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Progress in LLMs is increasingly measured through standardized benchmarks, where state-of-the-art improvements are often separated by fractions of a percentage point. At the same time, the computational cost of evaluating modern LLMs has…

Machine Learning · Computer Science 2026-05-21 David Pape , Jonathan Evertz , Lea Schönherr

All computing infrastructure suffers from performance variability, be it bare-metal or virtualized. This phenomenon originates from many sources: some transient, such as noisy neighbors, and others more permanent but sudden, such as changes…

Performance · Computer Science 2020-03-11 Dmitry Duplyakin , Alexandru Uta , Aleksander Maricq , Robert Ricci

Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware resources, such as virtual machines. However, virtualization…

Software Engineering · Computer Science 2023-08-16 Jinyang Liu , Zhihan Jiang , Jiazhen Gu , Junjie Huang , Zhuangbin Chen , Cong Feng , Zengyin Yang , Yongqiang Yang , Michael R. Lyu

Hybrid memory systems comprised of dynamic random access memory (DRAM) and non-volatile memory (NVM) have been proposed to exploit both the capacity advantage of NVM and the latency and dynamic energy advantages of DRAM. An important…

Hardware Architecture · Computer Science 2019-12-18 Yang Li , Jongmoo Choi , Jin Sun , Saugata Ghose , Hui Wang , Justin Meza , Jinglei Ren , Onur Mutlu

For many machine learning algorithms, predictive performance is critically affected by the hyperparameter values used to train them. However, tuning these hyperparameters can come at a high computational cost, especially on larger datasets,…

This paper presents results of the performance benchmarks of the Open Source hypervisor Xen. The study focuses on the network related performance as well as on the application related performance of multiple virtual machines that were…

Performance · Computer Science 2010-09-30 Adrian Heissler

In recent years, the rapid advancement of deep neural networks (DNNs) has revolutionized artificial intelligence, enabling models with unprecedented capabilities in understanding, generating, and processing complex data. These powerful…

Machine Learning · Computer Science 2025-06-27 Zixian Wang , Cole Ramos , Muhammad A. Awad , Keith Lowery

Multi-tenant machine learning services have become emerging data-intensive workloads in data centers with heavy usage of GPU resources. Due to the large scale, many tuning parameters and heavy resource usage, it is usually impractical to…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-11 Ruofan Liang , Bingsheng He , Shengen Yan , Peng Sun

Cloud computing aims to power the next generation data centers and enables application service providers to lease data center capabilities for deploying applications depending on user QoS (Quality of Service) requirements. Cloud…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-07-29 Rajkumar Buyya , Rajiv Ranjan , Rodrigo N. Calheiros

This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-03 Mani Tofigh , Edward Guo , Weiwei Jia , Xiaoning Ding , Zirui Neil Zhao , Jianchen Shan

Container technologies have been evolving rapidly in the cloud-native era. Kubernetes, as a production-grade container orchestration platform, has been proven to be successful at managing containerized applications in on-premises…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-25 Chao Zheng , Qinghui Zhuang , Fei Guo

Modern computer designs support composite prefetching, where multiple individual prefetcher components are used to target different memory access patterns. However, multiple prefetchers competing for resources can drastically hurt…

Hardware Architecture · Computer Science 2023-07-18 Erika S. Alcorta , Mahesh Madhav , Scott Tetrick , Neeraja J. Yadwadkar , Andreas Gerstlauer

This study proposes a unified forecasting framework for high-dimensional multi-task time series to meet the prediction demands of cloud native backend systems operating under highly dynamic loads, coupled metrics, and parallel tasks. The…

Machine Learning · Computer Science 2025-12-25 Zixiao Huang , Jixiao Yang , Sijia Li , Chi Zhang , Jinyu Chen , Chengda Xu

Task-based programming models are emerging as a promising alternative to make the most of multi-/many-core systems. These programming models rely on runtime systems, and their goal is to improve application performance by properly…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-24 Antoni Navarro , Arthur F. Lorenzon , Eduard Ayguadé , Vicenç Beltran

The rise of microservice architectures has revolutionized application design, fostering adaptability and resilience. These architectures facilitate scaling and encourage collaborative efforts among specialized teams, streamlining deployment…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-21 Herve Mbikayi Kabamba , Matthew Khouzam , Michel Dagenais

Multicore CPU architectures have been established as a structure for general-purpose systems for high-performance processing of applications. Recent multicore CPU has evolved as a system architecture based on non-uniform memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-26 Geunsik Lim , Sang-Bum Suh

Increased complexity of network-based software solutions and the ever-rising number of concurrent users forced a shift of the IT industry to cloud computing. Conventional network software systems commonly based on monolithic application…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-31 M. Sipek , D. Muharemagic , B. Mihaljevic , A. Radovan

Adding new hardware features to a cloud computing server requires testing both the functionalities and the performance of the new hardware mechanisms. However, commonly used cloud computing server workloads are not well-represented by the…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-07 Hao Wu , Fangfei Liu , Ruby B. Lee

Microservice architectures have become the dominant paradigm for cloud-native systems, offering flexibility and scalability. However, this shift has also led to increased demand for cloud resources, contributing to higher energy consumption…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-13 Julian Legler , Sebastian Werner , Maria C. Borges , Stefan Tai

In this paper, a re-evaluation undertaken for dynamic VM consolidation problem and optimal online deterministic algorithms for the single VM migration in an experimental environment. We proceeded to focus on energy and performance trade-off…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-12-18 Nasrin Akhter , Mohamed Othman , Ranesh Kumar Naha