Gotowa bibliografia na temat „PCM memory”
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Artykuły w czasopismach na temat "PCM memory"
Arjomand, Mohammad, Amin Jadidi, Mahmut T. Kandemir, Anand Sivasubramaniam i Chita R. Das. "HL-PCM: MLC PCM Main Memory with Accelerated Read". IEEE Transactions on Parallel and Distributed Systems 28, nr 11 (1.11.2017): 3188–200. http://dx.doi.org/10.1109/tpds.2017.2705125.
Pełny tekst źródłaPriya, Bhukya Krishna, i N. Ramasubramanian. "Improving the Lifetime of Phase Change Memory by Shadow Dynamic Random Access Memory". International Journal of Service Science, Management, Engineering, and Technology 12, nr 2 (marzec 2021): 154–68. http://dx.doi.org/10.4018/ijssmet.2021030109.
Pełny tekst źródłaMacyna, Wojciech, i Michal Kukowski. "Adaptive Merging on Phase Change Memory". Fundamenta Informaticae 188, nr 2 (15.03.2023): 103–26. http://dx.doi.org/10.3233/fi-222144.
Pełny tekst źródłaJabarov, Elkhan, Byung-Won On, Gyu Choi i Myong-Soon Park. "R-Tree for phase change memory". Computer Science and Information Systems 14, nr 2 (2017): 347–67. http://dx.doi.org/10.2298/csis160620008j.
Pełny tekst źródłaHong, Jeong Beom, Young Sik Lee, Yong Wook Kim i Tae Hee Han. "Error-Vulnerable Pattern-Aware Binary-to-Ternary Data Mapping for Improving Storage Density of 3LC Phase Change Memory". Electronics 9, nr 4 (9.04.2020): 626. http://dx.doi.org/10.3390/electronics9040626.
Pełny tekst źródłaDing, Feilong, Baokang Peng, Xi Li, Lining Zhang, Runsheng Wang, Zhitang Song i Ru Huang. "A review of compact modeling for phase change memory". Journal of Semiconductors 43, nr 2 (1.02.2022): 023101. http://dx.doi.org/10.1088/1674-4926/43/2/023101.
Pełny tekst źródłaTang, Pu, Jing Xiao i Ming Tao. "Thermal Crosstalk Analysis of Phase Change Memory Considering Thermoelectric Effect and Thermal Boundary Resistance". Journal of Physics: Conference Series 2624, nr 1 (1.10.2023): 012020. http://dx.doi.org/10.1088/1742-6596/2624/1/012020.
Pełny tekst źródłaStern, Keren, Yair Keller, Christopher M. Neumann, Eric Pop i Eilam Yalon. "Temperature-dependent thermal resistance of phase change memory". Applied Physics Letters 120, nr 11 (14.03.2022): 113501. http://dx.doi.org/10.1063/5.0081016.
Pełny tekst źródłaSun, Hao, Lan Chen, Xiaoran Hao, Chenji Liu i Mao Ni. "An Energy-Efficient and Fast Scheme for Hybrid Storage Class Memory in an AIoT Terminal System". Electronics 9, nr 6 (17.06.2020): 1013. http://dx.doi.org/10.3390/electronics9061013.
Pełny tekst źródłaShin, Dongsuk, Hakbeom Jang, Kiseok Oh i Jae W. Lee. "An Energy-Efficient DRAM Cache Architecture for Mobile Platforms With PCM-Based Main Memory". ACM Transactions on Embedded Computing Systems 21, nr 1 (31.01.2022): 1–22. http://dx.doi.org/10.1145/3451995.
Pełny tekst źródłaRozprawy doktorskie na temat "PCM memory"
Grönberg, Axel. "Emerging Non-Volatile Memory and Initial Experiences with PCM Main Memory". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-407070.
Pełny tekst źródłaSeong, Nak Hee. "A reliable, secure phase-change memory as a main memory". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/50123.
Pełny tekst źródłaSELMO, SIMONE. "Functional analysis of In-based nanowires for low power phase change memory applications". Doctoral thesis, Università degli Studi di Milano-Bicocca, 2017. http://hdl.handle.net/10281/153247.
