Filters








23 Hits in 6.7 sec

A survey of large-scale reasoning on the Web of data

Grigoris Antoniou, Sotiris Batsakis, Raghava Mutharaju, Jeff Z. Pan, Guilin Qi, Ilias Tachmazidis, Jacopo Urbani, Zhangquan Zhou
2018 Knowledge engineering review (Print)  
In this large and uncoordinated environment, reasoning can be used to check the consistency of the data and of associated ontologies, or to infer logical consequences which, in turn, can be used to obtain  ...  These systems differ significantly; for instance in terms of reasoning expressivity, computational properties such as completeness, or reasoning objectives.  ...  GPUs are highly parallel and follow the Single Instruction, Multiple Data (SIMD) model.  ... 
doi:10.1017/s0269888918000255 fatcat:bergc5uphbceznigppektgvzrm

A survey of parallel execution strategies for transitive closure and logic programs

Filippo Cacace, Stefano Ceri, Maurice Houtsma
1993 Distributed and parallel databases  
Finally, we consider Datalog queries, and present general methods for parallel rule execution; we recognize the similarities between these methods and the methods reviewed previously, when the former are  ...  We first analyze the relationship between the transitive closure of expressions in Relational Algebra and Datalog programs.  ...  Stefano Ceri is partially supported by Esprit Project P6333, IDEA and the research of Maurice Houtsma has been made possible by a fellowship of the Royal Netherlands Academy of Arts and Sciences.  ... 
doi:10.1007/bf01264013 fatcat:pe4vicsr3vctzoj437towrkdv4

EmptyHeaded: A Relational Engine for Graph Processing [article]

Christopher R. Aberger, Susan Tu, Kunle Olukotun, Christopher Ré
2017 arXiv   pre-print
In high-level engines, users write in query languages like datalog (SociaLite) or SQL (Grail).  ...  To achieve high performance, EmptyHeaded introduces a new join engine architecture, including a novel query optimizer and data layouts that leverage single-instruction multiple data (SIMD) parallelism.  ...  For comparison, Galois uses 7915MB and PowerGraph uses 8620MB.  ... 
arXiv:1503.02368v7 fatcat:hlbgwo66wbe7bmavodpli3xfb4

EmptyHeaded

Christopher R. Aberger, Susan Tu, Kunle Olukotun, Christopher Ré
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
In high-level engines, users write in query languages like datalog (SociaLite) or SQL (Grail).  ...  To achieve high performance, EmptyHeaded introduces a new join engine architecture, including a novel query optimizer and data layouts that leverage single-instruction multiple data (SIMD) parallelism.  ...  Thus, it is critically important to optimize set intersections and the associated data layout to be well-suited for SIMD parallelism.  ... 
doi:10.1145/2882903.2915213 pmid:28077912 pmcid:PMC5221635 dblp:conf/sigmod/AbergerTOR16 fatcat:gtq53m7ytzas7ixlqf7kkofbha

Big Graph Analytics Platforms

Da Yan, Yingyi Bu, Yuanyuan Tian, Amol Deshpande
2017 Foundations and Trends in Databases  
., 2015] scale Datalog evaluations to a cluster of machines in this way.  ...  use GPUs to achieve massive parallelism in a shared memory environment.  ...  We only present the simple case where v in and v out fit in main memory, and thus the computation only needs to read adjacency lists (i.e., columns of A T ) from SSD.  ... 
doi:10.1561/1900000056 fatcat:ucqrtzo4q5g2lpj6dmp7jv3e5m

Red Fox

Haicheng Wu, Gregory Diamos, Tim Sheard, Molham Aref, Sean Baxter, Michael Garland, Sudhakar Yalamanchili
2014 Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization  
Modern enterprise applications represent an emergent application arena that requires the processing of queries and computations over massive amounts of data.  ...  This paper introduces the design, implementation, and evaluation of Red Fox, a compiler and runtime infrastructure for executing relational queries on GPUs.  ...  We would also like to acknowledge the detailed and constructive comments of the reviewers. REFERENCES [1] Amazon. Amazon elastic compute cloud, 2013.  ... 
doi:10.1145/2544137.2544166 fatcat:p6mzg2ugcrgi5odbrg6vz7wtwa

Red Fox

Haicheng Wu, Gregory Diamos, Tim Sheard, Molham Aref, Sean Baxter, Michael Garland, Sudhakar Yalamanchili
2014 Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization - CGO '14  
Modern enterprise applications represent an emergent application arena that requires the processing of queries and computations over massive amounts of data.  ...  This paper introduces the design, implementation, and evaluation of Red Fox, a compiler and runtime infrastructure for executing relational queries on GPUs.  ...  Furthermore, well-defined properties associated with logical relations, such as commutativity and associativity of conjunctions, readily expose data parallelism in LogiQL programs.  ... 
doi:10.1145/2581122.2544166 fatcat:piwvqur6ubdgbobceu4uoafnnq

Inferray

Julien Subercaze, Christophe Gravier, Jules Chevalier, Frederique Laforest
2016 Proceedings of the VLDB Endowment  
using ad-hoc optimizations on MSD radix and a custom counting sort; 3) a dedicated temporary storage to perform efficient graph closure computation.  ...  The linked nature and the huge volume of data entail efficiency and scalability challenges when designing productive inference systems.  ...  The authors would also like to thank Satish Nadathur for his help on sorting algorithms, Jacopo Urbani for his help with WebPIE and QueryPIE and the authors of RDFox for their help in configuring their  ... 
doi:10.14778/2904121.2904123 fatcat:6ncfo5nx2zbydihf4dbxlzgc6q

