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Relevant bibliographies by topics / Heterogeneous computing

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Academic literature on the topic 'Heterogeneous computing'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Heterogeneous computing"

1

Zahran, Mohamed. "Heterogeneous computing." Communications of the ACM 60, no. 3 (2017): 42–45. http://dx.doi.org/10.1145/3024918.

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Yamagiwa, Shinichi. "Heterogeneous Computing." Journal of the Institute of Image Information and Television Engineers 68, no. 10 (2014): 798–805. http://dx.doi.org/10.3169/itej.68.798.

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Kalinov, Alexey, Alexey Lastovetsky, and Yves Robert. "Heterogeneous computing." Parallel Computing 31, no. 7 (2005): 649–52. http://dx.doi.org/10.1016/j.parco.2005.04.001.

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Iyer, Ravi, and Dean Tullsen. "Heterogeneous Computing." IEEE Micro 35, no. 4 (2015): 4–5. http://dx.doi.org/10.1109/mm.2015.82.

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Rubin, Norm. "Heterogeneous computing." ACM SIGPLAN Notices 49, no. 8 (2014): 315–16. http://dx.doi.org/10.1145/2692916.2558891.

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Cerf, Vinton G. "On heterogeneous computing." Communications of the ACM 64, no. 12 (2021): 9. http://dx.doi.org/10.1145/3492896.

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Song, Changxu. "Analysis on Heterogeneous Computing." Journal of Physics: Conference Series 2031, no. 1 (2021): 012049. http://dx.doi.org/10.1088/1742-6596/2031/1/012049.

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Abstract In the Internet industry, with the popularization of informatization and the rapid increase in data volume, people have new requirements for storage space. At the same time, computer applications such as artificial intelligence and big data have rapidly increased demand for computing power and diversified application scenarios. Heterogeneous computing has become the focus of research. This article introduces the choice of architecture for heterogeneous computing systems and programming languages for heterogeneous computing. Some typical technologies of heterogeneous computing are illu

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Reichenbach, Marc, Philipp Holzinger, Konrad Häublein, Tobias Lieske, Paul Blinzer, and Dietmar Fey. "Heterogeneous Computing Utilizing FPGAs." Journal of Signal Processing Systems 91, no. 7 (2018): 745–57. http://dx.doi.org/10.1007/s11265-018-1382-7.

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Dar, Rameez Mushtaq, and Romana Riyaz. "Grid Computing: An Insight into Heterogeneous Computing Environment." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 2 (2017): 57–61. http://dx.doi.org/10.23956/ijarcsse/v7i2/0123.

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Siegel, Howard Jay, Henry G. Dietz, and John K. Antonio. "Software support for heterogeneous computing." ACM Computing Surveys 28, no. 1 (1996): 237–39. http://dx.doi.org/10.1145/234313.234411.

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Dissertations / Theses on the topic "Heterogeneous computing"

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Lu, Howard J. (Howard Jason). "Heterogeneous multithreaded computing." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36584.

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Jackson, Robert Owen. "Heterogeneous parallel computing." Thesis, University of Birmingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366162.

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Fagg, Graham Edward. "Enabling technologies for parallel heterogeneous computing." Thesis, University of Reading, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266150.

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Scogland, Thomas R. "Runtime Adaptation for Autonomic Heterogeneous Computing." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/71315.

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Heterogeneity is increasing across all levels of computing, with the rise of accelerators such as GPUs, FPGAs, and other coprocessors into everything from cell phones to supercomputers. More quietly it is increasing with the rise of NUMA systems, hierarchical caching, OS noise, and a myriad of other factors. As heterogeneity becomes a fact of life, efficiently managing heterogeneous compute resources is becoming a critical, and ever more complex, task. The focus of this dissertation is to lay the foundation for an autonomic system for heterogeneous computing, employing runtime adaptation to im

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Shum, Kam Hong. "Adaptive parallelism for computing on heterogeneous clusters." Thesis, University of Cambridge, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627563.

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Lee, Jaekyu. "Shared resource management for efficient heterogeneous computing." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50217.

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The demand for heterogeneous computing, because of its performance and energy efficiency, has made on-chip heterogeneous chip multi-processors (HCMP) become the mainstream computing platform, as the recent trend shows in a wide spectrum of platforms from smartphone application processors to desktop and low-end server processors. The performance of on-chip GPUs is not yet comparable to that of discrete GPU cards, but vendors have integrated more powerful GPUs and this trend will continue in upcoming processors. In this architecture, several system resources are shared between CPUs and GPUs. T

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Herdman, Andy. "The readying of applications for heterogeneous computing." Thesis, University of Warwick, 2017. http://wrap.warwick.ac.uk/102343/.

