Literatura académica sobre el tema "Memory optimisation"
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Artículos de revistas sobre el tema "Memory optimisation"
Weinhardt, M. y W. Luk. "Memory access optimisation for reconfigurable systems". IEE Proceedings - Computers and Digital Techniques 148, n.º 3 (1 de mayo de 2001): 105–12. http://dx.doi.org/10.1049/ip-cdt:20010514.
Texto completoKulhavý, Rudolf y Petya Ivanova. "Memory-based prediction in control and optimisation". IFAC Proceedings Volumes 32, n.º 2 (julio de 1999): 4058–63. http://dx.doi.org/10.1016/s1474-6670(17)56692-6.
Texto completoSayadi, Fatma Elzahra, Marwa Chouchene, Haithem Bahri, Randa Khemiri y Mohamed Atri. "CUDA memory optimisation strategies for motion estimation". IET Computers & Digital Techniques 13, n.º 1 (6 de septiembre de 2018): 20–27. http://dx.doi.org/10.1049/iet-cdt.2017.0149.
Texto completoZhu, Zongwei, Xi Li, Chao Wang y Xuehai Zhou. "Memory power optimisation on low-bit multi-access cross memory address mapping schema". International Journal of Embedded Systems 6, n.º 2/3 (2014): 240. http://dx.doi.org/10.1504/ijes.2014.063822.
Texto completoMartin, Jose L. Risco, Oscar Garnica, Juan Lanchares, J. Ignacio Hidalgo y David Atienza. "Particle swarm optimisation of memory usage in embedded systems". International Journal of High Performance Systems Architecture 1, n.º 4 (2008): 209. http://dx.doi.org/10.1504/ijhpsa.2008.024205.
Texto completoBossard, Antoine. "Memory Optimisation on AVR Microcontrollers for IoT Devices’ Minimalistic Displays". Chips 1, n.º 1 (21 de abril de 2022): 2–13. http://dx.doi.org/10.3390/chips1010002.
Texto completoTirelli, D. y S. Mascelloni. "Characterisation and optimisation of shape memory alloys for seismic applications". Le Journal de Physique IV 10, PR9 (septiembre de 2000): Pr9–665—Pr9–670. http://dx.doi.org/10.1051/jp4:20009111.
Texto completoCao, Zhengnan, Xiaoqing Han, William Lyons y Fergal O'Rourke. "Energy management optimisation using a combined Long Short-Term Memory recurrent neural network – Particle Swarm Optimisation model". Journal of Cleaner Production 326 (diciembre de 2021): 129246. http://dx.doi.org/10.1016/j.jclepro.2021.129246.
Texto completoDing, Weijie, Jin Huang, Guanyu Shang, Xuexuan Wang, Baoqiang Li, Yunfei Li y Hourong Liu. "Short-Term Trajectory Prediction Based on Hyperparametric Optimisation and a Dual Attention Mechanism". Aerospace 9, n.º 8 (20 de agosto de 2022): 464. http://dx.doi.org/10.3390/aerospace9080464.
Texto completoThiruvady, Dhananjay, Asef Nazari y Aldeida Aleti. "Multi-objective Beam-ACO for Maximising Reliability and Minimising Communication Overhead in the Component Deployment Problem". Algorithms 13, n.º 10 (3 de octubre de 2020): 252. http://dx.doi.org/10.3390/a13100252.
Texto completoTesis sobre el tema "Memory optimisation"
Forrest, B. M. "Memory and optimisation in neural network models". Thesis, University of Edinburgh, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384164.
Texto completoFargus, Alexander. "Optimisation of correlation matrix memory prognostic and diagnostic systems". Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/9032/.
Texto completoUzor, Chigozirim. "Compact dynamic optimisation algorithm". Thesis, De Montfort University, 2015. http://hdl.handle.net/2086/13056.
Texto completoBeyler, Jean-Christophe. "Dynamic software memory access optimization : Dynamic low-cost reduction of memory latencies by binary analyses and transformations". Université Louis Pasteur (Strasbourg) (1971-2008), 2007. http://www.theses.fr/2007STR13171.
Texto completoThis thesis concerns the development of dynamic approaches for the control of the hardware/software couple. More precisely, works presented here have the main goal of minimizing program execution times on mono or multi-processor architectures, by anticipating memory accesses through dynamic prefetch of useful data in cache memory and in a way that is entirely transparent to the user. The developed systems consist in a dynamic analysis phase, where memory access latencies are measured, a phase of binary optimizing transformations when they have been evaluated as efficient, and where data prefetching instructions are inserted into the binary code, a dynamic analysis phase of the optimizations efficiency, and finally a canceling phase for transformations that have been evaluated as inefficient. Every phase applies individually to every memory access, and eventually applies several times if memory accesses have behaviors that are varying during the execution time of the target software
Maalej, Kammoun Maroua. "Low-cost memory analyses for efficient compilers". Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1167/document.