Pełny tekst źródłaPhase change memories (PCMs), based on chalcogenide alloys (mainly Ge2Sb2Te5), are the most promising candidate for the realization of “Storage Class Memories”, which would fill the gap between ‘‘operation’’ and ‘‘storage’’ memories. PCMs are also one of the few currently available technologies for the implementation of nanoeletronic synapses in high density neuromorphic systems. The main improvements needed in order to exploit the full potential of PCMs in these innovative applications are the reduction of the programming currents and power consumption, and further cell downscaling. Thanks to their nano-sized active volume to be programmed and self-heating behavior, phase change nanowires (NWs) are expected to exhibit improved memory performances with respected to commonly used thin-film/heater-based structures. The Ph. D. Thesis of the candidate reports the study of the phase change properties of ultra-thin In-based NWs for low power consuming PCMs, exploring the more promising features of this class of materials with respect to the commonly considered Ge-Sb-Te alloys. In particular, the self-assembly of In-Sb-Te, In-doped Sb and In-Ge-Te NWs was successfully achieved by Metal Organic Chemical Vapour Deposition (MOCVD), coupled to vapour-liquid-solid mechanism, catalysed by catalyst nanoparticles. The parameters influencing the NW self-assembly were studied and the compositional, morphological and structural analysis of the grown structures was performed. In all cases, NWs of several μm in length and with diameters as small as 15 nm were obtained. The experimental contribution of the Ph. D. candidate to the NWs growth study was mainly related to the substrates preparation, catalyst deposition and, morphological and elemental analysis of the grown samples. Moreover, the Ph. D. candidate has performed the functional analysis of In3Sb1Te2 and In-doped Sb NW-based PCM devices. To conduct that analysis, a suitable fabrication procedure of the devices and an appropriate electrical measuring set-up have been identified. Reversible and well reproducible phase change memory switching was demonstrated for In3Sb1Te2 and In-doped Sb NW devices, showing low working parameters, such as “RESET” voltage, current and power. The obtained results support the conclusion that In-based ultra-thin NWs are potential building blocks for the realization of ultra-scaled, high performance PCM devices.
Garbin, Daniele. "Etude de la variabilité des technologies PCM et OxRAM pour leur utilisation en tant que synapses dans les systèmes neuromorphiques". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT133/document.
Pełny tekst źródłaThe human brain is made of a large number of interconnected neural networks which are composed of neurons and synapses. With a low power consumption of only few Watts, the human brain is able to perform computational tasks that are out of reach for today’s computers, which are based on the Von Neumann architecture. Neuromorphic hardware design, taking inspiration from the human brain, aims to implement the next generation, non-Von Neumann computing systems. In this thesis, emerging non-volatile memory devices, specifically Phase-Change Memory (PCM) and Oxide-based resistive memory (OxRAM) devices, are studied as artificial synapses in neuromorphic systems. The use of PCM devices as binary probabilistic synapses is studied for complex visual pattern extraction applications, evaluating the impact of the PCM programming conditions on the system-level power consumption.A programming strategy is proposed to mitigate the impact of PCM resistance drift. It is shown that, using scaled devices, it is possible to reduce the synaptic power consumption. The OxRAM resistance variability is evaluated experimentally through electrical characterization, gathering statistics on both single memory cells and at array level. A model that allows to reproduce OxRAM variability from low to high resistance state is developed. An OxRAM-based convolutional neural network architecture is then proposed on the basis of this experimental work. By implementing the computation of convolution directly in memory, the Von Neumann bottleneck is avoided. Robustness to OxRAM variability is demonstrated with complex visual pattern recognition tasks such as handwritten characters and traffic signs recognition
Balasubramanian, Sanchayeni. "Improving Hard Disk Drive Write IO Performance with Phase Change Memory as a Buffer Cache". University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511881125562903.
Pełny tekst źródłaBaek, Seungcheol. "High-performance memory system architectures using data compression". Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51863.
