Matches in SemOpenAlex for { <https://semopenalex.org/work/W2250217037> ?p ?o ?g. }
- W2250217037 endingPage "29" @default.
- W2250217037 startingPage "1" @default.
- W2250217037 abstract "3D-stacked DRAM alleviates the limited memory bandwidth bottleneck that exists in modern systems by leveraging through silicon vias (TSVs) to deliver higher external memory channel bandwidth. Today’s systems, however, cannot fully utilize the higher bandwidth offered by TSVs, due to the limited internal bandwidth within each layer of the 3D-stacked DRAM. We identify that the bottleneck to enabling higher bandwidth in 3D-stacked DRAM is now the global bitline interface , the connection between the DRAM row buffer and the peripheral IO circuits. The global bitline interface consists of a limited and expensive set of wires and structures, called global bitlines and global sense amplifiers , whose high cost makes it difficult to simply scale up the bandwidth of the interface within a single DRAM layer in the 3D stack. We alleviate this bandwidth bottleneck by exploiting the observation that several global bitline interfaces already exist across the multiple DRAM layers in current 3D-stacked designs, but only a fraction of them are enabled at the same time. We propose a new 3D-stacked DRAM architecture, called Simultaneous Multi-Layer Access (SMLA), which increases the internal DRAM bandwidth by accessing multiple DRAM layers concurrently, thus making much greater use of the bandwidth that the TSVs offer. To avoid channel contention, the DRAM layers must coordinate with each other when simultaneously transferring data. We propose two approaches to coordination, both of which deliver four times the bandwidth for a four-layer DRAM, over a baseline that accesses only one layer at a time. Our first approach, Dedicated-IO, statically partitions the TSVs by assigning each layer to a dedicated set of TSVs that operate at a higher frequency. Unfortunately, Dedicated-IO requires a nonuniform design for each layer (increasing manufacturing costs), and its DRAM energy consumption scales linearly with the number of layers. Our second approach, Cascaded-IO, solves both issues by instead time multiplexing all of the TSVs across layers. Cascaded-IO reduces DRAM energy consumption by lowering the operating frequency of higher layers. Our evaluations show that SMLA provides significant performance improvement and energy reduction across a variety of workloads (55%/18% on average for multiprogrammed workloads, respectively) over a baseline 3D-stacked DRAM, with low overhead." @default.
- W2250217037 created "2016-06-24" @default.
- W2250217037 creator A5007585346 @default.
- W2250217037 creator A5036666743 @default.
- W2250217037 creator A5050695684 @default.
- W2250217037 creator A5070152284 @default.
- W2250217037 creator A5086615155 @default.
- W2250217037 date "2016-01-06" @default.
- W2250217037 modified "2023-10-18" @default.
- W2250217037 title "Simultaneous Multi-Layer Access" @default.
- W2250217037 cites W1574985978 @default.
- W2250217037 cites W1578894366 @default.
- W2250217037 cites W1970426108 @default.
- W2250217037 cites W1982063824 @default.
- W2250217037 cites W1983178358 @default.
- W2250217037 cites W2003312212 @default.
- W2250217037 cites W2007929622 @default.
- W2250217037 cites W2020460319 @default.
- W2250217037 cites W2028675360 @default.
- W2250217037 cites W2032512814 @default.
- W2250217037 cites W2035720033 @default.
- W2250217037 cites W2043634607 @default.
- W2250217037 cites W2092207361 @default.
- W2250217037 cites W2098040113 @default.
- W2250217037 cites W2100913437 @default.
- W2250217037 cites W2101865620 @default.
- W2250217037 cites W2109292926 @default.
- W2250217037 cites W2110090002 @default.
- W2250217037 cites W2115172404 @default.
- W2250217037 cites W2118703320 @default.
- W2250217037 cites W2129381159 @default.
- W2250217037 cites W2129513794 @default.
- W2250217037 cites W2135965542 @default.
- W2250217037 cites W2142875853 @default.
- W2250217037 cites W2143807959 @default.
- W2250217037 cites W2145930457 @default.
- W2250217037 cites W2150196852 @default.
- W2250217037 cites W2154502576 @default.
- W2250217037 cites W2154656016 @default.
- W2250217037 cites W2155702343 @default.
- W2250217037 cites W2158620667 @default.
- W2250217037 cites W2159515198 @default.
- W2250217037 cites W2159908132 @default.
- W2250217037 cites W2164586147 @default.
- W2250217037 cites W2170257519 @default.
- W2250217037 cites W2233523872 @default.
- W2250217037 cites W2537002257 @default.
- W2250217037 cites W3139689176 @default.
- W2250217037 cites W3140772298 @default.
- W2250217037 cites W3147974890 @default.
- W2250217037 cites W4206782120 @default.
- W2250217037 cites W4230104114 @default.
- W2250217037 cites W4233735179 @default.
- W2250217037 cites W4236382111 @default.
- W2250217037 cites W4238816702 @default.
- W2250217037 cites W4239813889 @default.
- W2250217037 doi "https://doi.org/10.1145/2832911" @default.
- W2250217037 hasPublicationYear "2016" @default.
- W2250217037 type Work @default.
- W2250217037 sameAs 2250217037 @default.
- W2250217037 citedByCount "123" @default.
- W2250217037 countsByYear W22502170372016 @default.
- W2250217037 countsByYear W22502170372017 @default.
- W2250217037 countsByYear W22502170372018 @default.
- W2250217037 countsByYear W22502170372019 @default.
- W2250217037 countsByYear W22502170372020 @default.
- W2250217037 countsByYear W22502170372021 @default.
- W2250217037 countsByYear W22502170372022 @default.
- W2250217037 countsByYear W22502170372023 @default.
- W2250217037 crossrefType "journal-article" @default.
- W2250217037 hasAuthorship W2250217037A5007585346 @default.
- W2250217037 hasAuthorship W2250217037A5036666743 @default.
- W2250217037 hasAuthorship W2250217037A5050695684 @default.
- W2250217037 hasAuthorship W2250217037A5070152284 @default.
- W2250217037 hasAuthorship W2250217037A5086615155 @default.
- W2250217037 hasBestOaLocation W22502170371 @default.
- W2250217037 hasConcept C100800780 @default.
- W2250217037 hasConcept C149635348 @default.
- W2250217037 hasConcept C188045654 @default.
- W2250217037 hasConcept C189930140 @default.
- W2250217037 hasConcept C2776257435 @default.
- W2250217037 hasConcept C2780513914 @default.
- W2250217037 hasConcept C31258907 @default.
- W2250217037 hasConcept C32666082 @default.
- W2250217037 hasConcept C41008148 @default.
- W2250217037 hasConcept C7366592 @default.
- W2250217037 hasConcept C9390403 @default.
- W2250217037 hasConcept C98986596 @default.
- W2250217037 hasConceptScore W2250217037C100800780 @default.
- W2250217037 hasConceptScore W2250217037C149635348 @default.
- W2250217037 hasConceptScore W2250217037C188045654 @default.
- W2250217037 hasConceptScore W2250217037C189930140 @default.
- W2250217037 hasConceptScore W2250217037C2776257435 @default.
- W2250217037 hasConceptScore W2250217037C2780513914 @default.
- W2250217037 hasConceptScore W2250217037C31258907 @default.
- W2250217037 hasConceptScore W2250217037C32666082 @default.
- W2250217037 hasConceptScore W2250217037C41008148 @default.
- W2250217037 hasConceptScore W2250217037C7366592 @default.