19 papers · ranked by Valyu relevance
K. K. Krishnan Namboodiri, Elizabath Peter, Derya Malak, Petros Elia
—This work establishes the fundamental limits of the classical problem of multi-user distributed computing of linearly separable functions. In particular, we consider a distributed computing setting involving L users, each requesting a linearly separable function over K basis subfunctions from a master node, who is…
Javad Maheri, K. K. Krishnan Namboodiri, Petros Elia
We consider a distributed computing system in which a master node coordinates $N$ workers to evaluate a function over $n$ input files, where this function accepts general decomposition. In particular, we focus on the general case where the requested function admits a $d$-uniform decomposition, meaning that it can be…
Mohamad Hayek, Martin Golasowski, Stephan Hachinger, Rubén J. García-Hernández + 8 more
Modern data-management frameworks promise a flexible and efficient management of data and metadata across storage backends. However, such claims need to be put to a meaningful test in daily practice. We conjecture that such frameworks should be fit to construct a data backend for workflows which use geographically…
Peter G. Hawkins, Eli M. Swanson, Megan Feichtel
The size of individual single cell samples continues to grow with advancing technologies, as do the number of samples included in individual experiments and across organizations. This presents challenges for processing this data at scale, both in terms of computational throughput and the required size of the machines…
Jose L Figueroa, Richard Allen White
We now exist in the era of massive datasets from genomics, large language models, and all the known knowledge of humanity right at our fingertips. Much of this data is becoming more accessible; however, processing such data remains an ongoing issue across systems including high performance computing (HPC)…
Xiao Fu, Yuanyuan Xu, Claudionor Ribeiro da Silva
The recent surge in digital agriculture has generated an emerging demand for scalable, resource-efficient solutions capable of handling both close-range images of agricultural products and high-scale remote-sensing images. Deep learning models have high accuracy, but they are expensive and lack the dynamism to be…
Mikhail Nesterenko, Joseph Oglio
We present QUANTAS 2: a new distributed algorithm simulator and quantitative performance analysis tool. We use the original QUANTAS as a foundation. QUANTAS 2 can perform fast abstract exploration, concrete validation, and adversarial fault injection while preserving a compact implementation model for distributed…
Tomas Oppelstrup, Nicholas Giamblanco, Delyan Z. Kalchev, Ilya Sharapov + 4 more
Simulation of physical systems is essential in many scientific and engineering domains. Commonly used domain decomposition methods are unable to deliver high simulation rate or high utilization in network computing environments. In particular, Exascale systems deliver only a small fraction their peak performance for…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Ray-I Chang, Ting-Wei Hsu, Yen-Ting Chen, Bartłomiej Płaczek + 1 more
Time-Sensitive Networking (TSN), particularly the Time-Aware Shaper (TAS) specified by IEEE 802.1Qbv, is critical for real-time communication in Industrial Sensor Networks (ISNs). However, many TAS scheduling approaches rely on centralized computation and can face scalability bottlenecks in large networks. In addition…
Marius de Arruda Botelho, Cem Ata Baykara, Ali Burak Ünal, Nico Pfeifer + 2 more
Ensuring privacy in distributed machine learning while computing the Area Under the Curve (AUC) is a significant challenge because pooling sensitive test data is often not allowed. Although cryptographic methods can address some of these concerns, they may compromise either scalability or accuracy. In this paper, we…
Da Wei, Evangelia Kalyvianaki
This paper introduces Dodoor, an efficient randomized decentralized scheduler designed for task scheduling in modern data centers. Dodoor leverages advanced research on the weighted balls-into-bins model with -batched setting. Unlike other decentralized schedulers that rely on real-time probing of remote servers…
Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides
This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore…
Salman Khan, Ibrar Ali Shah, Woong-Kee Loh, Javed Ali Khan + 3 more
Fog computing has revolutionized the world by providing its services close to the user premises, which results in reducing the communication latency for many real-time applications. This communication latency has been a major constraint in cloud computing and ultimately causes user dissatisfaction due to slow response…
Authors not listed
Next Generation Risk Assessment (NGRA) promotes animal-free, exposure-informed, and hypothesis-driven approaches to chemical safety assessment. In silico tools, such as quantitative structure-activity relationship (QSAR) models, are valuable new approach methodologies (NAMs) for use in NGRA. However, the practical…
Manuel Rueda, Dietmar Fernandez-Orth, Ivo G. Gut
Variant calling for next-generation sequencing (NGS) data relies on a diverse ecosystem of tools and workflows. Large-scale collaborative studies increasingly adopt federated analysis, where each institution processes sensitive data locally using standardized pipelines. Deploying identical pipelines across multiple…
Dhruv D. Jatkar, M. Ali Al-Radhawi, Christopher A. Voigt, Eduardo D. Sontag
Implementing logic functions in living cells is a fundamental area of interest among synthetic biologists. The goal of designing biochemical circuits in synthetic biology is to make modular and tractable systems that perform well with predictable behaviors. Developing formalisms towards the design of such systems has…
Kayson Fakhar, Danyal Akarca, Andrea I. Luppi, Stuart Oldham + 5 more
Brains are often described as cost-efficient communication networks, optimally balancing the cost of long connections with the benefits of fast communication. Here, inspired by the “use it or lose it” principle, we present a novel game-theoretic model of self-organizing neural units and show that the brain is, in fact…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…