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Related papers: A Review on Software Architectures for Heterogeneo…

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Not only with the large host memory for supporting large scale graph processing, GPU-accelerated heterogeneous architecture can also provide a great potential for high-performance computing. However, few existing heterogeneous systems can…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-05 Xianliang Li

Neural architectures and hardware accelerators have been two driving forces for the progress in deep learning. Previous works typically attempt to optimize hardware given a fixed model architecture or model architecture given fixed…

In this dissertation, we propose a memory and computing coordinated methodology to thoroughly exploit the characteristics and capabilities of the GPU-based heterogeneous system to effectively optimize applications' performance and privacy.…

Cryptography and Security · Computer Science 2022-09-07 Zhendong Wang , Yang Hu

As an important goal of high-performance computing, the concept of performance portability has been around for many years. As the failure of Moore's Law, it is no longer feasible to improve computer performance by simply increasing the…

Hardware Architecture · Computer Science 2023-08-29 Weifeng Liu , Linping Wu , Xiaowen Xu , Yuren Wang

In recent processor development, we have witnessed the integration of GPU and CPUs into a single chip. The result of this integration is a reduction of the data communication overheads. This enables an efficient collaboration of both…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-07 Francisco Corbera , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Antonio Vilches , María J. Garzarán

Non-uniform performance and power consumption across the processing elements (PEs) of heterogeneous SoCs increase the computation complexity of the task scheduling problem compared to homogeneous architectures. Latency of a software-based…

Hardware Architecture · Computer Science 2022-11-15 Alexander Fusco , Sahil Hassan , Joshua Mack , Ali Akoglu

Recent advancements in Large Language Models (LLMs) have led to increasingly diverse requests, accompanied with varying resource (compute and memory) demands to serve them. However, this in turn degrades the cost-efficiency of LLM serving…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-06 Youhe Jiang , Fangcheng Fu , Xiaozhe Yao , Guoliang He , Xupeng Miao , Ana Klimovic , Bin Cui , Binhang Yuan , Eiko Yoneki

Heterogeneous systems have become one of the most common architectures today, thanks to their excellent performance and energy consumption. However, due to their heterogeneity they are very complex to program and even more to achieve…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-26 Raúl Nozal , Jose Luis Bosque , Ramón Beivide

The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-14 David Abdurachmanov , Peter Elmer , Giulio Eulisse , Robert Knight , Tapio Niemi , Jukka K. Nurminen , Filip Nyback , Goncalo Pestana , Zhonghong Ou , Kashif Khan

Like other engineering disciplines, software engineering should also have principles to guide the construction of sustainable computer applications. Tangible properties include a) unlimited scalability, b) maximal reproducibility, and c)…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-07-23 Justin Shi

Embedded Systems combine one or more processor cores with dedicated logic running on an ASIC or FPGA to meet design goals at reasonable cost. It is achieved by profiling the application with variety of aspects like performance, memory…

Performance · Computer Science 2013-12-12 Rajendra Patel , Arvind Rajwat

Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-11 Fang Liu , Guoming Tang , Youhuizi Li , Zhiping Cai , Xingzhou Zhang , Tongqing Zhou

This paper presents a methodology for simultaneous heterogeneous computing, named ENEAC, where a quad core ARM Cortex-A53 CPU works in tandem with a preprogrammed on-board FPGA accelerator. A heterogeneous scheduler distributes the tasks…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-16 Kris Nikov , Mohammad Hosseinabady , Rafael Asenjo , Andrés Rodríguezz , Angeles Navarro , Jose Nunez-Yanez

High Performance Distributed Computing is essential to boost scientific progress in many areas of science and to efficiently deploy a number of complex scientific applications. These applications have different characteristics that require…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-12-04 Mariza Ferro , Antonio R. Mury , Laion F. Manfroi , Bruno Schlze

Serverless computing is increasingly popular because of the promise of lower cost and the convenience it provides to users who do not need to focus on server management. This has resulted in the availability of a number of proprietary and…

Performance · Computer Science 2019-12-16 Junfeng Li , Sameer G. Kulkarni , K. K. Ramakrishnan , Dan Li

Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specialized capabilities at the system-, science- and service-level…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-15 Ilkay Altintas , Ismael Perez , Dmitry Mishin , Adrien Trouillaud , Christopher Irving , John Graham , Mahidhar Tatineni , Thomas DeFanti , Shawn Strande , Larry Smarr , Michael L. Norman

Edge computing enables smart IoT-based systems via concurrent and continuous execution of latency-sensitive machine learning (ML) applications. These edge-based machine learning systems are often battery-powered (i.e., energy-limited). They…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-07-22 Ali Mokhtari , Md Abir Hossen , Pooyan Jamshidi , Mohsen Amini Salehi

There is a growing need for low latency for many devices and users. The traditional cloud computing paradigm can not meet this requirement, legitimizing the need for a new paradigm. Edge computing proposes to move computing capacities to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-12 Samuel Rac , Mats Brorsson

With the increasing popularity of accelerator technologies (e.g., GPUs and TPUs) and the emergence of domain-specific computing via ASICs and FPGA, the matter of heterogeneity and understanding its ramifications on the performance has…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-21 Ali Mokhtari , Drake Rawls , Tony Huynh , Jeremiah Green , Mohsen Amini Salehi

The aim of the paper is to introduce general techniques in order to optimize the parallel execution time of sorting on a distributed architectures with processors of various speeds. Such an application requires a partitioning step. For…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-08-16 Christophe Cérin , Jean-Christophe Dubacq , Jean-Louis Roch , the SafeScale Collaboration