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Related papers: CI at Scale: Lean, Green, and Fast

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This work unifies insights from the systems and functional programming communities, in order to enable compositional reasoning about software which is nonetheless efficiently realizable in hardware. It exploits a correspondence between…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-18 Thomas Dickerson

Lowering costs by driving high utilization across deep learning workloads is a crucial lever for cloud providers. We present Singularity, Microsoft's globally distributed scheduling service for highly-efficient and reliable execution of…

The race for artificial intelligence (AI) dominance often prioritizes scale over efficiency. Hyper-scaling is the common industry approach: larger models, more data, and as many computational resources as possible. Using more resources is a…

General Economics · Economics 2026-05-08 Marco Bornstein , Amrit Singh Bedi

We present a simple and easy to apply methodology for using high-level self-submitting parallel job queues in an MPI environment. Using C++, we implemented a library of functions, MPQueue, both for testing our concepts and for use in real…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-04-23 John M. Neuberger , Nandor Sieben , James W. Swift

Cloud-based computing systems can get oversubscribed due to the budget constraints of their users or limitations in certain resource types. The oversubscription can, in turn, degrade the users perceived Quality of Service (QoS). The…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-04-12 Chavit Denninnart , Mohsen Amini Salehi

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

Streaming algorithms are fundamental in the analysis of large and online datasets. A key component of many such analytic tasks is $q$-MAX, which finds the largest $q$ values in a number stream. Modern approaches attain a constant runtime by…

Data Structures and Algorithms · Computer Science 2024-07-11 Ran Ben-Basat , Gil Einziger , Wenchen Han , Bilal Tayh

Sequential algorithms for the Stable Matching Problem are often too slow in the context of some large scale applications like switch scheduling. Parallel architectures can offer a notable decrease in runtime complexity. We propose a stable…

Data Structures and Algorithms · Computer Science 2024-08-27 Scott Wynn , Alec Kyritsis , Stephora Alberi , Enyue Lu

Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon…

Multipath QUIC is a transport protocol that allows for the use of multiple network interfaces for a single connection. It thereby offers, on the one hand, the possibility to gather a higher throughput, while, on the other hand, multiple…

Networking and Internet Architecture · Computer Science 2023-05-08 Mahsa Noroozi , Flavio Gallistl , Majid Noroozi

It's long been accepted that continuous integration (CI) in software engineering increases the code quality of enterprise projects when adhered to by it's practitioners. But is any of that effort to increase code quality and velocity…

Software Engineering · Computer Science 2024-02-13 Parth Sane

Although a wide variety of handcrafted concurrent data structures have been proposed, there is considerable interest in universal approaches (henceforth called Universal Constructions or UCs) for building concurrent data structures. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-05 Ilya Kokorin , Alexander Fedorov , Trevor Brown , Vitaly Aksenov

Contemporary compute platforms increasingly offload compute kernels from CPU to integrated hardware accelerators to reach maximum performance per Watt. Unfortunately, the time the CPU spends on setup control and synchronization has…

Serverless computing has emerged as a compelling new paradigm of cloud computing models in recent years. It promises the user services at large scale and low cost while eliminating the need for infrastructure management. On cloud provider…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-01 Lucia Schuler , Somaya Jamil , Niklas Kühl

Round Robin, considered as the most widely adopted CPU scheduling algorithm, undergoes severe problems directly related to quantum size. If time quantum chosen is too large, the response time of the processes is considered too high. On the…

Operating Systems · Computer Science 2011-11-24 Abbas Noon , Ali Kalakech , Seifedine Kadry

Big data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary constraints of analytical users. The RO problem is challenging…

Databases · Computer Science 2024-09-24 Chenghao Lyu , Qi Fan , Fei Song , Arnab Sinha , Yanlei Diao , Wei Chen , Li Ma , Yihui Feng , Yaliang Li , Kai Zeng , Jingren Zhou

Cloud computing is a new archetype that provides dynamic computing services to cloud users through the support of datacenters that employs the services of datacenter brokers which discover resources and assign them Virtually. The focus of…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-29 J. Kok Konjaang , J. Y. Maipan-uku , Kumangkem Kennedy Kubuga

With the rising number of distributed computer systems, from microservice web applications to IoT platforms, the question of reliable communication between different parts of the aforementioned systems is becoming increasingly important. As…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-28 Veljko Maksimovic , Milos Simic , Milan Stojkov , Miroslav Zaric

Modern online platforms are increasingly employing recommendation systems to address information overload and improve user engagement. There is an evolving paradigm in this research field that recommendation network learning occurs both on…

Information Retrieval · Computer Science 2024-12-03 Zheqi Lv , Wenqiao Zhang , Zhengyu Chen , Shengyu Zhang , Kun Kuang

A fundamental challenge in large-scale cloud networks and data centers is to achieve highly efficient server utilization and limit energy consumption, while providing excellent user-perceived performance in the presence of uncertain and…

Probability · Mathematics 2017-06-23 Debankur Mukherjee , Souvik Dhara , Sem Borst , Johan S. H. van Leeuwaarden
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