Compliation Techniques for Graphs Algorithms on GPUs. Article Swipe
Ajay Brahmakshatriya
,
Yunming Zhang
,
Changwan Hong
,
Shoaib Kamil
,
Julian Shun
,
Saman Amarasinghe
·
YOU?
·
· 2020
· Open Access
·
YOU?
·
· 2020
· Open Access
·
The performance of graph programs depends highly on the algorithm, size, and structure of the input graphs, as well as the features of the underlying hardware. No single set of optimizations or one hardware platform works well across all settings. To achieve high performance, the programmer must carefully select which set optimizations as well as the hardware platform to use. However, currently when switching between CPUs and GPUs, programmer must re-implement the entire algorithm with different optimizations in order to achieve high performance. We propose the GG GPU compiler, a new graph processing framework that achieves high performance on both CPUs and GPUs using the same algorithm specification. GG significantly expands the optimization space of GPU graph processing frameworks with a novel GPU scheduling language and compiler that enables combining load balancing, edge traversal direction, active vertex set creation, active vertex set processing ordering, and kernel fusion optimizations. GG also introduces two performance optimizations, Edge-based Thread Warps CTAs load balancing (ETWC) and EdgeBlocking, to expand the optimization space for GPUs. ETWC improves load balance by dynamically partitioning the edges of each vertex into blocks that are assigned to threads, warps, and CTAs for execution. EdgeBlocking improves the locality of the program by reordering the edges and restricting random memory accesses to fit within L2 cache. We evaluate GG on 5 algorithms and 9 input graphs on both Pascal and Volta generation NVIDIA GPUs, and show that it achieves up to 5.11x speedup over state-of-the-art GPU graph processing frameworks, and is the fastest on 62 out of the 90 experiment
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://arxiv.org/pdf/2012.07990
- OA Status
- green
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3112216501
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3112216501Canonical identifier for this work in OpenAlex
- Title
-
Compliation Techniques for Graphs Algorithms on GPUs.Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-12-14Full publication date if available
- Authors
-
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong, Shoaib Kamil, Julian Shun, Saman AmarasingheList of authors in order
- Landing page
-
https://arxiv.org/pdf/2012.07990Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2012.07990Direct OA link when available
- Concepts
-
Computer science, Parallel computing, Compiler, Speedup, Locality, CUDA, Load balancing (electrical power), Programmer, Programming language, Philosophy, Grid, Mathematics, Linguistics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3112216501 |
|---|---|
| doi | |
| ids.mag | 3112216501 |
| ids.openalex | https://openalex.org/W3112216501 |
| fwci | |
| type | preprint |
| title | Compliation Techniques for Graphs Algorithms on GPUs. |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12292 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9987000226974487 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Graph Theory and Algorithms |
| topics[1].id | https://openalex.org/T11273 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9969000220298767 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Advanced Graph Neural Networks |
| topics[2].id | https://openalex.org/T10720 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9821000099182129 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1703 |
| topics[2].subfield.display_name | Computational Theory and Mathematics |
| topics[2].display_name | Complexity and Algorithms in Graphs |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.8687136173248291 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C173608175 |
| concepts[1].level | 1 |
| concepts[1].score | 0.6898366212844849 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q232661 |
| concepts[1].display_name | Parallel computing |
| concepts[2].id | https://openalex.org/C169590947 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5465285181999207 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q47506 |
| concepts[2].display_name | Compiler |
| concepts[3].id | https://openalex.org/C68339613 |
| concepts[3].level | 2 |
| concepts[3].score | 0.4960118234157562 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1549489 |
