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High-performance computing (HPC) requires resilience techniques such as checkpointing in order to tolerate failures in supercomputers. As the number of nodes and memory in supercomputers keeps on increasing, the size of checkpoint data also…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-13 Kai Keller , Leonardo Bautista Gomez

Accelerator-based heterogeneous architectures, such as CPU-GPU, CPU-TPU, and CPU-FPGA systems, are widely adopted to support the popular artificial intelligence (AI) algorithms that demand intensive computation. When deployed in real-time…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-20 An Zou , Yuankai Xu , Yinchen Ni , Jintao Chen , Yehan Ma , Jing Li , Christopher Gill , Xuan Zhang , Yier Jin

This paper provides an in-depth characterization of GPU-accelerated systems, to understand the interplay between overlapping computation and communication which is commonly employed in distributed training settings. Due to the large size of…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-07-08 Seonho Lee , Jihwan Oh , Junkyum Kim , Seokjin Go , Jongse Park , Divya Mahajan

We introduce a new Partition of Unity Method for the numerical homogenization of elliptic partial differential equations with arbitrarily rough coefficients. We do not restrict to a particular ansatz space or the existence of a finite…

Numerical Analysis · Mathematics 2016-05-04 Daniel Peterseim , Patrick Henning , Philipp Morgenstern

Many important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-09-21 Paweł Rościszewski

We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU…

Soft Condensed Matter · Physics 2018-08-01 Michael P. Howard , Athanassios Z. Panagiotopoulos , Arash Nikoubashman

This paper describes the main features of a pioneering unsteady solver for simulating ideal two-fluid plasmas on unstructured grids, taking profit of GPGPU (General-purpose computing on graphics processing units). The code, which has been…

A modern graphics processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two dimensional Ising model [T. Preis et al., J. Comp.…

Computational Physics · Physics 2010-07-22 Benjamin Block , Peter Virnau , Tobias Preis

We describe the use of Graphics Processing Units (GPUs) for speeding up the code NBODY6 which is widely used for direct $N$-body simulations. Over the years, the $N^2$ nature of the direct force calculation has proved a barrier for…

Instrumentation and Methods for Astrophysics · Physics 2015-06-05 Keigo Nitadori , Sverre J. Aarseth

Dynamic Parallelism (DP) is a runtime feature of the GPU programming model that allows GPU threads to execute additional GPU kernels, recursively. Apart from making the programming of parallel hierarchical patterns easier, DP can also…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-07 Felipe A. Quezada , Cristóbal A. Navarro , Miguel Romero , Cristhian Aguilera

We propose a high-performance GPU solver for inverse homogenization problems to design high-resolution 3D microstructures. Central to our solver is a favorable combination of data structures and algorithms, making full use of the parallel…

Optimization and Control · Mathematics 2023-05-26 Di Zhang , Xiaoya Zhai , Ligang Liu , Xiao-Ming Fu

In this paper, we introduce Heteroflow, a new C++ library to help developers quickly write parallel CPU-GPU programs using task dependency graphs. Heteroflow leverages the power of modern C++ and task-based approaches to enable efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-17 Tsung-Wei Huang , Yibo Lin

As deep learning models are increasingly deployed on mobile devices, modern mobile devices incorporate deep learning-specific accelerators to handle the growing computational demands, thus increasing their hardware heterogeneity. However,…

Machine Learning · Computer Science 2025-08-26 Duseok Kang , Yunseong Lee , Junghoon Kim

We discuss the development, verification, and performance of a GPU accelerated discontinuous Galerkin method for the solutions of two dimensional nonlinear shallow water equations. The shallow water equations are hyperbolic partial…

Numerical Analysis · Mathematics 2023-07-19 R Gandham , D S Medina , T Warburton

Heterogeneous computing is one of the most important computational solutions to meet rapidly increasing demands on system performance. It typically allows the main flow of applications to be executed on a CPU while the most computationally…

Software Engineering · Computer Science 2020-12-11 Hugo Andrade , Ola Benderius , Christian Berger , Ivica Crnkovic , Jan Bosch

We present a highly scalable, MPI-parallelized framework for reconstructing the initial cosmic density field, designed to meet the computational demands of next-generation cosmological simulations, particularly the upcoming ELUCID-DESI…

This paper introduces Helix, a distributed system for high-throughput, low-latency large language model (LLM) serving in heterogeneous GPU clusters. The key idea behind Helix is to formulate inference computation of LLMs over heterogeneous…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-07 Yixuan Mei , Yonghao Zhuang , Xupeng Miao , Juncheng Yang , Zhihao Jia , Rashmi Vinayak

This paper presents a Graphics Processing Units (GPUs) acceleration method of an iterative scheme for gas-kinetic model equations. Unlike the previous GPU parallelization of explicit kinetic schemes, this work features a fast converging…

Computational Physics · Physics 2020-01-08 Lianhua Zhu , Peng Wang , Songze Chen , Zhaoli Guo , Yonghao Zhang

The latest Graphics Processing Units (GPUs) are reported to reach up to 200 billion floating point operations per second (200 Gflops) and to have price performance of 0.1 cents per M flop. These facts raise great interest in the…

Graphics · Computer Science 2016-08-31 S. Tomov , M. McGuigan , R. Bennett , G. Smith , J. Spiletic

Recent breakthroughs in Large-scale language models (LLMs) have demonstrated impressive performance on various tasks. The immense sizes of LLMs have led to very high resource demand and cost for running the models. Though the models are…

Machine Learning · Computer Science 2024-03-05 Juntao Zhao , Borui Wan , Yanghua Peng , Haibin Lin , Chuan Wu
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