Effects of failure correlation on software in operation

2002 ◽  
Author(s):  
K. Goseva-Popstojanova ◽  
K. Trivedi
Keyword(s):  
Failure Correlation

Lung and myocardial thallium-201 kinetics in resting patients with congestive heart failure: Correlation with pulmonary capillary wedge pressure

1992 ◽  
Vol 123 (2) ◽  
pp. 427-432 ◽  
Author(s):  
Eulogio E. Martinez ◽  
Steven F. Horowitz ◽  
Helio J. Castello ◽  
Mario L.V. Castiglioni ◽  
Antonio C.C. Carvalho ◽  
...  
Keyword(s):  
Heart Failure ◽  
Congestive Heart Failure ◽  
Pulmonary Capillary Wedge Pressure ◽  
Thallium 201 ◽  
Pulmonary Capillary ◽  
Failure Correlation ◽  
Wedge Pressure

scholarly journals Fatal Void Size Comparisons in Via-Below and Via-Above Cu Dual-Damascene Interconnects

2004 ◽  
Vol 812 ◽  
Author(s):  
Z. -S. Choi ◽  
C. L. Gan ◽  
F. Wei ◽  
C. V. Thompson ◽  
J. H. Lee ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Failure Mechanisms ◽  
Simulation Tool ◽  
Void Size ◽  
Dual Damascene ◽  
Preferential Nucleation ◽  
Failure Correlation ◽  
Void Volumes ◽  
Damascene Interconnects ◽  
Critical Void

AbstractThe median-times-to-failure (t50's) for straight dual-damascene via-terminated copper interconnect structures, tested under the same conditions, depend on whether the vias connect down to underlaying leads (metal 2, M2, or via-below structures) or connect up to overlaying leads (metal 1, M1, or via-above structures). Experimental results for a variety of line lengths, widths, and numbers of vias show higher t50's for M2 structures than for analogous M1 structures. It has been shown that despite this asymmetry in lifetimes, the electromigration drift velocity is the same for these two types of structures, suggesting that fatal void volumes are different in these two cases. A numerical simulation tool based on the Korhonen model has been developed and used to simulate the conditions for void growth and correlate fatal void sizes with lifetimes. These simulations suggest that the average fatal void size for M2 structures is more than twice the size of that of M1 structures. This result supports an earlier suggestion that preferential nucleation at the Cu/Si3N4 interface in both M1 and M2 structures leads to different fatal void sizes, because larger voids are required to span the line thickness in M2 structures while smaller voids below the base of vias can cause failures in M1 structures. However, it is also found that the fatal void sizes corresponding to the shortest-times-to-failure (STTF's) are similar for M1 and M2, suggesting that the voids that lead to the shortest lifetimes occur at or in the vias in both cases, where a void need only span the via to cause failure. Correlation of lifetimes and critical void volumes provides a useful tool for distinguishing failure mechanisms.

Reliability and Performance Models for Grid Computing

2010 ◽  
pp. 219-245 ◽  
Author(s):  
Yuan-Shun Dai ◽  
Jack Dongarra
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Optimization Problems ◽  
Data Dependence ◽  
Performance Models ◽  
Task Partitioning ◽  
Modeling And Analysis ◽  
Failure Correlation ◽  
And Performance

Grid computing is a newly developed technology for complex systems with large-scale resource sharing, wide-area communication, and multi-institutional collaboration. It is hard to analyze and model the Grid reliability because of its largeness, complexity and stiffness. Therefore, this chapter introduces the Grid computing technology, presents different types of failures in grid system, models the grid reliability with star structure and tree structure, and finally studies optimization problems for grid task partitioning and allocation. The chapter then presents models for star-topology considering data dependence and treestructure considering failure correlation. Evaluation tools and algorithms are developed, evolved from Universal generating function and Graph Theory. Then, the failure correlation and data dependence are considered in the model. Numerical examples are illustrated to show the modeling and analysis.

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