Cloud-Based Scalable Parallel Electromagnetic Tools for Full-System Simulation

2011 ◽  
Author(s):  
Vikram Jandhyala ◽  
Dipanjan Gope ◽  
Swagato Chakraborty ◽  
Xiren Wang
Keyword(s):  
Large Scale ◽  
Consumer Electronics ◽  
Boundary Element Methods ◽  
Public Cloud ◽  
Full System ◽  
Computing Systems ◽  
Parasitic Extraction ◽  
On Demand ◽  
Commodity Computing ◽  
Eda Tools

Large-scale public cloud commodity computing is a potential paradigm-shifter for EDA tools. However, to go beyond merely web-hosted software and to exploit the true power of on-demand scalable computing is as yet an unmet challenge on many fronts. In this paper, we examine one computationally expensive and rapidly growing area within EDA as a candidate for the cloud, namely parasitic extraction and electromagnetic field simulation. With the growing emphasis on multifunctional systems in consumer electronics around commodity chips, the need for scale and speed in such tools is paramount. We examine from three aspects the suitability of and modifications needed to accelerated multilevel algorithms in boundary element methods in order to ensure cloud deployment: scalability without hitting Amdahl’s law prematurely, fault tolerance with low time penalties in realistic computing systems, and encryption-free approaches to ensuring IP security.

Cloud Computing Security

2012 ◽  
Vol 4 (1) ◽  
pp. 52-66 ◽  
Author(s):  
Junaid Arshad ◽  
Paul Townend ◽  
Jie Xu ◽  
Wei Jie
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
State Of The Art ◽  
Emerging Technology ◽  
The State ◽  
Computing Systems ◽  
Cloud Computing Security ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Security Challenges

The evolution of modern computing systems has lead to the emergence of Cloud computing. Cloud computing facilitates on-demand establishment of dynamic, large scale, flexible, and highly scalable computing infrastructures. However, as with any other emerging technology, security underpins widespread adoption of Cloud computing. This paper presents the state-of-the-art about Cloud computing along with its different deployment models. The authors also describe various security challenges that can affect an organization’s decision to adopt Cloud computing. Finally, the authors list recommendations to mitigate with these challenges. Such review of state-of-the-art about Cloud computing security can serve as a useful barometer for an organization to make an informed decision about Cloud computing adoption.

Scalable MD5 Crypt Cracker on PetaScale Supercomputer

2012 ◽  
Vol 532-533 ◽  
pp. 1080-1084 ◽  
Author(s):  
Zhi Cai Shi ◽  
Can Qun Yang ◽  
Qiang Wu
Keyword(s):  
Large Scale ◽  
Experimental Results ◽  
Brute Force ◽  
Full System ◽  
Computing Systems ◽  
Unix System ◽  
Cryptographic Algorithm ◽  
Brute Force Attack ◽  
Heterogeneous Programming ◽  
Password Cracking

MD5 Crypt is a cryptographic algorithm used commonly in UNIX system for authentication. Thanks to the additional randomization of the salt and complexity of the scheme, it makes the traditional password cracking techniques invalid on common computing systems so that the security of the system is guaranteed. As a result of the thriving of petaflops heterogeneous supercomputer system in recent decades, the security of MD5 Crypt is facing a threat of brute-force attack again. However, the complexity of heterogeneous programming and the sophistication of large-scale parallelism still hamper the password recovering. In this paper, we implemented brute-force attack of MD5 Crypt on Tianhe-1A，the world’s fastest supercomputer， by organizing the assignment between CPU and GPU reasonably and making several optimizations according to MD5 Crypt for GPU. Based on the experimental results, our algorithm achieves a great scalability. It checked more than 1.8 billion passwords in a second on the full system. Thus it issues a new challenge to the security of MD5 crypt for authentication.

scholarly journals An Overview of Public Cloud Security Issues

2014 ◽  
Vol 3 (2) ◽  
pp. 440-445
Author(s):  
Atefeh Heydari ◽  
Mohammad Ali Tavakoli ◽  
Mohammad Riazi
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Physical Space ◽  
Public Cloud ◽  
Huge Number ◽  
Security Issues ◽  
On Demand ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Computing Platforms

