Matches in SemOpenAlex for { <https://semopenalex.org/work/W2753129172> ?p ?o ?g. }
Showing items 1 to 62 of
62
with 100 items per page.
- W2753129172 abstract "HPCG and Graph500 can be regarded as the two most relevant benchmarks for high-performance computing systems. Existing supercomputer designs, however, tend to focus on floating-point peak performance, a metric less relevant for these two benchmarks, leaving resources underutilized, and resulting in little performance improvements, for these benchmarks, over time. In this work, we analyze the implementation of both benchmarks on a novel shared-memory near-data processing architecture. We study a number of aspects: 1. a system parameter design exploration, 2. software optimizations, and 3. the exploitation of unique architectural features like user-enhanced coherence as well as the exploitation of data-locality for inter near-data processor traffic.For the HPCG benchmark, we show a factor 2.5x application level speedup with respect to a CPU, and a factor 2.5x power-efficiency improvement with respect to a GPU. For the Graph500 benchmark, we show up to a factor 3.5x speedup with respect to a CPU. Furthermore, we show that, with many of the existing data-locality optimizations for this specific graph workload applied, local memory bandwidth is not the crucial parameter, and a high-bandwidth as well as low-latency interconnect are arguably more important, shining a new light on the near-data processing characteristics most relevant for this type of heavily optimized graph processing." @default.
- W2753129172 created "2017-09-15" @default.
- W2753129172 creator A5001983294 @default.
- W2753129172 creator A5018686817 @default.
- W2753129172 creator A5039264220 @default.
- W2753129172 creator A5058128591 @default.
- W2753129172 date "2017-08-01" @default.
- W2753129172 modified "2023-09-25" @default.
- W2753129172 title "Boosting the Efficiency of HPCG and Graph500 with Near-Data Processing" @default.
- W2753129172 cites W1969835518 @default.
- W2753129172 cites W1981579732 @default.
- W2753129172 cites W1981943579 @default.
- W2753129172 cites W1992011279 @default.
- W2753129172 cites W2048466306 @default.
- W2753129172 cites W2069809851 @default.
- W2753129172 cites W2093524602 @default.
- W2753129172 cites W2111784516 @default.
- W2753129172 cites W2141144145 @default.
- W2753129172 cites W2169631286 @default.
- W2753129172 cites W2170382128 @default.
- W2753129172 cites W2409755949 @default.
- W2753129172 cites W2478494156 @default.
- W2753129172 cites W4230357857 @default.
- W2753129172 cites W4245923077 @default.
- W2753129172 cites W4253426709 @default.
- W2753129172 doi "https://doi.org/10.1109/icpp.2017.12" @default.
- W2753129172 hasPublicationYear "2017" @default.
- W2753129172 type Work @default.
- W2753129172 sameAs 2753129172 @default.
- W2753129172 citedByCount "7" @default.
- W2753129172 countsByYear W27531291722019 @default.
- W2753129172 countsByYear W27531291722020 @default.
- W2753129172 countsByYear W27531291722021 @default.
- W2753129172 countsByYear W27531291722022 @default.
- W2753129172 crossrefType "proceedings-article" @default.
- W2753129172 hasAuthorship W2753129172A5001983294 @default.
- W2753129172 hasAuthorship W2753129172A5018686817 @default.
- W2753129172 hasAuthorship W2753129172A5039264220 @default.
- W2753129172 hasAuthorship W2753129172A5058128591 @default.
- W2753129172 hasConcept C154945302 @default.
- W2753129172 hasConcept C41008148 @default.
- W2753129172 hasConcept C46686674 @default.
- W2753129172 hasConceptScore W2753129172C154945302 @default.
- W2753129172 hasConceptScore W2753129172C41008148 @default.
- W2753129172 hasConceptScore W2753129172C46686674 @default.
- W2753129172 hasLocation W27531291721 @default.
- W2753129172 hasOpenAccess W2753129172 @default.
- W2753129172 hasPrimaryLocation W27531291721 @default.
- W2753129172 hasRelatedWork W109826989 @default.
- W2753129172 hasRelatedWork W115329727 @default.
- W2753129172 hasRelatedWork W1998940060 @default.
- W2753129172 hasRelatedWork W2003125512 @default.
- W2753129172 hasRelatedWork W2023972939 @default.
- W2753129172 hasRelatedWork W2255183448 @default.
- W2753129172 hasRelatedWork W2382510858 @default.
- W2753129172 hasRelatedWork W2948340715 @default.
- W2753129172 hasRelatedWork W3107474891 @default.
- W2753129172 hasRelatedWork W4206452239 @default.
- W2753129172 isParatext "false" @default.
- W2753129172 isRetracted "false" @default.
- W2753129172 magId "2753129172" @default.
- W2753129172 workType "article" @default.