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The main goal of parallel processing is to provide users with performance that is much better than that of single processor systems. The execution of jobs is scheduled, which requires certain resources in order to meet certain criteria.…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-02-07 Yang Cao , Fei Wu , Thomas Robertazzi

Trusted-execution environments (TEE), like Intel SGX, isolate user-space applications into secure enclaves without trusting the OS. Thus, TEEs reduce the trusted computing base, but add one to two orders of magnitude slow-down. The…

Cryptography and Security · Computer Science 2020-10-19 Zhijingcheng Yu , Shweta Shinde , Trevor E. Carlson , Prateek Saxena

In the landscape of generative artificial intelligence, diffusion-based models present challenges for socio-technical systems in data requirements and privacy. Traditional approaches like federated learning distribute the learning process…

Machine Learning · Computer Science 2024-08-19 Domenique Zipperling , Simeon Allmendinger , Lukas Struppek , Niklas Kühl

In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding the performance of a kernel based on its operational…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-18 Fabio Checconi , Jesmin Jahan Tithi , Fabrizio Petrini

Multicore parallel programming has some very difficult problems such as deadlocks during synchronizations and race conditions brought by concurrency. Added to the difficulty is the lack of a simple, well-accepted computing model for…

Programming Languages · Computer Science 2010-12-09 Yibing Wang

This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exposed to an attacker. It comes with several contributions:…

Cryptography and Security · Computer Science 2020-02-18 Katarzyna Kapusta , Gerard Memmi , Matthieu Rambaud

Recent trend towards increasing large machine learning models require both training and inference tasks to be distributed. Considering the huge cost of training these models, it is imperative to unlock optimizations in computation and…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-29 Abhinav Jangda , Jun Huang , Guodong Liu , Amir Hossein Nodehi Sabet , Saeed Maleki , Youshan Miao , Madanlal Musuvathi , Todd Mytkowicz , Olli Sarikivi

Chip multiprocessors (CMPs) are ubiquitous in most of today's computing fields. Although they provide noticeable benefits in terms of performance, cost and power efficiency, they also introduce some new issues. In this paper we analyze how…

Hardware Architecture · Computer Science 2012-06-28 Javier Merino , Valentin Puente , José Ángel Gregorio

Object storage solutions potentially address long-standing performance issues with POSIX file systems for certain I/O workloads, and new storage technologies offer promising performance characteristics for data-intensive use cases. In this…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-28 Nicolau Manubens , Tiago Quintino , Simon D. Smart , Emanuele Danovaro , Adrian Jackson

Distributed Asynchronous Object Store (DAOS) is a novel software-defined object store leveraging Non-Volatile Memory (NVM) devices, designed for high performance. It provides a number of interfaces for applications to undertake I/O, ranging…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-09-30 Nicolau Manubens , Johann Lombardi , Simon D. Smart , Emanuele Danovaro , Tiago Quintino , Dean Hildebrand , Adrian Jackson

In network slicing, the network operator needs to satisfy the service level agreements of multiple slices at the same time and on the same physical infrastructure. To do so with reduced provisioned resources, the operator may consider…

Networking and Internet Architecture · Computer Science 2024-04-30 Panagiotis Nikolaidis , John Baras

Serverless platforms essentially face a tradeoff between container startup time and provisioned concurrency (i.e., cached instances), which is further exaggerated by the frequent need for remote container initialization. This paper presents…

Operating Systems · Computer Science 2022-09-20 Xingda Wei , Fangming Lu , Tianxia Wang , Jinyu Gu , Yuhan Yang , Rong Chen , Haibo Chen

Performance modeling can help to improve the resource efficiency of clusters and distributed dataflow applications, yet the available modeling data is often limited. Collaborative approaches to performance modeling, characterized by the…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-24 Dominik Scheinert , Soeren Becker , Jonathan Will , Luis Englaender , Lauritz Thamsen

Large language models (LLMs) have achieved near-human performance across diverse reasoning tasks, yet their deployment on resource-constrained Internet-of-Things (IoT) devices remains impractical due to massive parameter footprints and…

Machine Learning · Computer Science 2025-11-07 Mingyu Sung , Vikas Palakonda , Suhwan Im , Sunghwan Moon , Il-Min Kim , Sangseok Yun , Jae-Mo Kang

Current 3D instance segmentation models generally use multi-stage methods to extract instance objects, including clustering, feature extraction, and post-processing processes. However, these multi-stage approaches rely on hyperparameter…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Chuan Tang , Xi Yang

As an emerging cloud computing deployment paradigm, serverless computing is gaining traction due to its efficiency and ability to harness on-demand cloud resources. However, a significant hurdle remains in the form of the cold start…

Software Engineering · Computer Science 2024-08-22 Cheryl Lee , Zhouruixing Zhu , Tianyi Yang , Yintong Huo , Yuxin Su , Pinjia He , Michael R. Lyu

Task-based programming models have proven to be a robust and versatile way to approach development of applications for distributed environments. They provide natural programming patterns with high performance. However, execution on this…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-08 Alex Barcelo , Anna Queralt , Toni Cortes

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

This work describes the design, implementation and performance analysis of a distributed two-tiered storage software. The first tier functions as a distributed software cache implemented using solid-state devices~(NVMes) and the second tier…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-13 Aparna Sasidharan , Xian-He , Jay Lofstead , Scott Klasky

Commodity applications contain more and more combinations of interacting components (user, application, library, and system) and exhibit increasingly diverse tradeoffs between isolation, performance, and programmability. We argue that the…

Cryptography and Security · Computer Science 2021-08-11 Bumjin Im , Fangfei Yang , Chia-Che Tsai , Michael LeMay , Anjo Vahldiek-Oberwagner , Nathan Dautenhahn
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