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In the field of MLLM-based GUI agents, compared to smartphones, the PC scenario not only features a more complex interactive environment, but also involves more intricate intra- and inter-app workflows. To address these issues, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Haowei Liu , Xi Zhang , Haiyang Xu , Yuyang Wanyan , Junyang Wang , Ming Yan , Ji Zhang , Chunfeng Yuan , Changsheng Xu , Weiming Hu , Fei Huang

A new class of Second generation high-performance computing applications with heterogeneous, dynamic and data-intensive properties have an extended set of requirements, which cover application deployment, resource allocation, -control, and…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-28 Ole Weidner , Malcolm Atkinson , Adam Barker , Rosa Filgueira

This paper presents a comparison of OpenMP and OpenCL based on the parallel implementation of algorithms from various fields of computer applications. The focus of our study is on the performance of benchmark comparing OpenMP and OpenCL. We…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-11-12 Krishnahari Thouti , S. R. Sathe

Parallel programming remains a daunting challenge, from the struggle to express a parallel algorithm without cluttering the underlying synchronous logic, to describing which devices to employ in a calculation, to correctness. Over the…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-08-10 Patrick Diehl , Steven R. Brandt , Hartmut Kaiser

The current trend of technology has brought parallel machines equipped with multiple processors and multiple memory sockets to be available off-the-shelf -- or via renting through Iaas Clouds -- at reasonable costs. This has opened the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-26 Romolo Marotta , Francesco Quaglia

Heterogeneous computing is the strategy of deploying multiple types of processing elements within a single workflow, and allowing each to perform the tasks to which is best suited. To fully harness the power of heterogeneity, we want to be…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-03 Nikolaos Mavrogeorgis

Asynchronous Many-Task (AMT) runtimes offer a productive alternative to the Message Passing Interface (MPI). However, the diverse AMT landscape makes fair comparisons challenging. Task Bench, proposed by Slaughter et al., addresses this…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-16 Torben R. Lahnor , Mia Reitz , Jonas Posner , Patrick Diehl

The scalability and efficiency of graph applications are significantly constrained by conventional systems and their supporting programming models. Technology trends like multicore, manycore, and heterogeneous system architectures are…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-22 Chirag Dekate , Matthew Anderson , Maciej Brodowicz , Hartmut Kaiser , Bryce Adelstein-Lelbach , Thomas Sterling

In the last fifteen years, the high performance computing (HPC) community has claimed for parallel programming environments that reconciles generality, higher level of abstraction, portability, and efficiency for distributed-memory parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-08-21 Francisco Heron de Carvalho-Junior , Rafael Dueire Lins

We present our experience with the modernization on the GR-MHD code BHAC, aimed at improving its novel hybrid (MPI+OpenMP) parallelization scheme. In doing so, we showcase the use of performance profiling tools usable on x86 (Intel-based)…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-30 Salvatore Cielo , Oliver Porth , Luigi Iapichino , Anupam Karmakar , Hector Olivares , Chun Xia

Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-15 J. Gregory Pauloski , Valerie Hayot-Sasson , Maxime Gonthier , Nathaniel Hudson , Haochen Pan , Sicheng Zhou , Ian Foster , Kyle Chard

Efficiently serving Large Language Models (LLMs) requires selecting an optimal parallel execution plan, balancing computation, memory, and communication overhead. However, determining the best strategy is challenging due to varying…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-01 Yi-Chien Lin , Woosuk Kwon , Ronald Pineda , Fanny Nina Paravecino

Driven by artificial intelligence, data science, and high-resolution simulations, I/O workloads and hardware on high-performance computing (HPC) systems have become increasingly complex. This complexity can lead to large I/O overheads and…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-01-03 Hammad Ather , Jean Luca Bez , Chen Wang , Hank Childs , Allen D. Malony , Suren Byna

The simplex algorithm has been successfully used for many years in solving linear programming (LP) problems. Due to the intensive computations required (especially for the solution of large LP problems), parallel approaches have also…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-11-22 Basilis Mamalis , Marios Perlitis

In the high performance computing (HPC) domain, performance variability is a major scalability issue for parallel computing applications with heavy synchronization and communication. In this paper, we present an experimental performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-10 Minyu Cui , Nikela Papadopoulou , Miquel Pericàs

Exceptions and errors occurring within mission critical applications due to hardware failures have a high cost. With the emerging Next Generation Platforms (NGPs), the rate of hardware failures will likely increase. Therefore, designing our…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-10-22 Nikunj Gupta , Jackson R. Mayo , Adrian S. Lemoine , Hartmut Kaiser

Over recent years heterogeneous systems have become more prevalent across HPC systems, with over 100 supercomputers in the TOP500 incorporating GPUs or other accelerators. These hardware platforms have different performance characteristics…

Performance · Computer Science 2019-04-11 John Lawson , Mehdi Goli , Duncan McBain , Daniel Soutar , Louis Sugy

FPGAs have found increasing adoption in data center applications since a new generation of high-level tools have become available which noticeably reduce development time for FPGA accelerators and still provide high quality of results.…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-06-15 Marius Meyer , Tobias Kenter , Christian Plessl

As dataset sizes increase, data analysis tasks in high performance computing (HPC) are increasingly dependent on sophisticated dataflows and out-of-core methods for efficient system utilization. In addition, as HPC systems grow, memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-01 George K. Thiruvathukal , Cameron Christensen , Xiaoyong Jin , François Tessier , Venkatram Vishwanath

Asymmetric multicore processors (AMPs) couple high-performance big cores and low-power small cores with the same instruction-set architecture but different features, such as clock frequency or microarchitecture. Previous work has shown that…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-02-13 Juan Carlos Saez , Fernando Castro , Manuel Prieto-Matias