Moore’s Law

Ghoting, Amol; Gunnels, John A.; Squillante, Mark S.; Meseguer, José; Cownie, James H.; Roweth, Duncan; Adve, Sarita V.; Boehm, Hans-J.; McKee, Sally A.; Wisniewski, Robert W.; Karypis, George; Malony, Allen D.; Gottlieb, Steven; Riesen, Rolf; Maccabe, Arthur B.; Bilardi, Gianfranco; Pietracaprina, Andrea; Kejariwal, Arun; Nicolau, Alexandru; Lengauer, Christian; Gustafson, John L.; Gropp, William; Prost, Jean-Pierre; Padua, David; Lowney, Geoff; Halstead, Robert H.; Nemirovsky, Mario; Amestoy, Patrick; Buttari, Alfredo; Duff, Iain S.; Guermouche, Abdou; L’Excellent, Jean-Yves; Uçar, Bora; Pakin, Scott

doi:10.1007/978-0-387-09766-4_81

Cited by 3 publications

(3 citation statements)

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“…Apple also followed suit along with other unicorns in Silicon Valley, most notably Facebook which also allegedly eavesdrops on people talking near a phone in which the Facebook app is installed (Lanier, 2014). The data could not be gathered or processed with an equal rise in data storage capacity and computing power, which was made available because of the advancement in the hardware technology as predicted by Moore's law (Gustafson, 2011).…”

Section: Algorithmic Bureaucracymentioning

confidence: 99%

An Islamic vision and approach for entrepreneurship: developing through a multi-stage comparative analysis of systems, ideologies and code of ethics

Javaid

2021

IJOES

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Purpose The purpose of this paper is to highlight the Islamic character of entrepreneurial activity along with its systemic, ideological and ethical particularities in contrast to the tech-based entrepreneurial model of Silicon Valley. Design/methodology/approach Hollingsworth’s framework of institutional analysis is used to analyze and compare the institutional design of tech-based entrepreneurship originated in Silicon Valley with the Islamic alternative. Findings An ideal Muslim entrepreneur will have a service-oriented-collectivist mindset, as opposed to an individualistic-self-centric mindset, where solving problems for all stakeholders is a priority instead of profit maximization at the expense of other stakeholders. A Muslim entrepreneur while ensuring the financial sustainability of the firm would avoid complexity on a systemic level, thus would adopt a personalized-family-like atmosphere. A Muslim entrepreneur will also constructively engage local stakeholders and will not possess a disintegrating tendency toward the local social structures. Practical implications The paper can help Muslim entrepreneurs to critically evaluate their entrepreneurial activities and firm design in contrast to the contemporary tech-based model. Originality/value A number of papers already have discussed the features of an Islamic model of entrepreneurship, however, none has done so while sequentially comparing the Islamic alternative with the contemporary model using Hollingsworth’s framework of institutional analysis. In this paper, the resulting model of Islamic entrepreneurship can be clearly evaluated and contrasted, feature by feature, with its tech-based counterpart.

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Section: Algorithmic Bureaucracymentioning

confidence: 99%

An Islamic vision and approach for entrepreneurship: developing through a multi-stage comparative analysis of systems, ideologies and code of ethics

Javaid

2021

IJOES

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“…Equation (1) also illustrates that every state has a corresponding amplitude value (α, β, γ, η), whose squared value corresponds to the probability of that state being the final state. system state = α(00)+β( 01)+γ (10)+ζ (11) (1) To understand the basic difference between classical and quantum systems, let us consider an analogy that presents a problem to determine the position (A, B, C, or D equivalent to states 00, 01, 10, and 11) of an object at a given instance. Figure 7 shows an example of how the solution approaches differ for classical and quantum systems.…”

Section: Two-qubit Superpositionmentioning

confidence: 99%

“…Moore's law states that the number of transistors doubles every two years on an Integrated Circuit. This doubling pattern is now at full capacity with high-end CPUs and GPUs [10]. Such physical saturation limits the computation power and causes processing, developmental, and discovery delays in the ML community.…”

Section: Introductionmentioning

confidence: 99%

Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead

et al. 2020

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Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. However, they are vulnerable to various security and reliability threats, at both hardware and software levels, that compromise their accuracy. These threats get aggravated in emerging edge ML devices that have stringent constraints in terms of resources (e.g., compute, memory, power/energy), and that therefore cannot employ costly security and reliability measures. Security, reliability, and vulnerability mitigation techniques span from network security measures to hardware protection, with an increased interest towards formal verification of trained ML models.This paper summarizes the prominent vulnerabilities of modern ML systems, highlights successful defenses and mitigation techniques against these vulnerabilities, both at the cloud (i.e., during the ML training phase) and edge (i.e., during the ML inference stage), discusses the implications of a resourceconstrained design on the reliability and security of the system, identifies verification methodologies to ensure correct system behavior, and describes open research challenges for building secure and reliable ML systems at both the edge and the cloud.

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Expansion of AI and ML Breakthroughs in HPC with Shift to Edge Computing in Remote Environments

Yadav

2024

High Performance Computing in Biomimetics

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Moore’s Law

Cited by 3 publications

References 0 publications

An Islamic vision and approach for entrepreneurship: developing through a multi-stage comparative analysis of systems, ideologies and code of ethics

An Islamic vision and approach for entrepreneurship: developing through a multi-stage comparative analysis of systems, ideologies and code of ethics

Robust Machine Learning Systems: Challenges,Current Trends, Perspectives, and the Road Ahead

Expansion of AI and ML Breakthroughs in HPC with Shift to Edge Computing in Remote Environments

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