Multipredicate Join Algorithms for Accelerating Relational Graph Processing on GPUs

Haicheng Wu, Daniel Zinn, Molham Aref, Sudhakar Yalamanchili
2014 Very Large Data Bases Conference  
In this paper, we take a closer look at graph problems such as finding all triangles and all four-cliques of a graph. In particular, we present two different join algorithms for the GPU.  ...  Furthermore, both our algorithms are competitive with the hand-written C++ implementation for finding triangles and four-cliques in the graph-processing system GraphLab executing on a multi-core CPU.  ...  Computing (ISTC-CC).  ... 
dblp:conf/vldb/WuZAY14 fatcat:hfdyv5lmm5fzfo227xaa5wgyka

Index—Volumes 1–89

1997 Artificial Intelligence  
of computer -89 purposive -1275 robot and machine -24 robotic -255 search procedure inherent in -1273 sensors 1067 stereo -1276 vision system 316,478 computer -322 MOSAIC 376,478 robot -1273  ...  of queries in -338 Horn -375 image -1037 inconsistent -67 1 medical -129 predicate-calculus -394 dataflow architecture highly-parallel -337 architectures 337 diagrams 679 graph 337 Datalog  ... 
doi:10.1016/s0004-3702(97)80122-1 fatcat:6az7xycuifaerl7kmv7l3x6rpm

The MADlib analytics library

Joseph M. Hellerstein, Kun Li, Arun Kumar, Christoper Ré, Florian Schoppmann, Daisy Zhe Wang, Eugene Fratkin, Aleksander Gorajek, Kee Siong Ng, Caleb Welton, Xixuan Feng
2012 Proceedings of the VLDB Endowment  
parallelism in mind.  ...  It provides an evolving suite of SQL-based algorithms for machine learning, data mining and statistics that run at scale within a database engine, with no need for data import/export to other tools.  ...  disk, memory, and multiple parallel machines.  ... 
doi:10.14778/2367502.2367510 fatcat:bqz6ufkkpvf2jngbjbmw7jhnwu

The MADlib Analytics Library or MAD Skills, the SQL [article]

Joe Hellerstein, Christopher Ré, Florian Schoppmann, Daisy Zhe Wang, Eugene Fratkin, Aleksander Gorajek, Kee Siong Ng, Caleb Welton, Xixuan Feng, Kun Li, Arun Kumar
2012 arXiv   pre-print
parallelism in mind.  ...  It provides an evolving suite of SQL-based algorithms for machine learning, data mining and statistics that run at scale within a database engine, with no need for data import/export to other tools.  ...  disk, memory, and multiple parallel machines.  ... 
arXiv:1208.4165v1 fatcat:uouyhvyo3va2veamidxbeacou4

Massively Parallel Databases and MapReduce Systems

Shivnath Babu
2012 Foundations and Trends in Databases  
This monograph covers the design principles and core features of systems for analyzing very large datasets using massively-parallel computation and storage techniques on large clusters of nodes.  ...  Timely and cost-effective analytics over "big data" has emerged as a key ingredient for success in many businesses, scientific and engineering disciplines, and government endeavors.  ...  Users specify computations over large datasets in terms of Map and Reduce functions, and the underlying run-time system automatically parallelizes the computation across large-scale clusters of machines  ... 
doi:10.1561/1900000036 fatcat:5moo66w5aneyppq3xpib4wtaam

Modeling and Multiple Perceptions [chapter]

Christine Parent, Stefano Spaccapietra, Esteban Zimányi
2017 Encyclopedia of GIS  
Cross-References Computer Environments for GIS and CAD Movement Patterns in Spatio-Temporal Data Cross-References Geospatial Semantic Web, Interoperability Metadata and Interoperability, Geospatial  ...  Modeling with Pictogrammic Languages OGC's Open Standards for Geospatial Interoperability Vector Data Cross-References Indexing, Query and Velocity-Constrained Privacy Threats in Location-Based Services  ...  When massively computing resources are available, different approaches can be deployed to parallelize scientific computation on computer clusters equipped with MIC processors.  ... 
doi:10.1007/978-3-319-17885-1_805 fatcat:d4t4ossygvcutpfabqn6f3hjcm

Structure-Aware Machine Learning over Multi-Relational Databases

Maximilian Schleich
2021 Proceedings of the 2021 International Conference on Management of Data  
itemsets [107] and association rule mining [12] .  ...  Whereas SQLaware data mining systems were mostly concerned with association rules, decision trees, and clustering, current workloads feature a broader spectrum of increasingly more sophisticated machine  ...  Chapter 21 K-Means Clustering We evaluate the performance of the Rk-means clustering algorithm from Section 9.2.2, where the steps 1 and 3 of the algorithm are computed in LMFAO (c.f. Section 15.3).  ... 
doi:10.1145/3448016.3461670 fatcat:xhqcdfxkdbdrnkn3gklevd6tmq
« Previous Showing results 1 — 15 out of 23 results