that processes large data sets.  ...  Traditionally, DSS queries have been accelerated using large-scale multiprocessor.  ...  TPC-H is a Decision Support System (DSS) benchmark. The queries employed by this benchmark are relevant to industry decision support operations.  ... 
doi:10.1145/1531743.1531763 dblp:conf/cf/TrancosoOA09 fatcat:aem46tslwvg6hjmvwslap7xwbm

PCA for large data sets with parallel data summarization

Carlos Ordonez, Naveen Mohanam, Carlos Garcia-Alvarado
2013 Distributed and parallel databases  
Parallel processing is essential for large-scale analytics.  ...  Benchmarking on multicore CPUs and a parallel DBMS running on multiple nodes confirms linear speedup and linear scalability.  ...  Acknowledgments This work was supported by NSF grant IIS 0914861.  ... 
doi:10.1007/s10619-013-7134-6 fatcat:aleeiv7g65brpnffeiuezpziv4

LIMoSim: A Lightweight and Integrated Approach for Simulating Vehicular Mobility with OMNeT++ [article]

Benjamin Sliwa, Johannes Pillmann, Fabian Eckermann, Christian Wietfeld
2017 arXiv   pre-print
The proposed framework Lightweight ICT-centric Mobility Simulation (LIMoSim) is available as Open Source software and can easily be combined with other third-party extension frameworks for providing vehicular  ...  In this paper, we present a lightweight and integrated approach for simulating vehicular mobility directly in Objective Modular Network Testbed in C++ (OMNeT++) and INET without the need for external tools  ...  ACKNOWLEDGMENT Part of the work on this paper has been supported by Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876 "Providing Information by Resource-Constrained  ... 
arXiv:1709.02020v1 fatcat:ancmnhguefgfhaexerbqje2tvi

Adaptive Data Processing in Heterogeneous Hardware Systems

Bala Gurumurthy, Tobias Drewes, David Broneske, Gunter Saake, Thilo Pionteck
2018 Workshop Grundlagen von Datenbanken  
Hence, it is evident that an adaptable DBMS is necessary for supporting this highly volatile environment.  ...  Before, a traditional DBMS was sufficient for performing a given operation, whereas a current DBMS is required to perform complex analytical tasks like graph analysis or OLAP.  ...  The parallelism in GPU has been already exploited extensively for several DBMS operations [3, 1] .  ... 
dblp:conf/gvd/GurumurthyDBSP18 fatcat:idhyo2ltlrhnjds45dxpwtmgza

Evaluating end-to-end optimization for data analytics applications in weld

Shoumik Palkar, Saman Amarasinghe, Samuel Madden, Matei Zaharia, James Thomas, Deepak Narayanan, Pratiksha Thaker, Rahul Palamuttam, Parimajan Negi, Anil Shanbhag, Malte Schwarzkopf, Holger Pirk
2018 Proceedings of the VLDB Endowment  
Our results show that common runtime designs like Weld may be a viable approach to accelerate analytics.  ...  Our optimizer eliminates multiple forms of overhead that arise when composing imperative libraries like Pandas and NumPy, and uses lightweight measurements to make data-dependent decisions at runtime in  ...  ACKNOWLEDGEMENTS We thank the members of the Stanford DAWN lab for their invaluable feedback on this work.  ... 
doi:10.14778/3213880.3213890 fatcat:oesslpgfy5awlb32xnylmjlnoa
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