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Academic Articles & Research Papers
Showing 20 of 40 academic articles
Abraham Silberschatz • IEEE Transactions on Software Engineering
(1979)
Recent advances in technology have made the construction of general-purpose systems out of many small independent microprocessors feasible. One of the issue's concerning distributed systems is the question of appropriate language constructs...
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DOI: https://doi.org/10.1109/tse.1979.230190
Virginia M. Lo • Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)
(1983)
This thesis addresses the problem of task assignment in distributed systems. A distributed system is defined as any configuration of two or more processors, each with private memory, in which computations utilize the combined resources of t...
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Javier S. Turek, Dennis E. Shasha • Computer
(1992)
Known results regarding consensus among processors are surveyed and related to practice. The ideas embodied in the various proofs are explained. The goal is to give practitioners some sense of the system hardware and software guarantees tha...
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DOI: https://doi.org/10.1109/2.153253
Isabela‐Anda Dragomir, Ilie Gligorea, Romana Oancea, Aurelian Raţiu • Ludovika Egyetemi Kiadó eBooks
(2024)
CybersecurityNowadays, the Internet is integrated into society both through social interaction and business transactions, so the need for data protection and security has become increasingly important.In addition, not only computers, but al...
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cc-by-nc-nd
DOI: https://doi.org/10.36250/01195_07
Roheen Qamar, Baqar Ali Zardari • Mesopotamian Journal of Computer Science
(2023)
Neural networks, also known as artificial neural networks (ANNs) or artificially generated neural networks (SNNs) are a subset of machine learning that provide the foundation of deep learning techniques. Their name and form are inspired by ...
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cc-by
DOI: https://doi.org/10.58496/mjcsc/2023/015
Christos Christodoulou, Michael Georgiopoulos • CERN Document Server (European Organization for Nuclear Research)
(2001)
From the Book:
Since the early 1990s, a plethora of electromagnetic problems have been tackled using neural networks, some more successfully than others. Because neural networks and electromagnetics are two different scientific fields, not...
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Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Cohen, Jonathan et al. • arXiv (Cornell University)
(2014)
We present a library of efficient implementations of deep learning primitives. Deep learning workloads are computationally intensive, and optimizing their kernels is difficult and time-consuming. As parallel architectures evolve, kernels mu...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1410.0759
Loïc Henriet, Lucas Béguin, Adrien Signoles, Thierry Lahaye et al. • Quantum
(2020)
The manipulation of neutral atoms by light is at the heart of countless scientific discoveries in the field of quantum physics in the last three decades. The level of control that has been achieved at the single particle level within arrays...
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cc-by
DOI: https://doi.org/10.22331/q-2020-09-21-327
Sergey B. Bravyi, Oliver Dial, Jay Gambetta, Darı́o Gil et al. • Journal of Applied Physics
(2022)
For the first time in history, we are seeing a branching point in computing paradigms with the emergence of quantum processing units (QPUs). Extracting the full potential of computation and realizing quantum algorithms with a super-polynomi...
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Open Access
DOI: https://doi.org/10.1063/5.0082975
David Fernández‐Baca • IEEE Transactions on Software Engineering
(1989)
The author studies the complexity of the problem of allocating modules to processes in a distributed system to minimize total communication and execution costs. He shows that unless P=NP, there can be no polynomial-time epsilon -approximate...
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DOI: https://doi.org/10.1109/32.41334
Tawei Chou, Jacob A. Abraham • IEEE Transactions on Software Engineering
(1982)
In a distributed computing system made up of different types of processors each processor in the system may have different performance and reliability characteristics. In order to take advantage of this diversity of processing power, a modu...
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DOI: https://doi.org/10.1109/tse.1982.235574
Jeff Magee, Jeff Kramer, Morris S. Sloman • IEEE Transactions on Software Engineering
(1989)
The Conic environment provides a language-based approach to the building of distributed systems which combines the simplicity and safety of a language approach with the flexibility and accessibility of an operating systems approach. It prov...
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DOI: https://doi.org/10.1109/32.24720
Pankaj Jalote (1994)
1. Introduction. Basic Concepts and Definitions. Phases in Fault Tolerance. Overview of Hardware Fault Tolerance. Reliability and Availability. Summary. 2. Distributed Systems. System Model. Interprocess Communication. Ordering of Events an...
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Rob Strom, Shaula Yemini • ACM Transactions on Computer Systems
(1985)
Optimistic Recovery is a new technique supporting application-independent transparent recovery from processor failures in distributed systems. In optimistic recovery communication, computation and checkpointing proceed asynchronously. Synch...
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Open Access
DOI: https://doi.org/10.1145/3959.3962
Akash Kundu, Leopoldo Sarra • Communications Physics
(2026)
Abstract Quantum computing offers exciting opportunities for simulating complex quantum systems and optimizing large-scale combinatorial problems, but its practical use is limited by device noise and constrained connectivity. Designing quan...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s42005-025-02475-6
Harry R. Tennant • Defense Technical Information Center (DTIC)
(1981)
Despite a large amount of research on developing natural language understanding programs, little work has been done on evaluating their performance or potential. The evaluations that have been done have been unsystematic and incomplete. Thi...
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A.K. Jain, Jianchang Mao, K.M. Mohiuddin • Computer
(1996)
Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected simple processors. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the arti...
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DOI: https://doi.org/10.1109/2.485891
Hava T. Siegelmann • Birkhäuser Boston eBooks
(1999)
The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnecte...
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DOI: https://doi.org/10.1007/978-1-4612-0707-8
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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