Texto completoThis thesis was motivated by the emergence of massively parallel processing and supercomputingthat tend to make computer programming extremely performing. Speedup, the power consump-tion, and the efficiency of both software and hardware are nowadays the main concerns of theinformation systems community. Handling memory in a correct and efficient way is a step towardless complex and more performing programs and architectures. This thesis falls into this contextand contributes to memory analysis and compilation fields in both theoretical and experimentalaspects.Besides the deep study of the current state-of-the-art of memory analyses and their limitations,our theoretical results stand in designing new algorithms to recover part of the imprecisionthat published techniques still show. Among the present limitations, we focus our research onthe pointer arithmetic to disambiguate pointers within the same data structure. We develop ouranalyses in the abstract interpretation framework. The key idea behind this choice is correctness,and scalability: two requisite criteria for analyses to be embedded to the compiler construction.The first alias analysis we design is based on the range lattice of integer variables. Given a pair ofpointers defined from a common base pointer, they are disjoint if their offsets cannot have valuesthat intersect at runtime. The second pointer analysis we develop is inspired from the Pentagonabstract domain. We conclude that two pointers do not alias whenever we are able to build astrict relation between them, valid at program points where the two variables are simultaneouslyalive. In a third algorithm we design, we combine both the first and second analysis, and enhancethem with a coarse grained but efficient analysis to deal with non related pointers.We implement these analyses on top of the LLVM compiler. We experiment and evaluate theirperformance based on two metrics: the number of disambiguated pairs of pointers compared tocommon analyses of the compiler, and the optimizations further enabled thanks to the extraprecision they introduce
Munns, Joseph. "Optimisation and applications of a Raman quantum memory for temporal modes of light". Thesis, Imperial College London, 2018. http://hdl.handle.net/10044/1/63867.
Texto completoAlsaiari, Mabkhoot Abdullah. "High throughput optimisation of functional nanomaterials and composite structures for resistive switching memory". Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/422863/.
Texto completoMarina, Sahakyan. "Optimisation des mises à jours XML pour les systèmes main-memory: implémentation et expériences". Phd thesis, Université Paris Sud - Paris XI, 2011. http://tel.archives-ouvertes.fr/tel-00641579.
Texto completoKaeslin, Alain E. "Performance Optimisation of Discrete-Event Simulation Software on Multi-Core Computers". Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191132.
Texto completoSIMLOX är en kommersiell mjukvara utvecklad av Systecon AB, vars huvudsakliga funktion är en händelsestyrd simuleringskärna för analys av underhållslösningar för komplexa tekniska system. För hantering av stora problem så används parallellexekvering för simuleringen, vilket i teorin borde ge en nästan linjär skalning med antal trådar. Prestandaförbättringen som observerats i praktiken var dock ytterst begränsad, varför en ordentlig analys av skalbarheten har gjorts i detta projekt. Genom användandet av ett profileringsverktyg med liten overhead och mikroarkitektur-analys, så kunde orsakerna hittas: atomiska operationer som skapar mycket overhead för kommunikation, dålig lokalitet ger fragmentering vid översättning till fysiska adresser och dåligt utnyttjande av TLB-cachen, och vissa flaskhalsar som kräver mycket CPU-kraft. Därefter implementerades och testade optimeringar för att undvika de identifierade problem. Testade lösningar inkluderar eliminering av dyra operationer, ökad effektivitet i minneshantering genom skalbara minneshanteringsalgoritmer och implementation av datastrukturer som ger bättre lokalitet och därmed bättre användande av cache-strukturen. Verifiering på verkliga testfall visade på uppsnabbningar på åtminstone 6.75 gånger på en processor med 8 kärnor. De flesta fall visade på en uppsnabbning med en faktor större än 7.2. Optimeringarna gav även en uppsnabbning med en faktor på åtminstone 1.5 vid sekventiell exekvering i en tråd. Slutsatsen är därmed att det är möjligt att uppnå nästan linjär skalning med antalet kärnor för denna typ av händelsestyrd simulering.
Laga, Arezki. "Optimisation des performance des logiciels de traitement de données sur les périphériques de stockage SSD". Thesis, Brest, 2018. http://www.theses.fr/2018BRES0087/document.
Texto completoThe growing volume of data poses a real challenge to data processing software like DBMS (DataBase Management Systems) and data storage infrastructure. New technologies have emerged in order to face the data volume challenges. We considered in this thesis the emerging new external memories like flash memory-based storage devices named SSD (Solid State Drive).SSD storage devices offer a performance gain compared to the traditional magnetic devices.However, SSD devices offer a new performance model that involves 10 cost optimization for data processing and management algorithms.We proposed in this thesis an 10 cost model to evaluate the data processing algorithms. This model considers mainly the SSD 10 performance and the data distribution.We also proposed a new external sorting algorithm: MONTRES. This algorithm includes optimizations to reduce the 10 cost when the volume of data is greater than the allocated memory space by an order of magnitude. We proposed finally a data prefetching mechanism: Lynx. This one makes use of a machine learning technique to predict and to anticipate future access to the external memory
Capítulos de libros sobre el tema "Memory optimisation"
Paviotti, Marco, Simon Cooksey, Anouk Paradis, Daniel Wright, Scott Owens y Mark Batty. "Modular Relaxed Dependencies in Weak Memory Concurrency". En Programming Languages and Systems, 599–625. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44914-8_22.
