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Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

David Beniamine

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Tags: Computer science, CUDA, nVidia, nVidia Quadro NVS 300, Task scheduling, Tesla C2050, Thesis

January 29, 2014 by hgpu

Automatic Resource-Constrained Static Task Parallelization

Dounia Khaldi

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Tags: Algorithms, Code generation, Computer science, MPI, OpenCL, Task scheduling, Thesis

January 28, 2014 by hgpu

A Dynamic Offload Scheduler for spatial multitasking on Intel Xeon Phi Coprocessor

Takamichi Miyamoto, Kazuhisa Ishizaka, Takeo Hosomi

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Tags: Computer science, Intel Xeon Phi, Task scheduling

January 26, 2014 by hgpu

Multi-GPU Load Balancing for In-Situ Simulation and Visualization

Yong Cao, Robert Hagan

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Tags: Computer science, nVidia, nVidia GeForce GTX 295, Rendering, Task scheduling, Visualization

December 27, 2013 by hgpu

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Tetsuya Odajima, Taisuke Boku, Mitsuhisa Sato, Toshihiro Hanawa, Yuetsu Kodama, Raymond Namyst, Samuel Thibault, Olivier Aumage

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Performance, Task scheduling, Tesla M2090

December 25, 2013 by hgpu

Towards global composition of performance-aware components for GPU-based systems

Usman Dastgeer, Christoph Kessler

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Tags: Computer science, CUDA, Flow analysis, Heterogeneous systems, nVidia, Task scheduling, Tesla C2050

December 20, 2013 by hgpu

Data Structures for Task-based Priority Scheduling

Martin Wimmer, Daniel Cederman, Francesco Versaci, Jesper Larsson Traff, Philippas Tsigas

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Source codes

Tags: Algorithms, Computer science, Intel Xeon Phi, Package, Task scheduling

December 17, 2013 by hgpu

Experience with Intel’s Many Integrated Core architecture in ATLAS software

S. Fleischmann, S. Kama, W. Lavrijsen, M. Neumann, R. Vitillo

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Tags: Computer science, High Energy Physics - Experiment, Intel Phi, Intel Xeon Phi, MPI, Physics, Task scheduling

November 21, 2013 by hgpu

Comparative Performance Analysis of Intel Xeon Phi, GPU, and CPU

George Teodoro, Tahsin Kurc, Jun Kong, Lee Cooper, Joel Saltz

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Tags: Computer science, CUDA, Intel Phi, Intel Xeon Phi, Microscopy, nVidia, OpenMP, Performance, Task scheduling, Tesla K20

November 6, 2013 by hgpu

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

Uri Verner, Avi Mendelson, Assaf Schuster

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Task scheduling, Tesla C2050, Tesla K10

November 4, 2013 by hgpu

Parallel CPU and GPU computations to solve the job shop scheduling problem with blocking

Abdelhakim AitZai, Adel Dabah, Mourad Boudhar

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia Quadro 2000, Task scheduling

November 3, 2013 by hgpu

Optimization of the HEFT algorithm for a CPU-GPU environment

Karan R. Shetti, Suhaib A. Fahmy, Timo Bretschneider

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Tags: Algorithms, Computer science, Heterogeneous systems, Task scheduling

October 21, 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

Impact of communication times on mixed CPU/GPU applications scheduling using KAAPI

Automatic Resource-Constrained Static Task Parallelization

A Dynamic Offload Scheduler for spatial multitasking on Intel Xeon Phi Coprocessor

Multi-GPU Load Balancing for In-Situ Simulation and Visualization

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Towards global composition of performance-aware components for GPU-based systems

Data Structures for Task-based Priority Scheduling

Experience with Intel’s Many Integrated Core architecture in ATLAS software

Comparative Performance Analysis of Intel Xeon Phi, GPU, and CPU

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

Parallel CPU and GPU computations to solve the job shop scheduling problem with blocking

Optimization of the HEFT algorithm for a CPU-GPU environment

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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