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With the increase in compute nodes in large compute platforms, a proportional increase in node failures will follow. Many application-based checkpoint/restart (C/R) techniques have been proposed for MPI applications to target the reduced…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-30 Kiril Dichev , Herbert Jordan , Konstantinos Tovletoglou , Thomas Heller , Dimitrios S. Nikolopoulos , Georgios Karakonstantis , Charles Gillan

Mixed-Criticality (MC) systems consolidate multiple functionalities with different criticalities onto a single hardware platform. Such systems improve the overall resource utilization while guaranteeing resources to critical tasks. In this…

Operating Systems · Computer Science 2020-03-13 Saravanan Ramanathan , Arvind Easwaran

Many high end and next generation computing systems to incorporated alternative memory technologies to meet performance goals. Since these technologies present distinct advantages and tradeoffs compared to conventional DDR* SDRAM, such as…

Performance · Computer Science 2021-10-06 M. Ben Olson , Brandon Kammerdiener , Kshitij A. Doshi , Terry Jones , Michael R. Jantz

Emerging computing architectures such as near-memory computing (NMC) promise improved performance for applications by reducing the data movement between CPU and memory. However, detecting such applications is not a trivial task. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-19 Stefano Corda , Gagandeep Singh , Ahsan Javed Awan , Roel Jordans , Henk Corporaal

Distributed locking mechanisms are fundamental to ensuring data consistency and integrity in distributed systems. This paper presents a comprehensive analysis of distributed locking algorithms, focusing on their performance characteristics…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-07 Andre Rodriguez , William Osborn

Resistive random-access memory (RRAM) is gaining popularity due to its ability to offer computing within the memory and its non-volatile nature. The unique properties of RRAM, such as binary switching, multi-state switching, and device…

Emerging Technologies · Computer Science 2024-07-08 Simranjeet Singh , Farhad Merchant , Sachin Patkar

Rollout-training disaggregation is emerging as the standard architecture for Reinforcement Learning (RL) post-training, where memory-bound rollout and compute-bound training are physically disaggregated onto purpose-built clusters to…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-16 Tianyuan Wu , Lunxi Cao , Yining Wei , Wei Gao , Yuheng Zhao , Dakai An , Shaopan Xiong , Zhiqiang Lv , Ju Huang , Siran Yang , Yinghao Yu , Jiamang Wang , Lin Qu , Wei Wang

The proliferation of fast, dense, byte-addressable nonvolatile memory suggests that data might be kept in pointer-rich "in-memory" format across program runs and even process and system crashes. For full generality, such data requires…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-17 Wentao Cai , Haosen Wen , H. Alan Beadle , Chris Kjellqvist , Mohammad Hedayati , Michael L. Scott

This paper presents MAMoC, a framework which brings together a diverse range of infrastructure types including mobile devices, cloudlets, and remote cloud resources under one unified API. MAMoC allows mobile applications to leverage the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-16 Dawand Sulaiman , Adam Barker

Disaggregated memory leverages recent technology advances in high-density, byte-addressable non-volatile memory and high-performance interconnects to provide a large memory pool shared across multiple compute nodes. Due to higher memory…

Hardware Architecture · Computer Science 2024-06-10 Haris Volos

Dropout is attracting intensive research interest in deep learning as an efficient approach to prevent overfitting. Recently incorporating structural information when deciding which units to drop out produced promising results comparing to…

Machine Learning · Computer Science 2021-06-17 Xiaoli Li

Applications in machine learning, optimization, and control require the sequential selection of a few system elements, such as sensors, data, or actuators, to optimize the system performance across multiple time steps. However, in…

Machine Learning · Statistics 2020-12-17 Vasileios Tzoumas , Ali Jadbabaie , George J. Pappas

Increasing investment in computing technologies and the advancements in silicon technology has fueled rapid growth in advanced driver assistance systems (ADAS) and corresponding SoC developments. An ADAS SoC represents a heterogeneous…

Hardware Architecture · Computer Science 2022-09-14 Hao Luan , Yu Yao , Chang Huang

Electrical power grids are vulnerable to cascading failures that can lead to large blackouts. Detection and prevention of cascading failures in power grids is impor- tant. Currently, grid operators mainly monitor the state (loading level)…

Physics and Society · Physics 2015-07-20 Martijn Warnier , Stefan Dulman , Yakup Koç , Eric Pauwels

Multi-access Edge Computing (MEC) is a type of network architecture that provides cloud computing capabilities at the edge of the network. We consider the use case of video surveillance for an university campus running on a 5G-MEC…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-28 Ricardo N. Boing , Hugo Vaz Sampaio , Fernando Koch , Rene N. S. Cruz , Carlos B. Westphall

We introduce the Adaptive Massively Parallel Computation (AMPC) model, which is an extension of the Massively Parallel Computation (MPC) model. At a high level, the AMPC model strengthens the MPC model by storing all messages sent within a…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-05-21 Soheil Behnezhad , Laxman Dhulipala , Hossein Esfandiari , Jakub Łącki , Warren Schudy , Vahab Mirrokni

As large language models continue to scale up, distributed training systems have expanded beyond 10k nodes, intensifying the importance of fault tolerance. Checkpoint has emerged as the predominant fault tolerance strategy, with extensive…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-04-10 Weilin Cai , Le Qin , Jiayi Huang

Memory disaggregation provides efficient memory utilization across network-connected systems. It allows a node to use part of memory in remote nodes in the same cluster. Recent studies have improved RDMA-based memory disaggregation systems,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Taekyung Heo , Seunghyo Kang , Sanghyeon Lee , Soojin Hwang , Jaehyuk Huh

Spreading information through a network of devices is a core activity for most distributed systems. As such, self-stabilizing algorithms implementing information spreading are one of the key building blocks enabling aggregate computing to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-23 Yuanqiu Mo , Soura Dasgupta , Jacob Beal

In model-predictive control (MPC), achieving the best closed-loop performance under a given computational resource is the underlying design consideration. This paper analyzes the MPC design problem with control performance and required…

Optimization and Control · Mathematics 2016-04-25 Vincent Bachtiar , Chris Manzie , William H. Moase , Eric C. Kerrigan
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