Texto completoBroderick, Ian y Enda Howley. "Particle Swarm Optimisation with Enhanced Memory Particles". En Lecture Notes in Computer Science, 254–61. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09952-1_24.
Texto completoPanda, Preeti Ranjan. "Power Optimisation Strategies Targeting the Memory Subsystem". En Designing Embedded Processors, 131–55. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5869-1_6.
Texto completoWhite, Leo y Alan Mycroft. "Concise Analysis Using Implication Algebras for Task-Local Memory Optimisation". En Static Analysis, 433–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38856-9_23.
Texto completoCatthoor, Francky, Sven Wuytack, Eddy De Greef, Florin Balasa, Lode Nachtergaele y Arnout Vandecappelle. "Optimisation of Global Data Transfer and Storage Organisation for Decreased Power and Area in Custom Data-Dominated Real-Time Systems". En Custom Memory Management Methodology, 1–15. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2849-1_1.
Texto completoBellizzi, Jennifer, Mark Vella, Christian Colombo y Julio Hernandez-Castro. "Real-Time Triggering of Android Memory Dumps for Stealthy Attack Investigation". En Secure IT Systems, 20–36. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70852-8_2.
Texto completoDodds, Mike, Mark Batty y Alexey Gotsman. "Compositional Verification of Compiler Optimisations on Relaxed Memory". En Programming Languages and Systems, 1027–55. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89884-1_36.
Texto completoCzezowski, Adam y Peter Strazdins. "Optimisations for the memory hierarchy of a Singular Value Decomposition algorithm implemented on the MIMD architecture". En High-Performance Computing and Networking, 215–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57981-8_119.
Texto completoAmine, Khalil. "Insights Into Simulated Annealing". En Advances in Computational Intelligence and Robotics, 121–39. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2857-9.ch007.
Texto completoIslekel, Ege Selin. "Nightmare Knowledges: Epistemologies of Disappearance". En Turkey's Necropolitical Laboratory, 253–72. Edinburgh University Press, 2019. http://dx.doi.org/10.3366/edinburgh/9781474450263.003.0012.
Texto completoActas de conferencias sobre el tema "Memory optimisation"
Turkington, Kieron, George A. Constantinides, Peter Y. K. Cheung y Konstantinos Masselos. "Co-optimisation of datapath and memory in outer loop pipelining". En 2008 International Conference on Field-Programmable Technology (FPT). IEEE, 2008. http://dx.doi.org/10.1109/fpt.2008.4762359.
Texto completoPalkovic, Martin, Henk Corporaal y Francky Catthoor. "Global memory optimisation for embedded systems allowed by code duplication". En the 2005 workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1140389.1140397.
Texto completoAbalenkovs, Maksims. "Performance optimisation of stencil-based codes for shared memory architectures". En 2017 11th European Conference on Antennas and Propagation (EUCAP). IEEE, 2017. http://dx.doi.org/10.23919/eucap.2017.7928861.
Texto completoCheng, Chuan y Christos-Savvas Bouganis. "Memory optimisation for hardware induction of axis-parallel decision tree". En 2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig). IEEE, 2014. http://dx.doi.org/10.1109/reconfig.2014.7032538.
Texto completoVogel, Pirmin, Andrea Marongiu y Luca Benini. "An Evaluation of Memory Sharing Performance for Heterogeneous Embedded SoCs with Many-Core Accelerators". En COSMIC '15: International Workshop on Code Optimisation for Multi and Many Cores. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2723772.2723775.
Texto completoSha, Jinze, Andrew Kadis, Fan Yang y Timothy D. Wilkinson. "Limited-memory BFGS Optimisation of Phase-Only Computer-Generated Hologram for Fraunhofer Diffraction". En Digital Holography and Three-Dimensional Imaging. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/dh.2022.w3a.3.
Texto completoPrakash, Ishan, Aniruddh Bansal, Rohit Verma y Rajeev Shorey. "SmartSplit: Latency-Energy-Memory Optimisation for CNN Splitting on Smartphone Environment". En 2022 14th International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2022. http://dx.doi.org/10.1109/comsnets53615.2022.9668610.
Texto completoSantos, Luis C., Filipe N. Santos, Andrae S. Aguiar, Antonio Valente y Pedro Costa. "Path Planning with Hybrid Maps for processing and memory usage optimisation". En 2022 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2022. http://dx.doi.org/10.1109/icarsc55462.2022.9784767.
Texto completoWang, Yongtian y John Macdonald. "Memory-Saving Techniques In Damped-Least-Squares Optimisation Of Complex Optical Systems". En 1988 International Congress on Optical Science and Engineering, editado por Andre Masson, Joachim J. Schulte-in-den-Baeumen y Hannfried Zuegge. SPIE, 1989. http://dx.doi.org/10.1117/12.949386.
Texto completoPrakash, Sidharth S. y Binsu C. Kovoor. "Performance optimisation of web applications using In-memory caching and asynchronous job queues". En 2016 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2016. http://dx.doi.org/10.1109/inventive.2016.7830234.
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