Editing Chapter 2
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@ -6,6 +6,8 @@
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@misc{noauthor_overview_nodate,
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title = {An {Overview} of the {Parallel} {Boost} {Graph} {Library} - 1.75.0},
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authors = {Edmonds, Nick and Gregor, Douglas and Lumsdaine, Andrew},
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year = {2009},
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url = {https://www.boost.org/doc/libs/1_75_0/libs/graph_parallel/doc/html/overview.html},
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}
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@ -16,7 +18,8 @@
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}
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@misc{noauthor_boost_nodate,
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title = {The {Boost} {Graph} {Library} - 1.75.0},
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title = {The {Boost} {Graph} {Library}, vers. 1.75.0},
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author = {Siek, Jeremy and Lee, Lie-Quan and Lumsdaine, Andrew},
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url = {https://www.boost.org/doc/libs/1_75_0/libs/graph/doc/index.html},
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}
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@ -13,8 +13,8 @@ nodes and edges, graph data structures suffer from poor cache locality, and memo
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\TUsection{Graph Generation Improvements} \label{sec:gen_improv}
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For architectural and hardware techniques for generation improvement, the authors of \cite{ainsworth_graph_2016} discuss the high cache miss rate, and how general prefetching
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does not increase the prediction rate due to nonsequential graph structures and data-dependent access patterns. However, the authors continue to discuss that the generation
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algorithm is known in advance, so explicit tuning of the hardware prefetcher to follow the traversal order pattern can lead to better performance. The authors were able to achieve
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does not increase the prediction rate due to nonsequential graph structures and data-dependent access patterns. However, the authors continue to discuss that generation
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algorithms are known in advance, so explicit tuning of the hardware prefetcher to follow the traversal order pattern can lead to better performance. The authors were able to achieve
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over 2x performance improvement of a breadth-first search approach with this method. Another hardware approach is to make use of accelerators. The authors of \cite{yao_efficient_2018}
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present an approach for minimizing the slowdown caused by the underlying graph atomic functions. By using the atomic function patterns, the authors utilized pipeline stages where vertex
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updates can be processed in parallel dynamically. Other works, such as those by the authors of \cite{zhang_boosting_2017} and \cite{dai_fpgp_2016}, leverage field-programmable gate arrays
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@ -23,7 +23,7 @@ on-chip block RAM, or even leveraging Hybrid Memory Cubes for optimizing paralle
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From a data structure standpoint, the authors of \cite{arifuzzaman_fast_2015} describe the infeasibility of adjacency matrices in large-scale graphs, and this work and other works such as those
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by the authors of \cite{yu_construction_2018} and \cite{liakos_memory-optimized_2016} discuss the appeal of distributing a graph representation across systems. The author of
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\cite{liakos_memory-optimized_2016} discuss the usage of distributed adjacency lists for assigning vertices to workers. The authors of \cite{liakos_memory-optimized_2016} and
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\cite{liakos_memory-optimized_2016} discusses the usage of distributed adjacency lists for assigning vertices to workers. The authors of \cite{liakos_memory-optimized_2016} and
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\cite{balaji_graph_2016} present other techniques for minimizing communication costs by achieving high compression ratios while maintaining a low compression cost. The Boost Graph Library
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and the Parallel Boost Graph Library both provide appealing features for working with graphs, with the latter library notably having interoperability with MPI, Graphviz, and METIS
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\cite{noauthor_overview_nodate}, \cite{noauthor_boost_nodate}.
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@ -103,10 +103,11 @@ J.~Balaji and R.~Sunderraman, ``Graph {Topology} {Abstraction} for
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May 2016.
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\bibitem{noauthor_overview_nodate}
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``An {Overview} of the {Parallel} {Boost} {Graph} {Library} - 1.75.0.''
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``An {Overview} of the {Parallel} {Boost} {Graph} {Library} - 1.75.0,'' 2009.
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\bibitem{noauthor_boost_nodate}
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``The {Boost} {Graph} {Library} - 1.75.0.''
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J.~Siek, L.-Q. Lee, and A.~Lumsdaine, ``The {Boost} {Graph} {Library}, vers.
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1.75.0.''
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\bibitem{cook_scalable_2016}
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K.~Cook, T.~Shaw, J.~Hale, and P.~Hawrylak, ``Scalable attack graph
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@ -10,42 +10,42 @@ A level-1 auxiliary file: Chapter6.aux
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The style file: ieeetr.bst
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Database file #1: Bibliography.bib
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Warning--entry type for "j_hale_compliance_nodate" isn't style-file defined
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--line 272 of file Bibliography.bib
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--line 275 of file Bibliography.bib
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Warning--entry type for "EUdataregulations2018" isn't style-file defined
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--line 1250 of file Bibliography.bib
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--line 1253 of file Bibliography.bib
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Warning--empty journal in ou_scalable_2006
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Warning--empty school in cook_rage_2018
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Warning--empty school in louthan_hybrid_2011
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You've used 30 entries,
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1876 wiz_defined-function locations,
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622 strings with 9004 characters,
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and the built_in function-call counts, 6493 in all, are:
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= -- 608
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624 strings with 9065 characters,
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and the built_in function-call counts, 6551 in all, are:
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num.names$ -- 25
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pop$ -- 147
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num.names$ -- 26
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warning$ -- 3
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while$ -- 59
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while$ -- 60
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width$ -- 32
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write$ -- 248
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(There were 5 warnings)
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This is pdfTeX, Version 3.141592653-2.6-1.40.23 (TeX Live 2021/Arch Linux) (preloaded format=pdflatex 2022.3.21) 27 MAR 2022 17:52
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This is pdfTeX, Version 3.141592653-2.6-1.40.23 (TeX Live 2021/Arch Linux) (preloaded format=pdflatex 2022.3.21) 27 MAR 2022 18:09
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entering extended mode
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y10.pfb></usr/share/texmf-dist/fonts/type1/public/amsfonts/cm/cmti12.pfb></usr/
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st/fonts/type1/public/cm-super/sfrm1200.pfb>
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Output written on Schrick-Noah_MS-Thesis.pdf (66 pages, 2061592 bytes).
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Output written on Schrick-Noah_MS-Thesis.pdf (66 pages, 2061642 bytes).
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PDF statistics:
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