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Multidimensional Range Queries on Modern Hardware [article]

Stefan Sprenger, Patrick Schäfer, Ulf Leser
2018 arXiv   pre-print
The question is whether this rule of thumb still holds when multidimensional range queries (MDRQ) are performed on modern architectures with large main memories holding all data, multi-core CPUs and data-parallel  ...  Range queries over multidimensional data are an important part of database workloads in many applications.  ...  ACKNOWLEDGMENTS We would like to thank the bioinformaticians from our working group, especially Yvonne Lichtblau, for their valuable feedback on the design of the GMRQ Benchmark.  ... 
arXiv:1801.03644v2 fatcat:bryyocuzjvbkbhjguje34bwtoe

Dynamic Pipelining of Multidimensional Range Queries

Amalia Duch, Daniel Lugosi, Edelmira Pasarella, Cristina Zoltan
2019 Alberto Mendelzon Workshop on Foundations of Data Management  
In this work we propose an alternative approach to evaluate multidimensional range queries based on the dynamic pipeline paradigm -using main memory and concurrency.  ...  In recent experimental works using modern hardware-with main memory and parallelism-the conclusion is that linear scan is preferable for almost every query configuration (even containing a 1% of the data  ...  Recently, multidimensional range queries as well as the efficiency of hierarchical multidimensional data structures to support them have been revisited under a modern hardware perspective [5] .  ... 
dblp:conf/amw/DuchLPZ19 fatcat:wboikzql5zeadcxbnywnjssdzm

Adaptive Cardinality Estimation [article]

Oleg Ivanov, Sergey Bartunov
2017 arXiv   pre-print
We consider cost-based query optimization approach as the most popular one. It was observed that cost-based optimization quality depends much on cardinality estimation quality.  ...  The execution time of different plans may differ by several orders, so query optimizer has a great influence on the whole DBMS performance.  ...  It is the only part in cost model, which depends not on hardware parameters but on data in database and clauses in the query.  ... 
arXiv:1711.08330v1 fatcat:gchmdbgjargkhfsfvbytepobea

Multidimensional Transfer Functions for Volume Rendering [chapter]

2005 Visualization Handbook  
We would also like to thank NVIDIA, ATI and sgi for their making their latest generations of hardware available.  ...  not be possible without the use of modern graphics hardware.  ...  Many modern graphics hardware platforms support multitexture and a number of user-defined operations for blending these textures per-pixel.  ... 
doi:10.1016/b978-012387582-2/50011-3 fatcat:cqbyrflfqrhjdce245u2ilhike

Hardware Partitioning for Big Data Analytics

Lisa Wu, Raymond J. Barker, Martha A. Kim, Kenneth A. Ross
2014 IEEE Micro  
In the era of big data, diverse fields such as natural language processing, medical science, national security, and business management depend on analyzing massive, multidimensional datasets.  ...  The system consists of two parts: an area and power-efficient specialized processing element for range partitioning, called the Hardware-Accelerated Range Partitioner (HARP); and a high-bandwidth, hardwaresoftware  ...  Block diagram of a typical two-core system with Hardware-Accelerated Range Partitioner (HARP) integration.  ... 
doi:10.1109/mm.2014.11 fatcat:qner4vegrbakbpstm2ursegkkm

Multidimensional Aggregation Process in Cloud Computing System

Song Li
2014 International Journal of Grid and Distributed Computing  
This paper presents multidimensional aggregation query processing algorithm in cloud computing system.  ...  Theoretical analysis and simulation results prove the validity of the multidimensional aggregate query plan.  ...  The computing hardware modern has many working state includes Active, Sleeping, Hibernate and Shutoff, the hardware power are significant differences in the diverse work state.  ... 
doi:10.14257/ijgdc.2014.7.5.01 fatcat:5wm7a5kvyvhyjdk6cus5aci3gu

Expressing Parallelism [chapter]

James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian
2020 Data Parallel C++  
We already know how to place code (Chapter 10.1007/978-1-4842-5574-2_2) and data (Chapter 10.1007/978-1-4842-5574-2_3) on a device—all we must do now is engage in the art of deciding what to do with it  ...  Multidimensional Kernels The parallel constructs of many other languages are one-dimensional, mapping work directly to a corresponding one-dimensional hardware resource (e.g., number of hardware threads  ...  Sub-Groups On many modern hardware platforms, subsets of the work-items in a work-group known as sub-groups are executed with additional scheduling guarantees.  ... 
doi:10.1007/978-1-4842-5574-2_4 fatcat:ppar5yv5nfgbjiclwwmw74eeua

Access Path Selection in Main-Memory Optimized Data Systems

Michael S. Kester, Manos Athanassoulis, Stratos Idreos
2017 Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17  
based on hardware advancements.  ...  In particular, contrary to the way traditional systems choose between scans and secondary indexes, we find that in addition to the query selectivity, the underlying hardware, and the system design, modern  ...  fully optimized for modern hardware and sharing.  ... 
doi:10.1145/3035918.3064049 dblp:conf/sigmod/KesterAI17 fatcat:6fl5342c5bhsvoj7g5sv7hnf2e