Pełny tekst źródłaTrabelsi, Ahmed. "Modulation des niveaux de résistance dans une mémoire PCM pour des applications neuromorphiques". Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALT027.
Pełny tekst źródłaThe exponential growth of data in recent years has led to a significant increase in energy consumption, creating a pressing need for innovative memory technologies to overcome the limitations of conventional solutions. This data deluge has resulted in a forecasted consumption surge in data centers, with an expected fourfold increase in data by 2025 compared to the present volume. To address this challenge, emerging memory technologies such as RRAM (Resistive RAM), PCM (Phase-Change Memory), and MRAM (Magnetoresistive RAM) are being developed to offer high density, fast access times, and non-volatility, thereby revolutionizing storage and memory solutions (Molas & Nowak, 2021).One promising technique to address the need for innovative memory technologies is the use of frequency modulation to modulate resistance in PCM which is a crucial aspect of its use in neuromorphic computing. PCM is a non-volatile memory technology based on the reversible phase transition between amorphous and crystalline phases of certain materials. The ability to alter conductance levels makes PCM well-suited for synaptic realizations in neuromorphic computing. The progressive crystallization of the phase-change material and the subsequent increase in device conductance enable PCM to be used in neuromorphic applications. Additionally, PCM-based memristor neural networks have been developed, and the resistance drift effect in PCM has been quantified, opening up new paths for the development of PCM-based memristor neuromorphic accelerators. Furthermore, frequency modulation has been identified as a promising technique to modulate resistance in PCM. This approach can be applied to PCM as well as RRAM, and it is expected to yield improved learning effects in more complex networks using multi-level cells (Wang et al., 2011). The primary aim of this thesis is to explore innovative methods for controlling resistance levels in PCM devices with a focus on their application in neuromorphic systems. The research involves a comprehensive understanding of the mechanisms underlying PCM devices and an identification of parameters that may influence the reliability of these devices. Additionally, the thesis aims to propose a novel approach to effectively modulate resistance levels in PCM devices, contributing to advancements in this field
Jensen, Peter, i Christopher Thacker. "A NEW GENERATION OF RECORDING TECHNOLOGY THE SOLID STATE RECORDER". International Foundation for Telemetering, 1998. http://hdl.handle.net/10150/607372.
Pełny tekst źródłaThe Test & Evaluation community is starting to migrate toward solid state recording. This paper outlines some of the important areas that are new to solid state recording as well as examining some of the issues involved in moving to a direct recording methodology. Some of the parameters used to choose a solid state memory architecture are included. A matrix to compare various methods of data recording, such as solid state and magnetic tape recording, will be discussed. These various methods will be evaluated using the following parameters: Ruggedness (Shock, Vibration, Temperature), Capacity, and Reliability (Error Correction). A short discussion of data formats with an emphasis on efficiency and usability is included.
Kiouseloglou, Athanasios. "Caractérisation et conception d' architectures basées sur des mémoires à changement de phase". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT128/document.
Pełny tekst źródłaSemiconductor memory has always been an indispensable component of modern electronic systems. The increasing demand for highly scaled memory devices has led to the development of reliable non-volatile memories that are used in computing systems for permanent data storage and are capable of achieving high data rates, with the same or lower power dissipation levels as those of current advanced memory solutions.Among the emerging non-volatile memory technologies, Phase Change Memory (PCM) is the most promising candidate to replace conventional Flash memory technology. PCM offers a wide variety of features, such as fast read and write access, excellent scalability potential, baseline CMOS compatibility and exceptional high-temperature data retention and endurance performances, and can therefore pave the way for applications not only in memory devices, but also in energy demanding, high-performance computer systems. However, some reliability issues still need to be addressed in order for PCM to establish itself as a competitive Flash memory replacement.This work focuses on the study of embedded Phase Change Memory in order to optimize device performance and propose solutions to overcome the key bottlenecks of the technology, targeting high-temperature applications. In order to enhance the reliability of the technology, the stoichiometry of the phase change material was appropriately engineered and dopants were added, resulting in an optimized thermal stability of the device. A decrease in the programming speed of the memory technology was also reported, along with a residual resistivity drift of the low resistance state towards higher resistance values over time.A novel programming technique was introduced, thanks to which the programming speed of the devices was improved and, at the same time, the resistance drift phenomenon could be successfully addressed. Moreover, an algorithm for programming PCM devices to multiple bits per cell using a single-pulse procedure was also presented. A pulse generator dedicated to provide the desired voltage pulses at its output was designed and experimentally tested, fitting the programming demands of a wide variety of materials under study and enabling accurate programming targeting the performance optimization of the technology
Navarro, Gabriele. "Analyse de la fiabilité de mémoires à changement de phase embarquées basées sur des matériaux innovants". Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-01061792.
