Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories
Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is current...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lashkare, Sandip [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Proceedings of the National Academy of Sciences - New York, NY : Springer, 2012, 93(2023), 3 vom: 04. Juni, Seite 459-476 |
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| Übergeordnetes Werk: |
volume:93 ; year:2023 ; number:3 ; day:04 ; month:06 ; pages:459-476 |
| Links: |
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| DOI / URN: |
10.1007/s40010-023-00828-w |
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SPR052917738 |
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| 520 | |a Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. | ||
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| 700 | 1 | |a Priyadarshi, Kumar |4 aut | |
| 700 | 1 | |a Ganguly, Udayan |4 aut | |
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10.1007/s40010-023-00828-w doi (DE-627)SPR052917738 (SPR)s40010-023-00828-w-e DE-627 ger DE-627 rakwb eng Lashkare, Sandip verfasserin (orcid)0000-0003-2018-1681 aut Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 Uddin, Wasi aut Priyadarshi, Kumar aut Ganguly, Udayan aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 93(2023), 3 vom: 04. Juni, Seite 459-476 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:93 year:2023 number:3 day:04 month:06 pages:459-476 https://dx.doi.org/10.1007/s40010-023-00828-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2023 3 04 06 459-476 |
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10.1007/s40010-023-00828-w doi (DE-627)SPR052917738 (SPR)s40010-023-00828-w-e DE-627 ger DE-627 rakwb eng Lashkare, Sandip verfasserin (orcid)0000-0003-2018-1681 aut Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 Uddin, Wasi aut Priyadarshi, Kumar aut Ganguly, Udayan aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 93(2023), 3 vom: 04. Juni, Seite 459-476 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:93 year:2023 number:3 day:04 month:06 pages:459-476 https://dx.doi.org/10.1007/s40010-023-00828-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2023 3 04 06 459-476 |
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10.1007/s40010-023-00828-w doi (DE-627)SPR052917738 (SPR)s40010-023-00828-w-e DE-627 ger DE-627 rakwb eng Lashkare, Sandip verfasserin (orcid)0000-0003-2018-1681 aut Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 Uddin, Wasi aut Priyadarshi, Kumar aut Ganguly, Udayan aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 93(2023), 3 vom: 04. Juni, Seite 459-476 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:93 year:2023 number:3 day:04 month:06 pages:459-476 https://dx.doi.org/10.1007/s40010-023-00828-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2023 3 04 06 459-476 |
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10.1007/s40010-023-00828-w doi (DE-627)SPR052917738 (SPR)s40010-023-00828-w-e DE-627 ger DE-627 rakwb eng Lashkare, Sandip verfasserin (orcid)0000-0003-2018-1681 aut Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 Uddin, Wasi aut Priyadarshi, Kumar aut Ganguly, Udayan aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 93(2023), 3 vom: 04. Juni, Seite 459-476 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:93 year:2023 number:3 day:04 month:06 pages:459-476 https://dx.doi.org/10.1007/s40010-023-00828-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2023 3 04 06 459-476 |
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10.1007/s40010-023-00828-w doi (DE-627)SPR052917738 (SPR)s40010-023-00828-w-e DE-627 ger DE-627 rakwb eng Lashkare, Sandip verfasserin (orcid)0000-0003-2018-1681 aut Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 Uddin, Wasi aut Priyadarshi, Kumar aut Ganguly, Udayan aut Enthalten in Proceedings of the National Academy of Sciences New York, NY : Springer, 2012 93(2023), 3 vom: 04. Juni, Seite 459-476 (DE-627)73921358X (DE-600)2707742-1 2250-1762 nnns volume:93 year:2023 number:3 day:04 month:06 pages:459-476 https://dx.doi.org/10.1007/s40010-023-00828-w lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 93 2023 3 04 06 459-476 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR052917738</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230830064747.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230830s2023 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s40010-023-00828-w</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR052917738</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s40010-023-00828-w-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Lashkare, Sandip</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-2018-1681</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. 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Lashkare, Sandip |
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Lashkare, Sandip misc Emerging memories misc RRAM misc PCM misc MRAM misc FeRAM misc Neuromorphic computing misc In-memory computing Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories |
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Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories Emerging memories (dpeaa)DE-He213 RRAM (dpeaa)DE-He213 PCM (dpeaa)DE-He213 MRAM (dpeaa)DE-He213 FeRAM (dpeaa)DE-He213 Neuromorphic computing (dpeaa)DE-He213 In-memory computing (dpeaa)DE-He213 |
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emerging memory technologies for data storage and brain-inspired computation: a global view with indian research insights with a focus on resistive memories |
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Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories |
| abstract |
Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract This article is an overview of emerging memory materials and their role in advanced brain-inspired computing technologies. It starts with the progress of memory technologies over the last 50 years along with emergence and dominance of NAND flash in the memory market. Though flash is currently leading the memory market due to its high volume manufacturing and low cost, it has a latency gap with dynamic random access memory. To address this, various nonvolatile memories have been explored across the world potentially to replace flash. Here, an overview of various major emerging nonvolatile memory (NVM) technologies is presented. Along with the global view of NVMs as their current status as a storage solution, the research of NVMs in India is discussed briefly with a focus on resistance random access memory and phase change memory. Further, the need of brain-inspired advanced computing technologies like neuromorphic computing, in-memory computing are discussed along with the utility of the NVMs for such brain-inspired computing technologies. Finally, various NVMs are presented for their unique characteristic to mimic synapse, neuron functionalities as required for neuromorphic computing and for in-memory computing solutions. © The Author(s), under exclusive licence to The National Academy of Sciences, India 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Emerging Memory Technologies for Data Storage and Brain-Inspired Computation: A Global View with Indian Research Insights with a Focus on Resistive Memories |
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https://dx.doi.org/10.1007/s40010-023-00828-w |
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Uddin, Wasi Priyadarshi, Kumar Ganguly, Udayan |
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| score |
7.402916 |