Results 41 to 50 of about 7,328 (165)

HARD: A performance portable radiation hydrodynamics code based on FleCSI framework

SoftwareX
Hydrodynamics And Radiation Diffusion (HARD) is an open-source application for high-performance simulations of compressible hydrodynamics with radiation-diffusion coupling.
Julien Loiseau, Hyun Lim, Andrés Yagüe López, Mammadbaghir Baghirzade, Shihab Shahriar Khan, Yoonsoo Kim, Sudarshan Neopane, Alexander Strack, Farhana Taiyebah, Ben Bergen   +9 more
doaj   +1 more source

DBEFT: A Dependency-Ratio Bundling Earliest Finish Time Algorithm for Heterogeneous Computing

IEEE Access, 2019
Performance effective task scheduling algorithms are essential for taking advantage of the heterogeneous multi-processor in heterogeneous computing environments.
Tao Li, Dingyuan Cao, Ye Lu, Tehui Huang, Chengjun Sun, Qiankun Dong, Xiaoli Gong   +6 more
doaj   +1 more source

Multi-Shape Task Placement Algorithm Based on Low Fragmentation Resource Management on 2D Heterogeneous Dynamic Partial Reconfigurable Devices

IEEE Access, 2020
The Dynamic Partial Reconfiguration function of reconfigurable devices permits tasks to be performed simultaneously on a single device. Nevertheless, task placement and resource management problems emerge with the parallelism of reconfigurable devices ...
Tingyu Zhou, Tieyuan Pan, Michael Conrad Meyer, Yiping Dong, Takahiro Watanabe   +4 more
doaj   +1 more source

Enhancement of GPU-accelerated smoothed particle hydrodynamics (SPH) method with dynamic parallelism

Results in Engineering
An innovative GPU programming architecture leveraging CUDA Dynamic Parallelism (CDP) is introduced in this study, aiming to enhance the computational efficiency of Smoothed Particle Hydrodynamics (SPH) simulations.
Liwen Xue, Shenglong Gu, Songdong Shao
doaj   +1 more source

Response errors explain the failure of independent-channels models of perception of temporal order

Frontiers in Psychology, 2012
Independent-channels models of perception of temporal order (also referred to as threshold models or perceptual latency models) have been ruled out because two formal properties of these models (monotonicity and parallelism) are not borne out by data ...
Miguel A García-Pérez, Rocio eAlcala-Quintana   +1 more
doaj   +1 more source

Towards Task-Parallel Reductions in OpenMP

, 2015
Reductions represent a common algorithmic pattern in many scientific applications. OpenMP* has always supported them on parallel and worksharing constructs. OpenMP 3.0’s tasking constructs enable new parallelization opportunities through the annotation of irregular algorithms.
Jan Ciesko, Sergi Mateo, Xavier Teruel, Xavier Martorell, Eduard Ayguadé, Jesús Labarta, Alex Duran, Bronis R. de Supinski, Stephen Olivier, Kelvin Li, Alexandre E. Eichenberger   +10 more
openaire   +2 more sources

Task-Level Checkpointing System for Task-Based Parallel Workflows

, 2023
Scientific applications are large and complex; task-based programming models are a popular approach to developing these applications due to their ease of programming and ability to handle complex workflows and distribute their workload across large infrastructures.
Pere Vergés, Francesc Lordan, Jorge Ejarque, Rosa M. Badia   +3 more
openaire   +2 more sources

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

International Journal of Reconfigurable Computing, 2018
CPU has insufficient resources to satisfy the efficient computation of the convolution neural network (CNN), especially for embedded applications. Therefore, heterogeneous computing platforms are widely used to accelerate CNN tasks, such as GPU, FPGA ...
Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang   +9 more
doaj   +1 more source

Distributed Memory Implementation of Bron-Kerbosch Algorithm

IEEE Access
This paper proposes a parallel implementation of the Bron-Kerbosch algorithm, which finds all maximal cliques in large, complex graphs using CPU and thread-level parallelism and distributed memory with multiple cores. With the growing size and complexity
Tejas Ravindra Rote, Murugan Krishnammorthy, Ansh Bhatia, Rishu Yadav, S. P. Raja   +4 more
doaj   +1 more source

Scalable deep text comprehension for Cancer surveillance on high-performance computing

BMC Bioinformatics, 2018
Background Deep Learning (DL) has advanced the state-of-the-art capabilities in bioinformatics applications which has resulted in trends of increasingly sophisticated and computationally demanding models trained by larger and larger data sets.
John X. Qiu, Hong-Jun Yoon, Kshitij Srivastava, Thomas P. Watson, J. Blair Christian, Arvind Ramanathan, Xiao C. Wu, Paul A. Fearn, Georgia D. Tourassi   +8 more
doaj   +1 more source