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The growing reliance on computer systems, particularly personal computers (PCs), necessitates heightened reliability to uphold user satisfaction. This research paper presents an in-depth analysis of extensive system telemetry data,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-02 Priyanka Mudgal , Rita H. Wouhaybi

Computer architecture design space is vast and complex. Tools are needed to explore new ideas and gain insights quickly, with low efforts and at a desired accuracy. We propose Calipers, a criticality-based framework to model key…

Performance · Computer Science 2022-01-19 Hossein Golestani , Rathijit Sen , Vinson Young , Gagan Gupta

A single-sensor two-detectors system is considered where the sensor communicates with both detectors and Detector 1 communicates with Detector 2, all over noise-free rate-limited links. The sensor and both detectors observe discrete…

Information Theory · Computer Science 2019-07-19 Pierre Escamilla , Michèle Wigger , Abdellatif Zaidi

We present a federated, asynchronous, memory-limited algorithm for online task scheduling across large-scale networks of hundreds of workers. This is achieved through recent advancements in federated edge computing that unlocks the ability…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-29 Andreas Grammenos , Evangelia Kalyvianaki , Peter Pietzuch

Recent years have witnessed the surge of asynchronous parallel (async-parallel) iterative algorithms due to problems involving very large-scale data and a large number of decision variables. Because of asynchrony, the iterates are computed…

Optimization and Control · Mathematics 2021-02-05 Zhimin Peng , Yangyang Xu , Ming Yan , Wotao Yin

Most existing deep multi-task learning models are based on parameter sharing, such as hard sharing, hierarchical sharing, and soft sharing. How choosing a suitable sharing mechanism depends on the relations among the tasks, which is not…

Computation and Language · Computer Science 2019-11-19 Tianxiang Sun , Yunfan Shao , Xiaonan Li , Pengfei Liu , Hang Yan , Xipeng Qiu , Xuanjing Huang

Consider the situation where a data analyst wishes to carry out an analysis on a given dataset. It is widely recognized that most of the analyst's time will be taken up with \emph{data engineering} tasks such as acquiring, understanding,…

Failure detection protocols---a fundamental building block for crafting fault-tolerant distributed systems---are in many cases described by their authors making use of informal pseudo-codes of their conception. Often these pseudo-codes use…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-04-15 Vincenzo De Florio , Chris Blondia

The computability power of a distributed computing model is determined by the communication media available to the processes, the timing assumptions about processes and communication, and the nature of failures that processes can suffer. In…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-27 Eric Goubault , Sergio Rajsbaum

Fault tolerance overhead of high performance computing (HPC) applications is becoming critical to the efficient utilization of HPC systems at large scale. HPC applications typically tolerate fail-stop failures by checkpointing. Another…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-06-22 Erlin Yao , Mingyu Chen , Rui Wang , Wenli Zhang , Guangming Tan

Serverless applications can be particularly difficult to troubleshoot, as these applications are often composed of various managed and partly managed services. Faults are often unpredictable and can occur at multiple points, even in simple…

Software Engineering · Computer Science 2024-07-16 Maria C. Borges , Sebastian Werner , Ahmet Kilic

Open-source matters, not just to the current cohort of HPC users but also to potential new HPC communities, such as machine learning, themselves often rooted in open-source. Many of these potential new workloads are, by their very nature,…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-27 Nick Brown , Oliver Thomson Brown , J. Mark Bull

In response to the increasing volume and sensitivity of data, traditional centralized computing models face challenges, such as data security breaches and regulatory hurdles. Federated Computing (FC) addresses these concerns by enabling…

Machine Learning · Computer Science 2024-04-04 René Schwermer , Ruben Mayer , Hans-Arno Jacobsen

Generative models excel at synthesizing high-fidelity samples from complex data distributions, but they often violate hard constraints arising from physical laws or task specifications. A common remedy is to project intermediate samples…

Machine Learning · Computer Science 2025-09-30 Jinhao Liang , Yixuan Sun , Anirban Samaddar , Sandeep Madireddy , Ferdinando Fioretto

The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) and polynomial degree ($p$) to be used on each cell - has long been known to have better theoretical convergence properties than either $h$-…

Numerical Analysis · Mathematics 2023-09-14 Marc Fehling , Wolfgang Bangerth

The paper proposes an alternative proof that Omega, an oracle that outputs a process identifier and guarantees that eventually the same correct process identifier is output at all correct processes, provides minimal information about…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-09-19 Eli Gafni , Petr Kuznetsov

Model degrees of freedom ($\df$) is a fundamental concept in statistics because it quantifies the flexibility of a fitting procedure and is indispensable in model selection. To investigate the gap between $\df$ and the number of independent…

Methodology · Statistics 2024-07-23 Lijun Wang , Hongyu Zhao , Xiaodan Fan

Safra's distributed termination detection algorithm employs a logical token ring structure within a distributed network; only passive nodes forward the token, and a counter in the token keeps track of the number of sent minus the number of…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-03 Wan Fokkink , Georgios Karlos , Andy Tatman

We propose a novel distribution-free scheme to solve optimization problems where the goal is to minimize the expected value of a cost function subject to probabilistic constraints. Unlike standard sampling-based methods, our idea consists…

Optimization and Control · Mathematics 2025-05-28 Francesco Cordiano , Matin Jafarian , Bart De Schutter

Hallucinations are a key concern when creating applications that rely on Foundation models (FMs). Understanding where and how these subtle failures occur in an application relies on evaluation methods known as \textit{evals}. Prior work…

Artificial Intelligence · Computer Science 2025-12-08 Dilani Widanapathiranage , Scott Barnett , Stefanus Kurniawan , Wannita Takerngsaksiri
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