Emerging Memory and Computing Devices in the Era of Intelligent Machines
dc.contributor.author | Khalili, Pedram | * |
dc.date.accessioned | 2021-02-11T12:26:08Z | |
dc.date.available | 2021-02-11T12:26:08Z | |
dc.date.issued | 2020 | * |
dc.date.submitted | 2020-06-09 16:38:57 | * |
dc.identifier | 46023 | * |
dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/46257 | |
dc.description.abstract | Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system. | * |
dc.language | English | * |
dc.subject | TA1-2040 | * |
dc.subject | T1-995 | * |
dc.subject.classification | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology | en_US |
dc.subject.other | n/a | * |
dc.subject.other | image classification | * |
dc.subject.other | bipolar resistive switching characteristics | * |
dc.subject.other | bioelectronic devices | * |
dc.subject.other | self-directed channel (SDC) | * |
dc.subject.other | programmable ramp-down current pulses | * |
dc.subject.other | nanoparticles | * |
dc.subject.other | protein | * |
dc.subject.other | DRAM | * |
dc.subject.other | convolutional neural networks | * |
dc.subject.other | silicon oxide-based memristors | * |
dc.subject.other | electrochemical metallization cell | * |
dc.subject.other | magnetic tunnel junction | * |
dc.subject.other | power gating | * |
dc.subject.other | resistance switching mechanism | * |
dc.subject.other | BCH | * |
dc.subject.other | Fast Fourier Transform | * |
dc.subject.other | nucleic acid | * |
dc.subject.other | biomemory | * |
dc.subject.other | conductive filament | * |
dc.subject.other | resistive random access memory (RRAM) | * |
dc.subject.other | non-von Neumann architecture | * |
dc.subject.other | emerging technologies | * |
dc.subject.other | Galois field | * |
dc.subject.other | variability | * |
dc.subject.other | logic-in-memory | * |
dc.subject.other | charge spreading | * |
dc.subject.other | memristor | * |
dc.subject.other | Hebbian training | * |
dc.subject.other | crossbar | * |
dc.subject.other | quantum point contact | * |
dc.subject.other | SONOS | * |
dc.subject.other | bionanohybrid material | * |
dc.subject.other | ECG | * |
dc.subject.other | neuromorphic computing | * |
dc.subject.other | CUDA | * |
dc.subject.other | low-latency | * |
dc.subject.other | iBM | * |
dc.subject.other | Oxygen-related trap | * |
dc.subject.other | nonvolatile memory | * |
dc.subject.other | phase change memory | * |
dc.subject.other | floating gate | * |
dc.subject.other | non-von neumann architecture | * |
dc.subject.other | 3D-stacked | * |
dc.subject.other | STT-MRAM | * |
dc.subject.other | solution-based dielectric | * |
dc.subject.other | GPU | * |
dc.subject.other | Internet of things | * |
dc.subject.other | configurable logic-in-memory architecture | * |
dc.subject.other | memory wall | * |
dc.subject.other | biologic gate | * |
dc.subject.other | synaptic weight | * |
dc.subject.other | guide training | * |
dc.subject.other | ion conduction | * |
dc.subject.other | perpendicular Nano Magnetic Logic (pNML) | * |
dc.subject.other | Weibull distribution | * |
dc.subject.other | real-time system | * |
dc.subject.other | in-DRAM cache | * |
dc.subject.other | task placement | * |
dc.subject.other | dynamic voltage scaling | * |
dc.subject.other | MCU (microprogrammed control unit) | * |
dc.subject.other | wire resistance | * |
dc.subject.other | multi-level cell | * |
dc.subject.other | chalcogenide | * |
dc.subject.other | decoder | * |
dc.subject.other | character recognition | * |
dc.subject.other | matrix-vector multiplication | * |
dc.subject.other | hybrid | * |
dc.subject.other | magnetoresistive random access memory | * |
dc.subject.other | blockchain | * |
dc.subject.other | electrochemical metallization (ECM) | * |
dc.subject.other | RISC-V | * |
dc.subject.other | U-shape recessed channel | * |
dc.subject.other | neuromorphic system | * |
dc.subject.other | in-memory computing | * |
dc.subject.other | crossbar array | * |
dc.subject.other | associative processor | * |
dc.subject.other | low-power | * |
dc.subject.other | plasma treatment | * |
dc.subject.other | voltage-controlled magnetic anisotropy | * |
dc.subject.other | flash memory | * |
dc.subject.other | resistive memory | * |
dc.subject.other | analogue computing | * |
dc.subject.other | bioprocessor | * |
dc.subject.other | annealing temperatures | * |
dc.subject.other | data retention | * |
dc.subject.other | flip-flop | * |
dc.subject.other | low-power technique | * |
dc.title | Emerging Memory and Computing Devices in the Era of Intelligent Machines | * |
dc.type | book | |
oapen.identifier.doi | 10.3390/books978-3-03928-503-7 | * |
oapen.relation.isPublishedBy | 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 | * |
oapen.relation.isbn | 9783039285037 | * |
oapen.relation.isbn | 9783039285020 | * |
oapen.pages | 276 | * |
oapen.edition | 1st | * |
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