scholarly journals Bounding Worst-Case Data Cache Behavior by Analytically Deriving Cache Reference Patterns

2005 ◽  
Author(s):  
H. Ramaprasad ◽  
F. Mueller
Keyword(s):  
Data Cache ◽  
Worst Case ◽  
Case Data

scholarly journals Bounding Worst-Case Data Cache Performance by Using Stack Distance

2009 ◽  
Vol 3 (4) ◽  
pp. 195-215 ◽  
Author(s):  
Yu Liu ◽  
Wei Zhang
Keyword(s):  
Data Cache ◽  
Cache Performance ◽  
Worst Case ◽  
Case Data

Calculation of the Worst-Case Data Patterns and Eye Diagram for Nonlinear High-Speed Links

2021 ◽  
pp. 1-5
Author(s):  
Xiuqin Chu ◽  
Na Li ◽  
Jun Wang ◽  
Yuhuan Luo ◽  
Feng Wu ◽  
...  
Keyword(s):  
High Speed ◽  
Worst Case ◽  
Eye Diagram ◽  
Case Data

scholarly journals Comprehensive Sensing Current Analysis and Its Guideline for the Worst-Case Scenario of RRAM Read Operation

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 224 ◽  
Author(s):  
Zhensen Tang ◽  
Yao Wang ◽  
Yaqing Chi ◽  
Liang Fang
Keyword(s):  
Case Scenario ◽  
Worst Case ◽  
Trade Off ◽  
Crossbar Array ◽  
Worst Case Scenario ◽  
Read Operation ◽  
Shunting Effect ◽  
Injection Effect ◽  
Parameter Dependent ◽  
Case Data

In this paper, the dependence of sensing currents on various device parameters is comprehensively studied by simulating the complete crossbar array rather than its equivalent analytical model. The worst-case scenario for read operation is strictly analyzed and defined in terms of selected location and data pattern, respectively, based on the effect of parasitic sneak paths and interconnection resistance. It is shown that the worst-case data pattern depends on the trade-off between the shunting effect of the parasitic sneak paths and the current injection effect of the parasitic sneak leakage, thus requiring specific analysis in practical simulations. In dealing with that, we propose a concept of the threshold array size incorporating the trade-off to define the parameter-dependent worst-case data pattern. This figure-of-merit provides guidelines for the worst-case scenario analysis of the crossbar array read operations.

Accident Epidemiology and the U.S. Chemical Industry: Accident History and Worst-Case Data from RMP*Info

Risk Analysis ◽  
2003 ◽  
Vol 23 (5) ◽  
pp. 865-881 ◽  
Author(s):  
Paul R. Kleindorfer ◽  
James C. Belke ◽  
Michael R. Elliott ◽  
Kiwan Lee ◽  
Robert A. Lowe ◽  
...  
Keyword(s):  
Chemical Industry ◽  
Worst Case ◽  
Case Data ◽  
The U.S

Worst-case data structures for the priority queue with attrition

1989 ◽  
Vol 31 (2) ◽  
pp. 69-75 ◽  
Author(s):  
Rajamani Sundar
Keyword(s):  
Data Structures ◽  
Priority Queue ◽  
Worst Case ◽  
Case Data

scholarly journals Encoding range minima and range top-2 queries

2014 ◽  
Vol 372 (2016) ◽  
pp. 20130131 ◽  
Author(s):  
Pooya Davoodi ◽  
Gonzalo Navarro ◽  
Rajeev Raman ◽  
S. Srinivasa Rao
Keyword(s):  
Data Structure ◽  
Lower Bounds ◽  
Query Time ◽  
Constant Time ◽  
Worst Case ◽  
Asymptotically Optimal ◽  
Random Array ◽  
Case Data ◽  
Natural Way

We consider the problem of encoding range minimum queries (RMQs): given an array A [1.. n ] of distinct totally ordered values, to pre-process A and create a data structure that can answer the query RMQ( i , j ), which returns the index containing the smallest element in A [ i .. j ], without access to the array A at query time. We give a data structure whose space usage is 2 n + o ( n ) bits, which is asymptotically optimal for worst-case data, and answers RMQs in O (1) worst-case time. This matches the previous result of Fischer and Heun, but is obtained in a more natural way. Furthermore, our result can encode the RMQs of a random array A in 1.919 n + o ( n ) bits in expectation, which is not known to hold for Fischer and Heun’s result. We then generalize our result to the encoding range top-2 query (RT2Q) problem, which is like the encoding RMQ problem except that the query RT2Q( i , j ) returns the indices of both the smallest and second smallest elements of A [ i .. j ]. We introduce a data structure using 3.272 n + o ( n ) bits that answers RT2Qs in constant time, and also give lower bounds on the effective entropy of the RT2Q problem.

Analysis of Worst-Case Data Dependent Temporal Approximation in Floating Point Units

2020 ◽  
pp. 1-1
Author(s):  
Chandan Kumar Jha ◽  
Ishita Doshi ◽  
Joycee Mekie
Keyword(s):  
Floating Point ◽  
Worst Case ◽  
Case Data
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