Cloud BI: Future of business intelligence in the Cloud

Hussain Al-Aqrabi, Lu Liu, Richard Hill, Nick Antonopoulos
2015 Journal of computer and system sciences (Print)  
The Cloud hosting of BI has been demonstrated with the help of a simulation on OPNET comprising a Cloud model with multiple OLAP application servers applying parallel query loads on an array of servers  ...  The simulation results reflected that true and extensible parallel processing of database servers on the Cloud can efficiently process OLAP application demands on Cloud computing.  ...  Hence, the query processing response time of each server will be different on the Cloud due to differences in hardware configurations.  ... 
doi:10.1016/j.jcss.2014.06.013 fatcat:gashotik6bfjbkyam5jmc6bgra

Cloud BI: Future of Business Intelligence in the Cloud [article]

Hussain Al-Aqrabi, Lu Liu, Richard Hill, Nick Antonopoulos
2019 arXiv   pre-print
The cloud hosting of BI has been demonstrated with the help of a simulation on OPNET comprising a cloud model with multiple OLAP application servers applying parallel query loads on an array of servers  ...  The simulation results have reflected that true and extensible parallel processing of database servers on the cloud can efficiently process OLAP application demands on cloud computing.  ...  Hence, the query processing response time of each server will be different on the cloud due to differences in hardware configurations.  ... 
arXiv:1901.08151v1 fatcat:utzep5z2rjdlvdyt6trogdro5e

Viewpoints: A High-Performance High-Dimensional Exploratory Data Analysis Tool

P. R. Gazis, C. Levit, M. J. Way
2010 Publications of the Astronomical Society of the Pacific  
It leverages the capabilities of modern graphics boards (GPUs) to run on a single workstation or laptop.  ...  , it is now possible, in principle, to view large complex data sets on a single workstation.  ...  -Relationships between query response time, query source location, time of day, type of query, etc.  ... 
doi:10.1086/657902 fatcat:odwg37btrvhadixdmsgi5kjhpe

Design of a Multi-Dimensional Packet Classifier for Network Processors

Stefano Giordano, Gregorio Procissi, Federico Rossi, Fabio Vitucci
2006 2006 IEEE International Conference on Communications  
In this paper we illustrate the design of a multidimensional packet classifier realized on the Radisys® ENP-2611 board equipped with Intel® IXP2400 Network Processor.  ...  Network Processors (NPs) are emerging as very promising platforms due to their capability to combine the flexibility of general-purpose processors with high performance of hardware-based solutions.  ...  allows achieving 100 million queries per second [11]).  ... 
doi:10.1109/icc.2006.254845 dblp:conf/icc/GiordanoPRV06 fatcat:jcohvxa4rjcvreied5v6unfsnm

Privacy-Preserving OLAP-Based Monitoring of Data Streams: The PP-OMDS Approach

Alfredo Cuzzocrea, Assaf Schuster, Gianni Vercelli, Massimiliano Nolich
2019 Sistemi Evoluti per Basi di Dati  
It is worth to recognize that the described application scenario well-describes a plethora of modern data stream applications, ranging from event detection to complex monitoring queries support, from near-duplicate  ...  top of a COUNT aggregate operator over a two-dimensional range 〈𝑟 1 , 𝑟 2 〉, being 𝑟 1 and 𝑟 2 two one-dimensional ranges along 𝐿𝑜𝑐𝑎𝑡𝑖𝑜𝑛 and 𝑇𝑖𝑚𝑒, respectively, which define the data cube  ... 
dblp:conf/sebd/CuzzocreaSVN19 fatcat:atk3v6ywrvafxd6xs4zsnduxiq

An Array Database Approach for Earth Observation Data Management and Processing

Zhenyu Tan, Peng Yue, Jianya Gong
2017 ISPRS International Journal of Geo-Information  
This paper suggests storing and processing EO data as multidimensional arrays based on state-of-the-art array database technologies.  ...  It allows consistent query semantics in databases and improves the in-database computing by adopting unified array models in databases for EO data.  ...  be transformed into operations on multidimensional arrays.  ... 
doi:10.3390/ijgi6070220 fatcat:jxaxfigfqbcnlk63zshygr2wf4

ARC 2014

Neil Scicluna, Christos-Savvas Bouganis
2015 ACM Transactions on Reconfigurable Technology and Systems  
This work focuses on the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which is one of the state-of-the-art clustering algorithms, and targets its acceleration using an  ...  The article presents an optimized, scalable, and parameterizable architecture that takes advantage of the internal memory structure of modern FPGAs in order to deliver a high-performance clustering system  ...  I DBSCAN Range Query Bias Analysis Dataset Imm. Neighb. Ext. Neighb. No. Size Eps MinPts Range Queries Range Queries 1 Table II .  ... 
doi:10.1145/2724722 fatcat:uge7llkunffkxi2vwvb5tbvjym
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