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High performance computing is approaching a potentially significant change in architectural design. With pressures on the cost and sheer amount of power, additional architectural features are emerging which require a re-think to the programming models deployed over the last two decades. Today's emerging high performance computing (HPC) systems are maximising performance per unit of power consumed resulting in the constituent parts of the system to be made up of a range of different specialised building blocks, each with their own purpose. This heterogeneity is not just limited to the hardware

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Sarjanoja, S. (Sampsa). "BM3D image denoising using heterogeneous computing platforms." Master's thesis, University of Oulu, 2015. http://urn.fi/URN:NBN:fi:oulu-201504141380.

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Noise reduction is one of the most fundamental digital image processing problems, and is often designed to be solved at an early stage of the image processing path. Noise appears on the images in many different ways, and it is inevitable. In general, various image processing algorithms perform better if their input is as error-free as possible. In order to keep the processing delays small in different computing platforms, it is important that the noise reduction is performed swiftly. The recent progress in the entertainment industry has led to major improvements in the computing capabilities o

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Elteir, Marwa Khamis. "A MapReduce Framework for Heterogeneous Computing Architectures." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/28786.

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Nowadays, an increasing number of computational systems are equipped with heterogeneous compute resources, i.e., following different architecture. This applies to the level of a single chip, a single node and even supercomputers and large-scale clusters. With its impressive price-to-performance ratio as well as power efficiently compared to traditional multicore processors, graphics processing units (GPUs) has become an integrated part of these systems. GPUs deliver high peak performance; however efficiently exploiting their computational power requires the exploration of a multi-dimensional s

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Lee, Young Choon. "Problem-centric scheduling for heterogeneous computing systems." Thesis, The University of Sydney, 2007. http://hdl.handle.net/2123/9321.

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This project addresses key scheduling problems in heterogeneous computing environments. Heterogeneous computing systems (HCSs) have received increased attention since the 1990s, particularly over the past 10 years with the popularity of grid computing systems. These computing environments consist of a variety of resources interconnected by a high-speed network. Many parallel and distributed applications can take advantage of this computing platform; however, resource heterogeneity and dynamism impose scheduling restrictions. It is extremely difficult for a single scheduling scheme to efficient

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Books on the topic "Heterogeneous computing"

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M, Eshaghian Mary, ed. Heterogeneous computing. Artech House, 1996.

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Jackson, Robert Owen. Heterogeneous parallel computing. University of Birmingham, 1999.

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Terzo, Olivier, Karim Djemame, Alberto Scionti, and Clara Pezuela, eds. Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602.

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J, Dongarra J., ed. High performance heterogeneous computing. John Wiley, 2009.

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Lastovetsky, Alexey. Parallel computing on heterogeneous networks. J. Wiley, 2003.

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Lastovetsky, Alexey. Parallel Computing on Heterogeneous Networks. John Wiley & Sons, Inc., 2003. http://dx.doi.org/10.1002/0471654167.

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Som, Sukhamoy. Node assignment in heterogeneous computing. Langley Research Center, 1993.

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Barkley, John F. Introduction to heterogeneous computing environments. U.S. Dept. of Commerce, National Institute of Standards and Technology, 1989.

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Barkley, John F. Introduction to heterogeneous computing environments. National Institute of Standards and Technology, 1989.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., ed. Node assigment in heterogeneous computing. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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Book chapters on the topic "Heterogeneous computing"

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Hluchý, Ladislav, Martin Bobák, Henning Müller, et al. "Heterogeneous Exascale Computing." In Recent Advances in Intelligent Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14350-3_5.

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Diogo, Miguel, and Clemens Grelck. "Towards Heterogeneous Computing without Heterogeneous Programming." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40447-4_18.

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Scionti, A., F. Lubrano, O. Terzo, and S. Mazumdar. "Heterogeneous Data Center Architectures: Software and Hardware Integration and Orchestration Aspects." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-1.

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Tsantekidis, M., M. Hamad, V. Prevelakis, and M. R. Agha. "Security for Heterogeneous Systems." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-10.

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Burgio, P., R. Cavicchioli, and M. Verucchi. "Real-Time Heterogeneous Platforms." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-11.

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Scionti, A., O. Terzo, F. Lubrano, C. Pezuela, and K. Djemame. "Future Challenges in Heterogeneity." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-12.

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Schubert, L., S. Bonfert, and S. Wesner. "Modular Operating Systems for Large-Scale, Distributed, and Heterogeneous Environments." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-2.

