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The emergence of cloud computing based on virtualization technologies brings huge opportunities to host virtual resource at low cost without the need of owning any infrastructure. Virtualization technologies enable users to acquire,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-08 Minxian Xu , Wenhong Tian , Rajkumar Buyya

Modern shared memory multiprocessors permit reordering of memory operations for performance reasons. These reorderings are often a source of subtle bugs in programs written for such architectures. Traditional approaches to verify weak…

Software Engineering · Computer Science 2016-02-29 Ganesh Narayanaswamy , Saurabh Joshi , Daniel Kroening

Memory-augmented neural networks consisting of a neural controller and an external memory have shown potentials in long-term sequential learning. Current RAM-like memory models maintain memory accessing every timesteps, thus they do not…

Machine Learning · Computer Science 2019-03-21 Hung Le , Truyen Tran , Svetha Venkatesh

Driven by great demands on low-latency services of the edge devices (EDs), mobile edge computing (MEC) has been proposed to enable the computing capacities at the edge of the radio access network. However, conventional MEC servers suffer…

Signal Processing · Electrical Eng. & Systems 2019-01-29 Pengfei Wang , Zijie Zheng , Boya Di , Lingyang Song

CPU-GPU heterogeneous systems are now commonly used in HPC (High-Performance Computing). However, improving the utilization and energy-efficiency of such systems is still one of the most critical issues. As one single program typically…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-08 Eishi Arima , Minjoon Kang , Issa Saba , Josef Weidendorfer , Carsten Trinitis , Martin Schulz

Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-20 Md Hasanul Ferdaus , Manzur Murshed , Rodrigo N. Calheiros , Rajkumar Buyya

To understand applications' memory usage details, engineers use instrumented builds and profiling tools. Both approaches are impractical for use in production environments or deployed mobile applications. As a result, developers can gather…

Software Engineering · Computer Science 2023-08-21 Gunnar Kudrjavets , Ayushi Rastogi , Jeff Thomas , Nachiappan Nagappan

The widespread adoption of Large Language Models (LLMs) has exponentially increased the demand for efficient serving systems. With growing requests and context lengths, key-value (KV)-related operations, including attention computation and…

Hardware Architecture · Computer Science 2026-02-13 Lian Liu , Shixin Zhao , Yutian Zhou , Yintao He , Mengdi Wang , Yinhe Han , Ying Wang

Commodity multicore systems are increasingly adopting hardware support that enables the system software to partition the last-level cache (LLC). This support makes it possible for the operating system (OS) or the Virtual Machine Monitor…

Hardware Architecture · Computer Science 2024-02-13 Juan Carlos Saez , Fernando Castro , Graziano Fanizzi , Manuel Prieto-Matias

Non-volatile memory (NVM) provides a scalable and power-efficient solution to replace DRAM as main memory. However, because of relatively high latency and low bandwidth of NVM, NVM is often paired with DRAM to build a heterogeneous memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-03 Kai Wu , Yingchao Huang , Dong Li

Modern hardware environments are becoming increasingly heterogeneous, leading to the emergence of applications specifically designed to exploit this heterogeneity. Efficiently adopting locks in these applications poses distinct challenges.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-12 Hanze Zhang , Rong Chen , Haibo Chen

In-memory computing is a promising alternative to traditional computer designs, as it helps overcome performance limits caused by the separation of memory and processing units. However, many current approaches struggle with unreliable…

Memory-centric computing aims to enable computation capability in and near all places where data is generated and stored. As such, it can greatly reduce the large negative performance and energy impact of data access and data movement, by…

Hardware Architecture · Computer Science 2023-09-15 Onur Mutlu

We study the problem of scheduling a general computational DAG on multiple processors in a 2-level memory hierarchy. This setting is a natural generalization of several prominent models in the literature, and it simultaneously captures…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-24 Pál András Papp , Toni Böhnlein , A. N. Yzelman

The significant resource demands in LLM serving prompts production clusters to fully utilize heterogeneous hardware by partitioning LLM models across a mix of high-end and low-end GPUs. However, existing parallelization approaches often…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-11 Zizhao Mo , Jianxiong Liao , Huanle Xu , Zhi Zhou , Chengzhong Xu

Compute and memory are tightly coupled within each server in traditional datacenters. Large-scale datacenter operators have identified this coupling as a root cause behind fleet-wide resource underutilization and increasing Total Cost of…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-09 Hasan Al Maruf , Mosharaf Chowdhury

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

This thesis (extended abstract) presents the software development efforts toward efficient exploitation of heterogeneity through intricate mapping of computational kernels, collaborative execution of multiple processing elements and…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-26 Siqi Wang

Cloud Computing has emerged as a successful computing paradigm for efficiently utilizing managed compute infrastructure such as high speed rack-mounted servers, connected with high speed networking, and reliable storage. Usually such…

Operating Systems · Computer Science 2016-11-17 Piyus Kedia , Sorav Bansal , Deepak Deshpande , Sreekanth Iyer

Edge computing enables latency-critical applications to process data close to end devices, yet task heterogeneity and limited resources pose significant challenges to efficient orchestration. This paper presents a measurement-driven,…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-01 Yongmin Zhang , Pengyu Huang , Mingyi Dong , Jing Yao