Pełny tekst źródłaKsiążki na temat "PCM memory"
Wadlow, Thomas A. Memory resident programming on the IBM PC. Reading, Mass: Addison-Wesley, 1987.
Znajdź pełny tekst źródłaProsise, Jeff. PCmagazine DOS 6 memory management with utilities. Emeryville, Calif: Ziff-Davis Press, 1993.
Znajdź pełny tekst źródłaMueller, Scott. Upgrading and repairing PCs. Indianapolis, IN: Que, 1998.
Znajdź pełny tekst źródłaStore, Linux General, red. Upgrading and repairing PCs. Indianapolis, Ind: Que, 2000.
Znajdź pełny tekst źródłaMueller, Scott. Upgrading and repairing PCs. Indianapolis, Ind: Que, 2001.
Znajdź pełny tekst źródłaHyman, Michael I. Memory resident utilities, interrupts, and disk management with MS and PC DOS. Portland, Or: Management Information Source, 1986.
Znajdź pełny tekst źródłaProsise, Jeff. PC magazine DOS 6 memory management with utilities. Emeryville, Calif: Ziff-Davis Press, 1993.
Znajdź pełny tekst źródłaUpgrading and repairing PCs. Indianapolis, IN: Que Pub., 2008.
Znajdź pełny tekst źródłaUpgrading and repairing PCs. Indianapolis, IN: Que, 2004.
Znajdź pełny tekst źródłaUpgrading and repairing PCs. Wyd. 2. Indianapolis, IN: Que, 2013.
Znajdź pełny tekst źródłaCzęści książek na temat "PCM memory"
Gleixner, Robert. "PCM Main Reliability Features". W Phase Change Memory, 89–124. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69053-7_5.
Pełny tekst źródłaVilla, Corrado. "PCM Array Architecture and Management". W Phase Change Memory, 285–311. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69053-7_10.
Pełny tekst źródłaSousa, Véronique, i Gabriele Navarro. "Material Engineering for PCM Device Optimization". W Phase Change Memory, 181–222. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69053-7_7.
Pełny tekst źródłaAtwood, Gregory. "PCM Applications and an Outlook to the Future". W Phase Change Memory, 313–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69053-7_11.
Pełny tekst źródłaNoé, Pierre, i Françoise Hippert. "Structure and Properties of Chalcogenide Materials for PCM". W Phase Change Memory, 125–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69053-7_6.
Pełny tekst źródłaKong, Dejiang, i Fei Wu. "Visual Dialog with Multi-turn Attentional Memory Network". W Advances in Multimedia Information Processing – PCM 2018, 611–21. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00776-8_56.
Pełny tekst źródłaRahiman, Amir Rizaan Abdul, i Putra Sumari. "Probability Based Page Data Allocation Scheme in Flash Memory". W Advances in Multimedia Information Processing - PCM 2009, 300–310. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10467-1_26.
Pełny tekst źródłaNoh, Tae Hoon, i Se Jin Kwon. "Memory Management Strategy for PCM-Based IoT Cloud Server". W Lecture Notes in Electrical Engineering, 69–77. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1059-1_7.
Pełny tekst źródłaChen, Kaimeng, Peiquan Jin i Lihua Yue. "Efficient Buffer Management for PCM-Enhanced Hybrid Memory Architecture". W Web Technologies and Applications, 29–40. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25255-1_3.