| concepts[3].display_name | Speedup |
| concepts[4].id | https://openalex.org/C2779808786 |
| concepts[4].level | 2 |
| concepts[4].score | 0.47021153569221497 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q6664603 |
| concepts[4].display_name | Locality |
| concepts[5].id | https://openalex.org/C2778119891 |
| concepts[5].level | 2 |
| concepts[5].score | 0.46422502398490906 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q477690 |
| concepts[5].display_name | CUDA |
| concepts[6].id | https://openalex.org/C138959212 |
| concepts[6].level | 3 |
| concepts[6].score | 0.4345822334289551 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1806783 |
| concepts[6].display_name | Load balancing (electrical power) |
| concepts[7].id | https://openalex.org/C2778514511 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4119871258735657 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1374194 |
| concepts[7].display_name | Programmer |
| concepts[8].id | https://openalex.org/C199360897 |
| concepts[8].level | 1 |
| concepts[8].score | 0.19804435968399048 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[8].display_name | Programming language |
| concepts[9].id | https://openalex.org/C138885662 |
| concepts[9].level | 0 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[9].display_name | Philosophy |
| concepts[10].id | https://openalex.org/C187691185 |
| concepts[10].level | 2 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q2020720 |
| concepts[10].display_name | Grid |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C41895202 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[12].display_name | Linguistics |
| concepts[13].id | https://openalex.org/C2524010 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[13].display_name | Geometry |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.8687136173248291 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/parallel-computing |
| keywords[1].score | 0.6898366212844849 |
| keywords[1].display_name | Parallel computing |
| keywords[2].id | https://openalex.org/keywords/compiler |
| keywords[2].score | 0.5465285181999207 |
| keywords[2].display_name | Compiler |
| keywords[3].id | https://openalex.org/keywords/speedup |
| keywords[3].score | 0.4960118234157562 |
| keywords[3].display_name | Speedup |
| keywords[4].id | https://openalex.org/keywords/locality |
| keywords[4].score | 0.47021153569221497 |
| keywords[4].display_name | Locality |
| keywords[5].id | https://openalex.org/keywords/cuda |
| keywords[5].score | 0.46422502398490906 |
| keywords[5].display_name | CUDA |
| keywords[6].id | https://openalex.org/keywords/load-balancing |
| keywords[6].score | 0.4345822334289551 |
| keywords[6].display_name | Load balancing (electrical power) |
| keywords[7].id | https://openalex.org/keywords/programmer |
| keywords[7].score | 0.4119871258735657 |
| keywords[7].display_name | Programmer |
| keywords[8].id | https://openalex.org/keywords/programming-language |
| keywords[8].score | 0.19804435968399048 |
| keywords[8].display_name | Programming language |
| language | en |
| locations[0].id | mag:3112216501 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | arXiv (Cornell University) |
| locations[0].landing_page_url | https://arxiv.org/pdf/2012.07990 |
| authorships[0].author.id | https://openalex.org/A5046807118 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5295-4186 |
| authorships[0].author.display_name | Ajay Brahmakshatriya |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Ajay Brahmakshatriya |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5102790106 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-3087-5580 |
| authorships[1].author.display_name | Yunming Zhang |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yunming Zhang |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5027442506 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-9069-8374 |
| authorships[2].author.display_name | Changwan Hong |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Changwan Hong |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5039453861 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-5965-3717 |
| authorships[3].author.display_name | Shoaib Kamil |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Shoaib Kamil |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5051583907 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-6163-6625 |
