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Early Experiences in Running Many-Task Computing Workloads on GPGPUs

Scott J. Krieder, Benjamin Grimmer, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, Task scheduling

October 19, 2013 by hgpu

Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

Andrey Vladimirov and Vadim Karpusenko

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Tags: Heterogeneous systems, Intel Phi, Intel Xeon Phi, Monte Carlo simulation, MPI, Portability, Task scheduling

October 18, 2013 by Andrey Vladimirov

Dynamic Load Balancing in GPU-Based Systems – Early Experiments

Alvaro Luiz Fazenda, Celso L. Mendes, Laxmikant V. Kale, Jairo Panetta, Eduardo Rocha Rodrigues

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Tags: Computer science, CUDA, nVidia, OpenACC, Task scheduling, Tesla K20, Virtualization

October 18, 2013 by hgpu

OpenCL Task Partitioning in the Presence of GPU Contention

Dominik Grewe, Zheng Wang, and Michael F.P. O'Boyle

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Tags: Computer science, Heterogeneous systems, Intel, Intel HD Graphics 4000, Machine learning, OpenCL, Task scheduling

September 25, 2013 by hgpu

A Feedback Approach to Task Partitioning in Heterogeneous Architectures

Yasir Ali, Zuhair Qadir

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Tags: ATI, ATI Radeon HD 5770, Computer science, Heterogeneous systems, OpenCL, Task scheduling

August 30, 2013 by hgpu

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

Lars Schor, Andreas Tretter, Tobias Scherer, Lothar Thiele

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Tags: ATI, ATI Radeon HD 7750, Computer science, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 670, nVidia Quadro K 2000 M, OpenCL, Task scheduling

August 13, 2013 by hgpu

Opportunities for Heterogeneous CPUGPU Task Scheduling

Christiaan Arnoldus, Robert Witte

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Tags: ATI, ATI Radeon HD 4850, Computer science, Heterogeneous systems, nVidia, nVidia GeForce 9200 M GS, OpenCL, Task scheduling

July 31, 2013 by hgpu

Scheduling by Work-Stealing in Hybrid Parallel Architectures

Vinicius Garcia Pinto, Nicolas Maillard

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Task scheduling

July 24, 2013 by hgpu

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Vu Dinh Trung, Tran Van Lang

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 250, Task scheduling

July 17, 2013 by hgpu

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Bilel Ben Romdhanne, Mohamed Said Mosli, Navid Nikaein, Christian Bonnet

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Task scheduling

July 9, 2013 by hgpu

Towards Performance-Portable, Scalable, and Convenient Linear Algebra

Philippe Tillet, Karl Rupp, Siegfried Selberherr, Chin-Teng Lin

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Tags: ATI, ATI Radeon HD 7970, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 470, OpenCL, Task scheduling

July 1, 2013 by hgpu

Parallel Asynchronous Modelization and Execution of Cholesky Algorithm using Petri Nets

Gustavo Wolfmann, Armando De Giusti

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 470, Task scheduling

June 19, 2013 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Early Experiences in Running Many-Task Computing Workloads on GPGPUs

Heterogeneous Clustering with Homogeneous Code: Accelerate MPI Applications Without Code Surgery Using Intel Xeon Phi Coprocessors

Dynamic Load Balancing in GPU-Based Systems – Early Experiments

OpenCL Task Partitioning in the Presence of GPU Contention

A Feedback Approach to Task Partitioning in Heterogeneous Architectures

Exploiting the Parallelism of Heterogeneous Systems using Dataflow Graphs on Top of OpenCL

Opportunities for Heterogeneous CPUGPU Task Scheduling

Scheduling by Work-Stealing in Hybrid Parallel Architectures

Parallelization the Job-shop Problem on Distributed and Shared Memory Architectures

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Towards Performance-Portable, Scalable, and Convenient Linear Algebra

Parallel Asynchronous Modelization and Execution of Cholesky Algorithm using Petri Nets

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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