high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming

Peng Du, Rick Weber, Piotr Luszczek, Stanimire Tomov, Gregory Peterson, Jack Dongarra

View

Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, OpenCL, Optimization, Performance, Tesla C2050

September 26, 2011 by hgpu

Identifying scalar behavior in CUDA kernels

Sylvain Collange

View

Download (PDF)

Tags: Benchmarking, Code generation, Compilers, Computer science, CUDA, nVidia, PTX

September 26, 2011 by hgpu

Putting Automatic Polyhedral Compilation for GPGPU to Work

Soufiane Baghdadi, Armin Grosslinger, Albert Cohen

View

Download (PDF)

Source codes

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, Package

September 26, 2011 by hgpu

Running unstructured grid-based CFD solvers on modern graphics hardware

Andrew Corrigan, Fernando F. Camelli, Rainald Lohner, John Wallin

View

Download (PDF)

Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Tesla

September 26, 2011 by hgpu

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

View

Download (PDF)

Tags: Algorithms, Code generation, Computer science, nVidia, OpenCL, Optimization, Statistics, Tesla C1060

September 25, 2011 by hgpu

Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

Thomas Grosser, Alexandros Gremm, Sebastian Veith, Gerald Heim, Wolfgang Rosenstiel, Victor Medeiros, Manoel Eusebio de Lima

View

Download (PDF)

Tags: Earth and Space Sciences, FPGA, Geoscience, Heterogeneous systems, nVidia, OpenCL, Optimization, Seismic modeling, Seismology, Tesla T10P

September 25, 2011 by hgpu

Harnessing the Power of GPUs without Losing Abstractions in SaC and ArrayOL: A Comparative Study

Jing Guo, Wendell Rodrigues, Jeyarajan Thiyagalingamz, Frederic Guyomarch, Pierre Boulet, Sven-Bodo Scholz

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Video encoding

September 25, 2011 by hgpu

Accelerating image recognition on mobile devices using GPGPU

Miguel Bordallo Lopez, Henri Nykanen, Jari Hannuksela, Olli Silven, Markku Vehvilainen

View

Download (PDF)

Tags: Algorithms, Computer science, Image processing, Image recognition, OpenCL, OpenGL

September 25, 2011 by hgpu

GPGPU workload analysis and media performance studies

Ashwini Simha

View

Download (PDF)

Tags: ATI, Benchmarking, Computer science, OpenCL, Performance, Thesis

September 25, 2011 by hgpu

Numerical Accuracy Differences in CPU and GPGPU Codes

Devon Yablonski

View

Download (PDF)

Tags: Computer science, CUDA, Floating point error, nVidia, Tesla C1060, Thesis

September 25, 2011 by hgpu

The Test and Evaluation Uses of Heterogeneous Computing: GPGPUs and Other Approaches

Dan M. Davis, Gene Wagenbreth, Robert F. Lucas, Paul C. Gregory

View

Download (PDF)

Tags: Computer science, Energy-efficient computing, Heterogeneous systems, nVidia, Overview, Tesla C1060

September 25, 2011 by hgpu

GPU-Based Acceleration of the MLEM Algorithm for SPECT Parallel Imaging with Attenuation Correction and Compensation for Detector Response

Akos Szlavecz, Gabor Hesz, Tamas Bukki, Bela Kari, Balazs Benyo

View

Download (PDF)

Tags: Algorithms, Computed tomography, CT, CUDA, Medicine, nVidia, nVidia GeForce GTX 480, Tomography, Visualization

September 25, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

From CUDA to OpenCL: Towards a Performance-portable Solution for Multi-platform GPU Programming

Identifying scalar behavior in CUDA kernels

Putting Automatic Polyhedral Compilation for GPGPU to Work

Running unstructured grid-based CFD solvers on modern graphics hardware

Optimizing OpenCL Kernels for Iterative Statistical Applications on GPUs

Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

Harnessing the Power of GPUs without Losing Abstractions in SaC and ArrayOL: A Comparative Study

Accelerating image recognition on mobile devices using GPGPU

GPGPU workload analysis and media performance studies

Numerical Accuracy Differences in CPU and GPGPU Codes

The Test and Evaluation Uses of Heterogeneous Computing: GPGPUs and Other Approaches

GPU-Based Acceleration of the MLEM Algorithm for SPECT Parallel Imaging with Attenuation Correction and Compensation for Detector Response

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)