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Related papers: ASA -- The Adaptive Scheduling Algorithm

200 papers

Modern operating system schedulers employ a single, static policy, which struggles to deliver optimal performance across the diverse and dynamic workloads of contemporary systems. This "one-policy-fits-all" approach leads to significant…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-18 Xinbo Wang , Shian Jia , Ziyang Huang , Jing Cao , Mingli Song

Domain-specific systems-on-chip (DSSoCs) aim at bridging the gap between application-specific integrated circuits (ASICs) and general-purpose processors. Traditional operating system (OS) schedulers can undermine the potential of DSSoCs…

Hardware Architecture · Computer Science 2021-09-24 A. Alper Goksoy , Anish Krishnakumar , Md Sahil Hassan , Allen J. Farcas , Ali Akoglu , Radu Marculescu , Umit Y. Ogras

Although High Performance Computing (HPC) users understand basic resource requirements such as the number of CPUs and memory limits, internal infrastructural utilization data is exclusively leveraged by cluster operators, who use it to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-19 Abel Souza , Kristiaan Pelckmans , Johan Tordsson

Asynchronous methods are fundamental for parallelizing computations in distributed machine learning. They aim to accelerate training by fully utilizing all available resources. However, their greedy approach can lead to inefficiencies using…

Machine Learning · Computer Science 2025-05-23 Artavazd Maranjyan , El Mehdi Saad , Peter Richtárik , Francesco Orabona

In a cloud-native era, the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes. However, when encountering continuous workflow requests and unexpected resource request…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-04 Chenggang Shan , Chuge Wu , Yuanqing Xia , Zehua Guo , Danyang Liu , Jinhui Zhang

Increasing data volumes in scientific experiments necessitate the use of high-performance computing (HPC) resources for data analysis. In many scientific fields, the data generated from scientific instruments and supercomputer simulations…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-25 Sam Nickolay , Eun-Sung Jung , Rajkumar Kettimuthu , Ian Foster

In an overloaded FaaS cluster, individual worker nodes strain under lengthening queues of requests. Although the cluster might be eventually horizontally-scaled, adding a new node takes dozens of seconds. As serving applications are tuned…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-01 Paweł Żuk , Bartłomiej Przybylski , Krzysztof Rzadca

A queue is required when a service provider is not able to handle jobs arriving over the time. In a highly flexible and dynamic environment, some jobs might demand for faster execution at run-time especially when the resources are limited…

Performance · Computer Science 2015-03-24 Yash Gupta , Kamalakar Karlapalem

This study presents a novel computer system performance optimization and adaptive workload management scheduling algorithm based on Q-learning. In modern computing environments, characterized by increasing data volumes, task complexity, and…

Machine Learning · Computer Science 2024-11-11 Pochun Li , Yuyang Xiao , Jinghua Yan , Xuan Li , Xiaoye Wang

HPC users aim to improve their execution times without particular regard for increasing system utilization. On the contrary, HPC operators favor increasing the number of executed applications per time unit and increasing system utilization.…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-11 Ahmed Eleliemy , Florina M. Ciorba

The dynamic adaptation of resource levels enables the system to enhance energy efficiency while maintaining the necessary computational resources, particularly in scenarios where workloads fluctuate significantly over time. The proposed…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-14 Said Muhammad , Lahlou Laaziz , Nadjia Kara , Phat Tan Nguyen , Timothy Murphy

Migrating heterogeneous high-performance computing (HPC) systems to resource-aware scheduling introduces both technical and behavioral challenges, particularly in production environments with established user workflows. This paper presents…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-31 Glen MacLachlan , Joseph Creech , Rubeel Muhammad Iqbal , Clark Gaylord , Jake Messick

On High-Performance Computing (HPC) systems, several hyperparameter configurations can be evaluated in parallel to speed up the Hyperparameter Optimization (HPO) process. State-of-the-art HPO methods follow a bandit-based approach and build…

Machine Learning · Computer Science 2025-11-03 Marcel Aach , Rakesh Sarma , Helmut Neukirchen , Morris Riedel , Andreas Lintermann

In many service systems, especially those in healthcare, customer waiting times can result in increased service requirements. Such service slowdowns can significantly impact system performance. Therefore, it is important to properly account…

Optimization and Control · Mathematics 2025-01-22 Jing Dong , Berk Görgülü , Vahid Sarhangian

The growing disparity between CPU core counts and available memory bandwidth has intensified memory contention in servers. This particularly affects highly parallelizable applications, which must achieve efficient cache utilization to…

Hardware Architecture · Computer Science 2025-03-17 Alessandro Fogli , Bo Zhao , Peter Pietzuch , Jana Giceva

Advance reservation is important to guarantee the quality of services of jobs by allowing exclusive access to resources over a defined time interval on resources. It is a challenge for the scheduler to organize available resources…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-03-06 Bo Li , Yijian Pei , Bin Shen , Hao Wu , Min He , Jundong Yang

Accelerator-based heterogeneous architectures, such as CPU-GPU, CPU-TPU, and CPU-FPGA systems, are widely adopted to support the popular artificial intelligence (AI) algorithms that demand intensive computation. When deployed in real-time…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-20 An Zou , Yuankai Xu , Yinchen Ni , Jintao Chen , Yehan Ma , Jing Li , Christopher Gill , Xuan Zhang , Yier Jin

Real time system technology traditionally developed for safety critical systems, has now been extended to support multimedia systems and virtual reality. A large number of real-time application, related to multimedia and adaptive control…

Operating Systems · Computer Science 2012-12-17 Shri Prakash Dwivedi

An acceptable response time of a server is an important aspect in many client-server applications; this is evident in situations in which the server is overloaded by many computationally intensive requests. In this work, we consider that…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-09 István Módos , Přemysl Šůcha , Roman Václavík , Jan Smejkal , Zdeněk Hanzálek

High intensive computation applications can usually take days to months to finish an execution. During this time, it is common to have variations of the available resources when considering that such hardware is usually shared among a…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-27 Kiran Mantripragada , Alecio Binotto , Leonardo P. Tizzei
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