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The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of processor, such as CPUs, GPUs, and FPGAs. Several types of…

Software Engineering · Computer Science 2020-05-19 Hugo Andrade , Ivica Crnkovic , Jan Bosch

The growing demand for real-time DNN applications on edge devices necessitates faster inference of increasingly complex models. Although many devices include specialized accelerators (e.g., mobile GPUs), dynamic control-flow operators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-12-15 Chong Tang , Hao Dai , Jagmohan Chauhan

Heterogeneous computing platforms consisting of general purpose processors (GPPs) and graphics processing units (GPUs) have become commonplace in personal mobile devices and embedded systems. For years, programming of these platforms was…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-11 Jani Boutellier , Ilkka Hautala

Heterogeneous many-cores are now an integral part of modern computing systems ranging from embedding systems to supercomputers. While heterogeneous many-core design offers the potential for energy-efficient high-performance, such potential…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-11 Jianbin Fang , Chun Huang , Tao Tang , Zheng Wang

In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-12 Jose Nunez-Yanez , Mohammad Hosseinabady , Moslem Amiri , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Rubén Gran-Tejero , Darío Suárez-Gracia

This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogeneous many-core architectures. Our approach employs a…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-10 Peng Zhang , Jianbin Fang , Canqun Yang , Chun Huang , Tao Tang , Zheng Wang

Due to the diversity and implicit redundancy in terms of processing units and compute kernels, off-the-shelf heterogeneous systems offer the opportunity to detect and tolerate faults during task execution in hardware as well as in software.…

Operating Systems · Computer Science 2014-05-14 Mario Kicherer , Wolfgang Karl

The usage of large language models (LLMs) has grown increasingly fragmented, with no single model dominating. Meanwhile, cloud providers offer a wide range of mid-tier and older-generation GPUs that enjoy better availability and deliver…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-07 Yixuan Mei , Zikun Li , Zixuan Chen , Shiqi Pan , Mengdi Wu , Xupeng Miao , Zhihao Jia , K. V. Rashmi

Massively multicore processors, such as Graphics Processing Units (GPUs), provide, at a comparable price, a one order of magnitude higher peak performance than traditional CPUs. This drop in the cost of computation, as any…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-18 Samer Al-Kiswany , Abdullah Gharaibeh , Matei Ripeanu

Deep neural network (DNN) has driven extensive applications in mobile technology. However, for long-running mobile apps like voice assistants or video applications on smartphones, energy efficiency is critical for battery-powered devices.…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-01 Zheng Lin , Bin Guo , Sicong Liu , Wentao Zhou , Yasan Ding , Yu Zhang , Zhiwen Yu

Because most optimisations to achieve higher computational performance eventually are limited, parallelism that scales is required. Parallelised hardware alone is not sufficient, but software that matches the architecture is required to…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-11 Oskar Schirmer

We propose a new hybrid topology optimization algorithm based on multigrid approach that combines the parallelization strategy of CPU using OpenMP and heavily multithreading capabilities of modern Graphics Processing Units (GPU). In…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-01 Arya Prakash Padhi , Souvik Chakraborty , Anupam Chakrabarti , Rajib Chowdhury

This paper presents an empirical study regarding the energy consumption of the most used web browsers on the Android ecosystem. In order to properly compare the web browsers in terms of energy consumption, we defined a set of typical usage…

Software Engineering · Computer Science 2022-05-24 Nélson Gonçalves , Rui Rua , Jácome Cunha , Rui Pereira , João Saraiva

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

Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contending with constrained memory availability and heterogeneous hardware targets. To realize this…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-21 Reese Levine , Rithik Sharma , Nikhil Jain , Abhijit Ramesh , Zheyuan Chen , Neha Abbas , James Contini , Tyler Sorensen

Multi-chiplet architectures enabled by glass interposer offer superior electrical performance, enable higher bus widths due to reduced crosstalk, and have lower capacitance in the redistribution layer than current silicon interposer-based…

Hardware Architecture · Computer Science 2025-07-25 Harsh Sharma , Janardhan Rao Doppa , Umit Y. Ogras , Partha Pratim Pande

Performance and energy are the two most important objectives for optimisation on modern parallel platforms. Latest research demonstrated the importance of workload distribution as a decision variable in the bi-objective optimisation for…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-10 Hamidreza Khaleghzadeh , Muhammad Fahad , Arsalan Shahid , Ravi Reddy Manumachu , Alexey Lastovetsky

Heterogeneous computers integrate general-purpose host processors with domain-specific accelerators to combine versatility with efficiency and high performance. To realize the full potential of heterogeneous computers, however, many…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-12 Andreas Kurth , Björn Forsberg , Luca Benini

Energy efficiency can have a significant influence on user experience of mobile devices such as smartphones and tablets. Although energy is consumed by hardware, software optimization plays an important role in saving energy, and thus…

Software Engineering · Computer Science 2016-08-19 Xueliang Li , John P. Gallagher

Decreasing hardware feature sizes and increasing heterogeneity in multicore hardware require software that can adapt to these platforms' properties. We implemented ROMAIN, an OS service providing redundant multithreading on top of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-05-14 Björn Döbel , Robert Muschner , Hermann Härtig