Exploiting parallelism through run-time analysis on a vector processor (abstract)

1990 ◽  
Author(s):  
V. P. Krothapalli ◽  
P. Sadayappan
Keyword(s):  
Time Analysis ◽  
Vector Processor ◽  
Run Time Analysis ◽  
Run Time

scholarly journals Run-Time Analysis for Atomicity

2003 ◽  
Vol 89 (2) ◽  
pp. 191-209 ◽  
Author(s):  
Liqiang Wang ◽  
Scott D. Stoller
Keyword(s):  
Time Analysis ◽  
Run Time Analysis ◽  
Run Time

scholarly journals Program Instrumentation and Run-Time Analysis of Scoped Memory in Java

2005 ◽  
Vol 113 ◽  
pp. 105-121 ◽  
Author(s):  
D. Garbervetsky ◽  
C. Nakhli ◽  
S. Yovine ◽  
H. Zorgati
Keyword(s):  
Time Analysis ◽  
Program Instrumentation ◽  
Run Time Analysis ◽  
Run Time

scholarly journals PRACTICALITY AND TIME COMPLEXITY OF A SPARSIFIED RNA FOLDING ALGORITHM

2012 ◽  
Vol 10 (02) ◽  
pp. 1241007 ◽  
Author(s):  
SLAVICA DIMITRIEVA ◽  
PHILIPP BUCHER
Keyword(s):  
Time Complexity ◽  
Rna Folding ◽  
Minimum Free Energy ◽  
Energy Structure ◽  
Base Pairing ◽  
Time Analysis ◽  
Folding Algorithm ◽  
Run Time Analysis ◽  
Run Time ◽  
Standard Energy

Commonly used RNA folding programs compute the minimum free energy structure of a sequence under the pseudoknot exclusion constraint. They are based on Zuker's algorithm which runs in time O(n3). Recently, it has been claimed that RNA folding can be achieved in average time O(n2) using a sparsification technique. A proof of quadratic time complexity was based on the assumption that computational RNA folding obeys the "polymer-zeta property". Several variants of sparse RNA folding algorithms were later developed. Here, we present our own version, which is readily applicable to existing RNA folding programs, as it is extremely simple and does not require any new data structure. We applied it to the widely used Vienna RNAfold program, to create sibRNAfold, the first public sparsified version of a standard RNA folding program. To gain a better understanding of the time complexity of sparsified RNA folding in general, we carried out a thorough run time analysis with synthetic random sequences, both in the context of energy minimization and base pairing maximization. Contrary to previous claims, the asymptotic time complexity of a sparsified RNA folding algorithm using standard energy parameters remains O(n3) under a wide variety of conditions. Consistent with our run-time analysis, we found that RNA folding does not obey the "polymer-zeta property" as claimed previously. Yet, a basic version of a sparsified RNA folding algorithm provides 15- to 50-fold speed gain. Surprisingly, the same sparsification technique has a different effect when applied to base pairing optimization. There, its asymptotic running time complexity appears to be either quadratic or cubic depending on the base composition. The code used in this work is available at: http://sibRNAfold.sourceforge.net/ .

scholarly journals EnergyPlus Run Time Analysis

2008 ◽  
Author(s):  
Tianzhen Hong ◽  
Fred Buhl ◽  
Philip Haves
Keyword(s):  
Time Analysis ◽  
Run Time Analysis ◽  
Run Time
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