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Fumero, J., C. Kotselidis, F. Zakkak, et al. "Programming and Architecture Models." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-3.

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Ejarque, J., D. Jiménez-González, C. Álvarez, X. Martorell, and R. M. Badia. "Simplifying Parallel Programming and Execution for Distributed Heterogeneous Computing Platforms." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-4.

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De Landtsheer, R., J. C. Deprez, and L. Guedria. "Design-Time Tooling to Guide Programming for Embedded Heterogeneous Hardware Platforms." In Heterogeneous Computing Architectures. CRC Press, 2019. http://dx.doi.org/10.1201/9780429399602-5.

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Conference papers on the topic "Heterogeneous computing"

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Guo, Xi, Ming He, Shouhao Qin, Dexuan Wang, and Chenjun Li. "PS-Based Heterogeneous Computing Framework." In 2024 Sixth International Conference on Next Generation Data-driven Networks (NGDN). IEEE, 2024. http://dx.doi.org/10.1109/ngdn61651.2024.10744160.

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Shen, Jiamin, Yao Chen, Weng-Fai Wong, and Ee-Chien Chang. "T-Edge: Trusted Heterogeneous Edge Computing." In 2024 Annual Computer Security Applications Conference (ACSAC). IEEE, 2024. https://doi.org/10.1109/acsac63791.2024.00027.

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Jun, Soon. "Heterogeneous Computing." In Heterogeneous Computing. US DOE, 2025. https://doi.org/10.2172/2553033.

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"Proceedings Heterogeneous Computing Workshop." In Proceedings Heterogeneous Computing Workshop. IEEE, 1994. http://dx.doi.org/10.1109/hcw.1994.324970.

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Zahran, Mohamed. "Heterogeneous Computing." In Applicative 2016. ACM Press, 2016. http://dx.doi.org/10.1145/2959689.2960086.

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Rubin, Norm. "Heterogeneous computing." In the 19th ACM SIGPLAN symposium. ACM Press, 2014. http://dx.doi.org/10.1145/2555243.2558891.

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Mitra, Tulika. "Mobile heterogeneous computing." In ESWEEK'17: THIRTEENTH EMBEDDED SYSTEM WEEK. ACM, 2017. http://dx.doi.org/10.1145/3139315.3151619.

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"Heterogeneous computing workshop." In 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings. IEEE, 2004. http://dx.doi.org/10.1109/ipdps.2004.1303046.

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Crago, Steve, Kyle Dunn, Patrick Eads, et al. "Heterogeneous Cloud Computing." In 2011 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, 2011. http://dx.doi.org/10.1109/cluster.2011.49.

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Du, Dong, Yubin Xia, Binyu Zang, and Haibo Chen. "Heterogeneous Serverless Computing." In ACM TURC '23: ACM Turing Award Celebration Conference 2023. ACM, 2023. http://dx.doi.org/10.1145/3603165.3607393.

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Reports on the topic "Heterogeneous computing"

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Barkley, John F., and Karen Olsen. Introduction to heterogeneous computing environments. National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.sp.500-176.

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Duke, D. W., and T. P. Green. [Research toward a heterogeneous networked computing cluster]. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/674884.

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Skroch, D. A., and R. J. Fornaro. A heterogeneous hierarchical architecture for real-time computing. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/476634.

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Tran, C. V. Wide-Area, Heterogeneous, Distributed Computing: Toward Computational Grids. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada358636.

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Zhang, Bo, Philip Davis, Manish PArshar, Nicolas Morales, and Keita Teranishi. Toward Resilient Heterogeneous Computing Workflow through Kokkos-DataSpaces Integration. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1738875.

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Bowman, Ian, John Shalf, Kwan-Liu Ma, and Wes Bethel. Performance Modeling for 3D Visualization in a Heterogeneous Computing Environment. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/841324.

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Veracierto, Marcelo. Computing Equilibria of Stochastic Heterogeneous Agent Models Using Decision Rule Histories. Federal Reserve Bank of Chicago, 2020. http://dx.doi.org/10.21033/wp-2020-05.

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Barrett, Richard Frederick, Li Tang, and Sharon X. Hu. Performance and Energy Implications for Heterogeneous Computing Systems: A MiniFE Case Study. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1494614.

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Abu-Gazaleh, Nael. Using Heterogeneous High Performance Computing Cluster for Supporting Fine-Grained Parallel Applications. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada459900.

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Hou, Thomas Y. A Multiscale Finite Element Method for Computing Wave Propagation and Scattering in Heterogeneous Media. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada360925.

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