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TestU01: A C library for empirical testing of random number generators
 ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
, 2007
"... We introduce TestU01, a software library implemented in the ANSI C language, and offering a collection of utilities for the empirical statistical testing of uniform random number generators (RNGs). It provides general implementations of the classical statistical tests for RNGs, as well as several ot ..."
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Cited by 85 (3 self)
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We introduce TestU01, a software library implemented in the ANSI C language, and offering a collection of utilities for the empirical statistical testing of uniform random number generators (RNGs). It provides general implementations of the classical statistical tests for RNGs, as well as several others tests proposed in the literature, and some original ones. Predefined tests suites for sequences of uniform random numbers over the interval (0, 1) and for bit sequences are available. Tools are also offered to perform systematic studies of the interaction between a specific test and the structure of the point sets produced by a given family of RNGs. That is, for a given kind of test and a given class of RNGs, to determine how large should be the sample size of the test, as a function of the generator’s period length, before the generator starts to fail the test systematically. Finally, the library provides various types of generators implemented in generic form, as well as many specific generators proposed in the literature or found in widelyused software. The tests can be applied to instances of the generators predefined in the library, or to userdefined generators, or to streams of random numbers produced by any kind of device or stored in files. Besides introducing TestU01, the paper provides a survey and a classification of statistical tests for RNGs. It also applies batteries of tests to a long list of widely used RNGs.
Variable latency speculative addition: A new paradigm for arithmetic circuit design
 In Proceedings of the Conference and Exhibition on Design, Automation and Test in Europe (DATE’08
"... Adders are one of the key components in arithmetic circuits. Enhancing their performance can significantly improve the quality of arithmetic designs. This is the reason why the theoretical lower bounds on the delay and area of an adder have been analysed, and circuits with performance close to these ..."
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Cited by 23 (0 self)
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Adders are one of the key components in arithmetic circuits. Enhancing their performance can significantly improve the quality of arithmetic designs. This is the reason why the theoretical lower bounds on the delay and area of an adder have been analysed, and circuits with performance close to these bounds have been designed. In this paper, we present a novel adder design that is exponentially faster than traditional adders; however, it produces incorrect results, deterministically, for a very small fraction of input combinations. We have also constructed a reliable version of this adder that can detect and correct mistakes when they occur. This creates the possibility of a variablelatency adder that produces a correct result very fast with extremely high probability; however, in some rare cases when an error is detected, the correction term must be applied and the correct result is produced after some time. Since errors occur with extremely low probability, this new type of adder is significantly faster than stateoftheart adders when the overall latency is averaged over many additions. 1
Probability Distributions for DNA Sequence Comparisons
 LECTURES ON MATHEMATICS IN THE LIFE SCIENCES VOLUME 17
, 1986
"... Recently DNA sequence comparisons have focused on finding long matching segments between two sequences, rather than matching the entire sequences. Generalizations of the celebrated ErdosRenyi law give laws of large numbers and extreme value distributions for random variables equal to the length o ..."
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Cited by 3 (1 self)
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Recently DNA sequence comparisons have focused on finding long matching segments between two sequences, rather than matching the entire sequences. Generalizations of the celebrated ErdosRenyi law give laws of large numbers and extreme value distributions for random variables equal to the length of the longest exact match and longest approximate match between the sequences. The cases of independent, identically distributed sequences and of Markov chains are presented. In the final section, simulated sequences and sequences from bacteriophage lambda are analyzed in light of these theoretical results.