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Low-level database operators often admit multiple physical implementations ("kernels") that are semantically equivalent but have vastly different performance characteristics depending on the input data distribution. Existing database…

Databases · Computer Science 2026-02-05 Zijie Zhao , Ryan Marcus

Test-time scaling is a promising new approach to language modeling that uses extra test-time compute to improve performance. Recently, OpenAI's o1 model showed this capability but did not publicly share its methodology, leading to many…

We initiate a systematic study of the computational complexity of property testing, focusing on the relationship between query and time complexity. While traditional work in property testing has emphasized query complexity, relatively…

Computational Complexity · Computer Science 2026-03-12 Renato Ferreira Pinto , Diptaksho Palit , Sofya Raskhodnikova

Supercomputers are equipped with an increasingly large number of cores to use computational power as a way of solving problems that are otherwise intractable. Unfortunately, getting serial algorithms to run in parallel to take advantage of…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-31 Faisal N. Abu-Khzam , Khuzaima Daudjee , Amer E. Mouawad , Naomi Nishimura

Performance tools for emerging heterogeneous exascale platforms must address two principal challenges when analyzing execution measurements. First, measurement of large-scale executions may record mountains of performance data. Second,…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-11 Jonathon Anderson , Yumeng Liu , John Mellor-Crummey

We investigate the parallel performance of Parallel Spectral Deferred corrections, a numerical approach that provides small-scale parallelism for the numerical solution of initial value problems. The scheme is applied to the shallow-water…

Computational Engineering, Finance, and Science · Computer Science 2026-03-04 Philip Freese , Sebastian Götschel , Thibaut Lunet , Daniel Ruprecht , Martin Schreiber

Quantum computing promises polynomial and exponential speedups in many domains, such as unstructured search and prime number factoring. However, quantum programs yield probabilistic outputs from exponentially growing distributions and are…

Software Engineering · Computer Science 2024-10-29 Noah H. Oldfield , Christoph Laaber , Tao Yue , Shaukat Ali

There are billions of lines of sequential code inside nowadays' software which do not benefit from the parallelism available in modern multicore architectures. Automatically parallelizing sequential code, to promote an efficient use of the…

Programming Languages · Computer Science 2016-04-13 Alcides Fonseca , Bruno Cabral , João Rafael , Ivo Correia

Testing random number generators is a very important task that, in the resent past, has taken upwards of twelve hours when testing with the current agship testing suite TestU01. Through this paper we will discuss the possible performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-27 Joshua Beizer

In this paper, we address some of the key limitations to realizing a generic heterogeneous parallel programming model for quantum-classical heterogeneous platforms. We discuss our experience in enabling user-level multi-threading in QCOR as…

The design of heterogeneous systems that include domain specific accelerators is a challenging and time-consuming process. While taking into account area constraints, designers must decide which parts of an application to accelerate in…

The standard RSA relies on multiple big-number modular exponentiation operations and longer key-length is required for better protection. This imposes a hefty time penalty for encryption and decryption. In this study, we analyzed and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-14 Jun-jie Liu , Kang-Too Tsang , Yu-Hui Deng

The frequent elements problem, a key component in demanding stream-data analytics, involves selecting elements whose occurrence exceeds a user-specified threshold. Fast, memory-efficient $\epsilon$-approximate synopsis algorithms select all…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-04 Victor Jarlow , Charalampos Stylianopoulos , Marina Papatriantafilou

We revisit test-time scaling for language model reasoning and ask a fundamental question: at equal token budget and compute, is it better to run multiple independent chains in parallel, or to run fewer chains that iteratively refine through…

Machine Learning · Computer Science 2025-11-05 Aman Sharma , Paras Chopra

Parallel-across-the method time integration can provide small scale parallelism when solving initial value problems. Spectral deferred corrections (SDC) with a diagonal sweeper, which is closely related to iterated Runge-Kutta methods…

Numerical Analysis · Mathematics 2025-02-12 Gayatri Čaklović , Thibaut Lunet , Sebastian Götschel , Daniel Ruprecht

We propose an effective parallel program debugging approach based on the timing annotation technique. With prevalent multi-core platforms, parallel programming is required to fully utilize the computing power. However, the non-determinism…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-10 Yun Chang , Hsin-I Wu , Ren-Song Tsay

Writing concurrent programs is a hard task, even when using high-level synchronization primitives such as transactional memories together with a functional language with well-controlled side-effects such as Haskell, because the…

Logic in Computer Science · Computer Science 2013-12-11 Romain Demeyer , Wim Vanhoof

There has been considerable recent interest in distribution-tests whose run-time and sample requirements are sublinear in the domain-size $k$. We study two of the most important tests under the conditional-sampling model where each query…

Data Structures and Algorithms · Computer Science 2015-04-17 Moein Falahatgar , Ashkan Jafarpour , Alon Orlitsky , Venkatadheeraj Pichapathi , Ananda Theertha Suresh

We propose new sequential sorting operations by adapting techniques and methods used for designing parallel sorting algorithms. Although the norm is to parallelize a sequential algorithm to improve performance, we adapt a contrarian…

Data Structures and Algorithms · Computer Science 2016-09-01 Alexandros V Gerbessiotis

We show how to extend classical work-stealing to deal also with data parallel tasks that can require any number of threads r >= 1 for their execution. We explain in detail the so introduced idea of work-stealing with deterministic…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-12-23 Martin Wimmer , Jesper Larsson Träff
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