Pełny tekst źródłaLi, Fu, Shaowu Yang, Xiaodong Yi i Xuejun Yang. "Towards Visual SLAM with Memory Management for Large-Scale Environments". W Advances in Multimedia Information Processing – PCM 2017, 776–86. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77383-4_76.
Pełny tekst źródłaStreszczenia konferencji na temat "PCM memory"
Ferreira, Alexandre P., Miao Zhou, Santiago Bock, Bruce Childers, Rami Melhem i Daniel Mosse. "Increasing PCM main memory lifetime". W 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010). IEEE, 2010. http://dx.doi.org/10.1109/date.2010.5456923.
Pełny tekst źródłaLiu, Yining, Chuangshi Zhou i Xiaohua Cheng. "Hybrid SSD with PCM". W 2011 11th Annual Non-Volatile Memory Technology Symposium (NVMTS). IEEE, 2011. http://dx.doi.org/10.1109/nvmts.2011.6137103.
Pełny tekst źródłaChang, Yu-Ming, Yuan-Hao Chang, Hsiu-Chang Chen i Tei-Wei Kuo. "Enabling Hybrid PCM Memory System with Inherent Memory Management". W RACS '16: International Conference on Research in Adaptive and Convergent Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2987386.2987398.
Pełny tekst źródłaArjomand, Mohammad, Amin Jadidi, Mahmut T. Kandemir, Anand Sivasubramaniam i Chita Das. "MLC PCM main memory with accelerated read". W 2016 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). IEEE, 2016. http://dx.doi.org/10.1109/ispass.2016.7482082.
Pełny tekst źródłaJeong, Hongsik. "High density PCM(phase change memory) technology". W 2016 International SoC Design Conference (ISOCC). IEEE, 2016. http://dx.doi.org/10.1109/isocc.2016.7799850.
Pełny tekst źródłaBoybat, I., S. R. Nandakumar, M. Le Gallo, B. Rajendran, Y. Leblebici, A. Sebastian i E. Eleftheriou. "Impact of conductance drift on multi-PCM synaptic architectures". W 2018 Non-Volatile Memory Technology Symposium (NVMTS). IEEE, 2018. http://dx.doi.org/10.1109/nvmts.2018.8603100.
Pełny tekst źródłaCalderoni, A., M. Ferro, D. Ventrice, P. Fantini i D. Ielmini. "Physical Modeling and Control of Switching Statistics in PCM Arrays". W 2011 3rd IEEE International Memory Workshop (IMW). IEEE, 2011. http://dx.doi.org/10.1109/imw.2011.5873230.
Pełny tekst źródłaBez, Roberto. "Chalcogenide PCM: a memory technology for next decade". W 2009 IEEE International Electron Devices Meeting (IEDM). IEEE, 2009. http://dx.doi.org/10.1109/iedm.2009.5424415.
Pełny tekst źródłaShafiee, Amin, Benoit Charbonnier, Sudeep Pasricha i Mahdi Nikdast. "Design Space Exploration for PCM-based Photonic Memory". W GLSVLSI '23: Great Lakes Symposium on VLSI 2023. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3583781.3590228.
Pełny tekst źródłaJin, Peiquan, Xiaoliang Wang, Dezhi Zhang i Lihua Yue. "Effective simulation of DRAM/PCM-based hybrid memory". W the Thirteenth ACM International Conference. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3125503.3125564.
Pełny tekst źródłaRaporty organizacyjne na temat "PCM memory"
Murphy, Richard C. Building more powerful less expensive supercomputers using Processing-In-Memory (PIM) LDRD final report. Office of Scientific and Technical Information (OSTI), wrzesień 2009. http://dx.doi.org/10.2172/993898.
Pełny tekst źródłaMott, Joanna, Heather Brown, Di Kilsby, Emily Eller i Tshering Choden. Ferramenta de auto-avaliação de Igualdade de Género e Inclusão Social. The Sanitation Learning Hub, Institute of Development Studies, listopad 2022. http://dx.doi.org/10.19088/slh.2022.021.
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