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In competitive parallel computing, the identical copies of a code in a phase of a sequential program are assigned to processor cores and the result of the fastest core is adopted. In the literature, it is reported that a superlinear speedup…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-22 Naoki Yonezawa

We revisit the outlier hypothesis testing framework of Li \emph{et al.} (TIT 2014) and derive fundamental limits for the optimal test under the generalized Neyman-Pearson criterion. In outlier hypothesis testing, one is given multiple…

Information Theory · Computer Science 2022-02-15 Lin Zhou , Yun Wei , Alfred Hero

We prove that parallel processing with homogeneous processors is logically equivalent to fast serial processing. The reverse proposition can also be used to identify obscure opportunities for applying parallelism. To our knowledge, this…

Performance · Computer Science 2020-10-05 Neil J. Gunther

Properties such as provable security and correctness for randomized programs are naturally expressed relationally as approximate equivalences. As a result, a number of relational program logics have been developed to reason about such…

Logic in Computer Science · Computer Science 2024-12-04 Philipp G. Haselwarter , Kwing Hei Li , Alejandro Aguirre , Simon Oddershede Gregersen , Joseph Tassarotti , Lars Birkedal

In this paper, we study the problem of generating inputs to a higher-order program causing it to error. We first study the problem in the setting of PCF, a typed, core functional language and contribute the first relatively complete method…

Programming Languages · Computer Science 2015-04-22 Phuc C. Nguyen , David Van Horn

Randomized parallel algorithms for many fundamental problems achieve optimal linear work in expectation, but upgrading this guarantee to hold with high probability (whp) remains a recurring theoretical challenge. In this paper, we address…

Data Structures and Algorithms · Computer Science 2026-03-03 Chase Hutton , Adam Melrod

Parallel Monte Carlo simulations often expose faults in random number generators

Distributed, Parallel, and Cluster Computing · Computer Science 2011-04-04 Boris D. Lubachevsky

This paper investigates the error probability of a stochastic decision and the way in which it differs from the error probability of an optimal decision, i.e., the maximum a posteriori decision. This paper calls attention to the fact that…

Information Theory · Computer Science 2017-05-01 Jun Muramatsu , Shigeki Miyake

A central approach to algorithmic derandomization is to construct probability distributions with small support that "fool" randomized algorithms, often enabling efficient parallel (NC) implementations. An abstraction of this idea is fooling…

Data Structures and Algorithms · Computer Science 2026-01-27 Jeff Giliberti , David G. Harris

A lower bound on the minimum error probability for multihypothesis testing is established. The bound, which is expressed in terms of the cumulative distribution function of the tilted posterior hypothesis distribution given the observation…

Information Theory · Computer Science 2011-07-19 Po-Ning Chen , Fady Alajaji

Quantitative research relies heavily on coding, and coding errors are relatively common even in published research. In this paper, we examine whether individuals are more or less likely to check their code depending on the results they…

General Economics · Economics 2025-09-26 Bruno Ferman , Lucas Finamor

Flaky tests can make automated software testing unreliable due to their unpredictable behavior. These tests can pass or fail on the same code base on multiple runs. However, flaky tests often do not refer to any fault, even though they can…

Software Engineering · Computer Science 2025-10-31 Hasnain Iqbal , Zerina Begum , Kazi Sakib

The purpose of this book is to help you program shared-memory parallel systems without risking your sanity. Nevertheless, you should think of the information in this book as a foundation on which to build, rather than as a completed…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-13 Paul E. McKenney

We introduce process-oriented programming as a natural extension of object-oriented programming for parallel computing. It is based on the observation that every class of an object-oriented language can be instantiated as a process,…

Programming Languages · Computer Science 2014-07-22 Edward Givelberg

Optimistic parallelization is a promising approach for the parallelization of irregular algorithms: potentially interfering tasks are launched dynamically, and the runtime system detects conflicts between concurrent activities, aborting and…

Programming Languages · Computer Science 2012-06-28 Francesco Versaci , Keshav Pingali

A sumtest for a discrete semimeasure $P$ is a function $f$ mapping bitstrings to non-negative rational numbers such that \[ \sum P(x)f(x) \le 1 \,. \] Sumtests are the discrete analogue of Martin-L\"of tests. The behavior of sumtests for…

Computational Complexity · Computer Science 2013-12-09 Bruno Bauwens

Polymorphism in programming languages enables code reuse. Here, we show that polymorphism has broad applicability far beyond computations for technical computing: parallelism in distributed computing, presentation of visualizations of…

Programming Languages · Computer Science 2014-11-07 Jiahao Chen , Alan Edelman

Let L be some extension of classical propositional logic. The non-iterated probabilistic logic over L, is the logic PL that is defined by adding non-nested probabilistic operators in the language of L. For example in PL we can express a…

Logic in Computer Science · Computer Science 2019-02-12 Ioannis Kokkinis

We show how phase and amplitude estimation algorithms can be parallelized. This can reduce the gate depth of the quantum circuits to that of a single Grover operator with a small overhead. Further, we show that for quantum amplitude…

Quantum Physics · Physics 2022-12-19 M. C. Braun , T. Decker , N. Hegemann , S. F. Kerstan

We study termination of higher-order probabilistic functional programs with recursion, stochastic conditioning and sampling from continuous distributions. Reasoning about the termination probability of programs with continuous distributions…

Programming Languages · Computer Science 2021-04-13 Raven Beutner , Luke Ong