| authorships[4].author.display_name | Julian Shun |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Julian Shun |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5046791216 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-7231-7643 |
| authorships[5].author.display_name | Saman Amarasinghe |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Saman P. Amarasinghe |
| authorships[5].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2012.07990 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Compliation Techniques for Graphs Algorithms on GPUs. |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-10-10T17:16:08.811792 |
| primary_topic.id | https://openalex.org/T12292 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9987000226974487 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Graph Theory and Algorithms |
| related_works | https://openalex.org/W2808229499, https://openalex.org/W1907157718, https://openalex.org/W2740828438, https://openalex.org/W3095418274, https://openalex.org/W2240152262, https://openalex.org/W1965470147, https://openalex.org/W2766010992, https://openalex.org/W2027789717, https://openalex.org/W2617189289, https://openalex.org/W2026812620, https://openalex.org/W2285422792, https://openalex.org/W2260499435, https://openalex.org/W2780646942, https://openalex.org/W3007313775, https://openalex.org/W132869365, https://openalex.org/W2295952195, https://openalex.org/W2732588537, https://openalex.org/W3013281160, https://openalex.org/W3123568939, https://openalex.org/W2523448744 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | mag:3112216501 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | arXiv (Cornell University) |
| best_oa_location.landing_page_url | https://arxiv.org/pdf/2012.07990 |
| primary_location.id | mag:3112216501 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | arXiv (Cornell University) |
| primary_location.landing_page_url | https://arxiv.org/pdf/2012.07990 |
| publication_date | 2020-12-14 |
| publication_year | 2020 |
| referenced_works_count | 0 |
| abstract_inverted_index.5 | 219 |
| abstract_inverted_index.9 | 222 |
| abstract_inverted_index.a | 89, 120 |
| abstract_inverted_index.62 | 253 |
| abstract_inverted_index.90 | 257 |
| abstract_inverted_index.GG | 86, 108, 148, 217 |
| abstract_inverted_index.L2 | 213 |
| abstract_inverted_index.No | 26 |
| abstract_inverted_index.To | 40 |
| abstract_inverted_index.We | 83, 215 |
| abstract_inverted_index.as | 17, 19, 52, 54 |
| abstract_inverted_index.by | 174, 201 |
| abstract_inverted_index.in | 77 |
| abstract_inverted_index.is | 249 |
| abstract_inverted_index.it | 236 |
| abstract_inverted_index.of | 2, 13, 22, 29, 114, 179, 198, 255 |
| abstract_inverted_index.on | 7, 98, 218, 225, 252 |
| abstract_inverted_index.or | 31 |
| abstract_inverted_index.to | 58, 79, 163, 187, 210, 239 |
| abstract_inverted_index.up | 238 |
| abstract_inverted_index.GPU | 87, 115, 122, 244 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.all | 38 |
| abstract_inverted_index.and | 11, 66, 101, 125, 144, 161, 190, 205, 221, 228, 233, 248 |
| abstract_inverted_index.are | 185 |
| abstract_inverted_index.fit | 211 |
| abstract_inverted_index.for | 168, 192 |
| abstract_inverted_index.new | 90 |
| abstract_inverted_index.one | 32 |
| abstract_inverted_index.out | 254 |
| abstract_inverted_index.set | 28, 50, 137, 141 |
| abstract_inverted_index.the | 8, 14, 20, 23, 44, 55, 71, 85, 104, 111, 165, 177, 196, 199, 203, 250, 256 |
| abstract_inverted_index.two | 151 |
| abstract_inverted_index.CPUs | 65, 100 |
| abstract_inverted_index.CTAs | 157, 191 |
| abstract_inverted_index.ETWC | 170 |
| abstract_inverted_index.GPUs | 102 |
| abstract_inverted_index.also | 149 |
| abstract_inverted_index.both | 99, 226 |
| abstract_inverted_index.each | 180 |
| abstract_inverted_index.edge | 132 |
| abstract_inverted_index.high | 42, 81, 96 |
| abstract_inverted_index.into | 182 |
| abstract_inverted_index.load | 130, 158, 172 |
| abstract_inverted_index.must | 46, 69 |
| abstract_inverted_index.over | 242 |
| abstract_inverted_index.same | 105 |
| abstract_inverted_index.show | 234 |
| abstract_inverted_index.that | 94, 127, 184, 235 |
| abstract_inverted_index.use. | 59 |
| abstract_inverted_index.well | 18, 36, 53 |
| abstract_inverted_index.when | 62 |
| abstract_inverted_index.with | 74, 119 |
| abstract_inverted_index.5.11x | 240 |
| abstract_inverted_index.GPUs, | 67, 232 |
| abstract_inverted_index.GPUs. | 169 |
| abstract_inverted_index.Volta | 229 |
| abstract_inverted_index.Warps | 156 |
| abstract_inverted_index.edges | 178, 204 |