Traditionally, computational needs of organizations were alleviated by purchasing, updating and maintaining required equipments. Beside expensive devices, physical space to hold them, technical staffs to maintain them and many other side costs were essential prerequisites of this matter. Nowadays with the development of cloud computing services, a huge number of peoples and organizations are served in terms of computational needs by large scale computing platforms. Offering enormous amounts of economical compute resources on-demand motivates organizations to outsource their computational needs incrementally. Public cloud computing vendors offer their infrastructure to the customers via the internet. It means that the control of customers’ data is not in their hands anymore. Unfortunately various security issues are emerged from this subject. In this paper the security issues of public cloud computing are overviewed. More destructive security issues are highlighted in order to be used by organizations in making better decisions for moving to cloud.

Public cloud computing for seismological research: Calculating large-scale noise cross-correlations using ALIYUN

2018 ◽  
Vol 31 (5-6) ◽  
pp. 227-233
Author(s):  
Weitao Wang ◽  
◽  
Baoshan Wang ◽  
Xiufen Zheng ◽  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Public Cloud ◽  
Cross Correlations

scholarly journals A Survey on Machine-Learning Based Security Design for Cyber-Physical Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5458
Author(s):  
Sangjun Kim ◽  
Kyung-Joon Park
Keyword(s):  
Machine Learning ◽  
Physical System ◽  
Large Scale ◽  
Computing System ◽  
Future Research ◽  
Physical Security ◽  
Computing Systems ◽  
Physical Systems ◽  
Security Research ◽  
Simultaneous Control

A cyber-physical system (CPS) is the integration of a physical system into the real world and control applications in a computing system, interacting through a communications network. Network technology connecting physical systems and computing systems enables the simultaneous control of many physical systems and provides intelligent applications for them. However, enhancing connectivity leads to extended attack vectors in which attackers can trespass on the network and launch cyber-physical attacks, remotely disrupting the CPS. Therefore, extensive studies into cyber-physical security are being conducted in various domains, such as physical, network, and computing systems. Moreover, large-scale and complex CPSs make it difficult to analyze and detect cyber-physical attacks, and thus, machine learning (ML) techniques have recently been adopted for cyber-physical security. In this survey, we provide an extensive review of the threats and ML-based security designs for CPSs. First, we present a CPS structure that classifies the functions of the CPS into three layers: the physical system, the network, and software applications. Then, we discuss the taxonomy of cyber-physical attacks on each layer, and in particular, we analyze attacks based on the dynamics of the physical system. We review existing studies on detecting cyber-physical attacks with various ML techniques from the perspectives of the physical system, the network, and the computing system. Furthermore, we discuss future research directions for ML-based cyber-physical security research in the context of real-time constraints, resiliency, and dataset generation to learn about the possible attacks.

scholarly journals How Much Can Large-Scale Video-on-Demand Benefit From Users' Cooperation?

2015 ◽  
Vol 23 (6) ◽  
pp. 1846-1861 ◽  
Author(s):  
Delia Ciullo ◽  
Valentina Martina ◽  
Michele Garetto ◽  
Emilio Leonardi
Keyword(s):  
Large Scale ◽  
Video On Demand ◽  
On Demand

Large-Scale Video-on-Demand Systems

2006 ◽  
pp. 391-399
Author(s):  
J. Feng ◽  
W. F. Poon ◽  
K. T. Lo
Keyword(s):  
Large Scale ◽  
Video On Demand ◽  
Demand Systems ◽  
On Demand

Using Broadcast Networks to Create On-demand Extremely Large Scale High-throughput Computing Infrastructures

2012 ◽  
Vol 10 (3) ◽  
pp. 419-445 ◽  
Author(s):  
Rostand Costa ◽  
Francisco Brasileiro ◽  
Guido Lemos Filho ◽  
Dênio Sousa
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Broadcast Networks ◽  
High Throughput Computing ◽  
On Demand
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