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Automatic Command Queue Scheduling for Task-Parallel Workloads in OpenCL

Ashwin M. Aji, Antonio J. Pena, Pavan Balaji, Wu-chun Feng

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Tags: Computer science, Heterogeneous systems, nVidia, OpenCL, Performance, Seismology, Task scheduling, Tesla C2050

February 23, 2016 by hgpu

High performance high-order numerical methods: applications in ocean modeling

Rajesh Gandham

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Tags: ATI, ATI Radeon HD 7970, cfd, Computer science, CUDA, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX Titan, OCCA, OpenCL, OpenMP, real time systems, Tesla C2050, Tesla K20, Tesla K40, Thesis

February 8, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Mishal Almazrooie, Mogana Vadiveloo, Rosni Abdullah

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla C2050

January 7, 2016 by hgpu

Parallel 3D Fast Wavelet Transform comparison on CPUs and GPUs

Gregorio Bernabe

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Tags: Computer science, CUDA, FFT, nVidia, OpenCL, OpenMP, Pthreads, Tesla C2050

December 31, 2015 by hgpu

On the Way to Future’s High Energy Particle Physics Transport Code

Gabor Biro, Gergely Gabor Barnafoldi, Endre Futo

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Tags: Computational Physics, Computer science, nVidia, OpenCL, Physics, SYCL, Tesla C2050

December 23, 2015 by hgpu

Efficient Query Processing in Co-Processor-accelerated Databases

Sebastian Bress

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Package, Tesla C1060, Tesla C2050, Thesis

December 19, 2015 by hgpu

Estimation of numerical reproducibility on CPU and GPU

Fabienne Jezequel, Jean-Luc Lamotte, Issam Said

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, OpenCL, Tesla C2050, Tesla K20

October 31, 2015 by hgpu

A progressive mesh method for physical simulations using lattice Boltzmann method on single-node multi-gpu architectures

Julien Duchateau, Francois Rousselle, Nicolas Maquignon, Gilles Roussel, Christophe Renaud

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Tesla C2050

October 16, 2015 by hgpu

Exploiting Task-Parallelism on GPU Clusters via OmpSs and rCUDA Virtualization

Adrian Castello, Rafael Mayo, Judit Planas, Enrique S. Quintana-Orti

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Tags: Computer science, CUDA, GPU cluster, nVidia, OmpSs, Tesla C2050, Tesla M2050, Virtualization

October 8, 2015 by hgpu

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 by hgpu

Scheduling for new computing platforms with GPUs

Florence Monna

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Tags: Computer science, Data Structures and Algorithms, nVidia, OpenCL, Task scheduling, Tesla C2050, Thesis

August 24, 2015 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Automatic Command Queue Scheduling for Task-Parallel Workloads in OpenCL

High performance high-order numerical methods: applications in ocean modeling

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Parallel 3D Fast Wavelet Transform comparison on CPUs and GPUs

On the Way to Future’s High Energy Particle Physics Transport Code

Efficient Query Processing in Co-Processor-accelerated Databases

Estimation of numerical reproducibility on CPU and GPU

A progressive mesh method for physical simulations using lattice Boltzmann method on single-node multi-gpu architectures

Exploiting Task-Parallelism on GPU Clusters via OmpSs and rCUDA Virtualization

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Scheduling for new computing platforms with GPUs

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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