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A survey of large-scale reasoning on the Web of data
2018
Knowledge engineering review (Print)
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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
1993
Distributed and parallel databases
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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]
2017
arXiv
pre-print
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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
2016
Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16
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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
2017
Foundations and Trends in Databases
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., 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
2014
Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization
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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
2014
Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization - CGO '14
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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
2016
Proceedings of the VLDB Endowment
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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
2014
Very Large Data Bases Conference
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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
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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
2012
Proceedings of the VLDB Endowment
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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]
2012
arXiv
pre-print
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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
2012
Foundations and Trends in Databases
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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]
2017
Encyclopedia of GIS
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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
2021
Proceedings of the 2021 International Conference on Management of Data
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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
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