| abstract_inverted_index.graph | 3, 91, 116, 245 |
| abstract_inverted_index.input | 15, 223 |
| abstract_inverted_index.novel | 121 |
| abstract_inverted_index.order | 78 |
| abstract_inverted_index.size, | 10 |
| abstract_inverted_index.space | 113, 167 |
| abstract_inverted_index.using | 103 |
| abstract_inverted_index.which | 49 |
| abstract_inverted_index.works | 35 |
| abstract_inverted_index.(ETWC) | 160 |
| abstract_inverted_index.NVIDIA | 231 |
| abstract_inverted_index.Pascal | 227 |
| abstract_inverted_index.Thread | 155 |
| abstract_inverted_index.across | 37 |
| abstract_inverted_index.active | 135, 139 |
| abstract_inverted_index.blocks | 183 |
| abstract_inverted_index.cache. | 214 |
| abstract_inverted_index.entire | 72 |
| abstract_inverted_index.expand | 164 |
| abstract_inverted_index.fusion | 146 |
| abstract_inverted_index.graphs | 224 |
| abstract_inverted_index.highly | 6 |
| abstract_inverted_index.kernel | 145 |
| abstract_inverted_index.memory | 208 |
| abstract_inverted_index.random | 207 |
| abstract_inverted_index.select | 48 |
| abstract_inverted_index.single | 27 |
| abstract_inverted_index.vertex | 136, 140, 181 |
| abstract_inverted_index.warps, | 189 |
| abstract_inverted_index.within | 212 |
| abstract_inverted_index.achieve | 41, 80 |
| abstract_inverted_index.balance | 173 |
| abstract_inverted_index.between | 64 |
| abstract_inverted_index.depends | 5 |
| abstract_inverted_index.enables | 128 |
| abstract_inverted_index.expands | 110 |
| abstract_inverted_index.fastest | 251 |
| abstract_inverted_index.graphs, | 16 |
| abstract_inverted_index.program | 200 |
| abstract_inverted_index.propose | 84 |
| abstract_inverted_index.speedup | 241 |
| abstract_inverted_index.However, | 60 |
| abstract_inverted_index.accesses | 209 |
| abstract_inverted_index.achieves | 95, 237 |
| abstract_inverted_index.assigned | 186 |
| abstract_inverted_index.compiler | 126 |
| abstract_inverted_index.evaluate | 216 |
| abstract_inverted_index.features | 21 |
| abstract_inverted_index.hardware | 33, 56 |
| abstract_inverted_index.improves | 171, 195 |
| abstract_inverted_index.language | 124 |
| abstract_inverted_index.locality | 197 |
| abstract_inverted_index.platform | 34, 57 |
| abstract_inverted_index.programs | 4 |
| abstract_inverted_index.threads, | 188 |
| abstract_inverted_index.algorithm | 73, 106 |
| abstract_inverted_index.balancing | 159 |
| abstract_inverted_index.carefully | 47 |
| abstract_inverted_index.combining | 129 |
| abstract_inverted_index.compiler, | 88 |
| abstract_inverted_index.creation, | 138 |
| abstract_inverted_index.currently | 61 |
| abstract_inverted_index.different | 75 |
| abstract_inverted_index.framework | 93 |
| abstract_inverted_index.hardware. | 25 |
| abstract_inverted_index.ordering, | 143 |
| abstract_inverted_index.settings. | 39 |
| abstract_inverted_index.structure | 12 |
| abstract_inverted_index.switching | 63 |
| abstract_inverted_index.traversal | 133 |
| abstract_inverted_index.Edge-based | 154 |
| abstract_inverted_index.algorithm, | 9 |
| abstract_inverted_index.algorithms | 220 |
| abstract_inverted_index.balancing, | 131 |
| abstract_inverted_index.direction, | 134 |
| abstract_inverted_index.execution. | 193 |
| abstract_inverted_index.experiment | 258 |
| abstract_inverted_index.frameworks | 118 |
| abstract_inverted_index.generation | 230 |
| abstract_inverted_index.introduces | 150 |
| abstract_inverted_index.processing | 92, 117, 142, 246 |
| abstract_inverted_index.programmer | 45, 68 |
| abstract_inverted_index.reordering | 202 |
| abstract_inverted_index.scheduling | 123 |
| abstract_inverted_index.underlying | 24 |
| abstract_inverted_index.dynamically | 175 |
| abstract_inverted_index.frameworks, | 247 |
| abstract_inverted_index.performance | 1, 97, 152 |
| abstract_inverted_index.restricting | 206 |
| abstract_inverted_index.EdgeBlocking | 194 |
| abstract_inverted_index.optimization | 112, 166 |
| abstract_inverted_index.partitioning | 176 |
| abstract_inverted_index.performance, | 43 |
| abstract_inverted_index.performance. | 82 |
| abstract_inverted_index.re-implement | 70 |
| abstract_inverted_index.EdgeBlocking, | 162 |
| abstract_inverted_index.optimizations | 30, 51, 76 |
| abstract_inverted_index.significantly | 109 |
| abstract_inverted_index.optimizations, | 153 |
| abstract_inverted_index.optimizations. | 147 |
| abstract_inverted_index.specification. | 107 |
| abstract_inverted_index.state-of-the-art | 243 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile |