high performance computing on graphics processing units: hgpu.org

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Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

Prabhakar Misra, Mainak Chaudhuri

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, Performance, Tesla C2070

September 8, 2012 by hgpu

GPU Computing and CUDA technology used to accelerate a mesh generator application

Adriana Gaudiani, Santiago Montiel, Javier Pimas

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Tags: Computer science, CUDA, nVidia, Tesla C2070

September 7, 2012 by hgpu

A GPGPU Implementation of Approximate String Matching with Regular Expression Operators and Comparison with Its FPGA Implementation

Yuichiro Utan, Masato Inagi, Shin'ichi Wakabayashi, Shinobu Nagayama

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Tags: Algorithms, Computer science, CUDA, Databases, FPGA, nVidia, String matching, Tesla C2070

September 5, 2012 by hgpu

A Portable High-Productivity Approach to Program Heterogeneous Systems

Zeki Bozkus, Basilio B. Fraguela

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Tags: Computer science, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Tesla C2070

September 1, 2012 by hgpu

A GPU Support for Large Scale Quantum Chemistry Applications

Selva Kumar Sengottaiyan, Fang Liu, Masha Sosonkina

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Tags: Chemistry, CUDA, nVidia, Tesla C2070, Visualization

September 1, 2012 by hgpu

High accuracy solutions to energy gradient flows from material science models

Andrew Christlieb, Jaylan Jones, Keith Promislow, Brian Wetton, Mark Willoughby

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Tags: CUDA, Materials Science, nVidia, Spectral methods, Tesla C2070

August 16, 2012 by hgpu

A GPU implementation of the Simulated Annealing Heuristic for the Quadratic Assignment Problem

Gerald Paul

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Tags: Computer science, CUDA, Metaheuristics, nVidia, Tesla C2070

August 14, 2012 by hgpu

Designing OP2 for GPU architectures

M.B. Giles, G.R. Mudalige, B. Spencer, C. Bertolli, I. Reguly

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Source codes

Tags: Computer science, nVidia, nVidia GeForce GTX 560 Ti, Optimization, Package, Performance, Tesla C2070

August 11, 2012 by hgpu

Compiler Optimizations for Industrial Unstructured Mesh CFD Applications on GPUs

C. Bertolli, A. Betts, N. Loriant, G. R. Mudalige, D. Radford, M. B. Giles, P. H.J. Kelly

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Tags: CUDA, Fluid dynamics, nVidia, Tesla C2070

August 11, 2012 by hgpu

OP2: An Active Library Framework for Solving Unstructured Mesh-based Applications on Multi-Core and Many-Core Architectures

G.R. Mudalige, M.B. Giles, I. Reguly, C. Bertolli, P.H.J Kelly

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, Performance, Tesla C2050, Tesla C2070

August 11, 2012 by hgpu

Optimizing Memory-Bound Numerical Kernels on GPU Hardware Accelerators

Ahmad Abdelfattah, Jack Dongarra, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, nVidia, Optimization, Package, Tesla C2070

August 10, 2012 by hgpu

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

Haicheng Wu, Gregory Diamos, Ashwin Lele, Jin Wang, Srihari Cadambi, Sudhakar Yalamanchili, Srimat Chakradhar

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Tags: Compilers, Computer science, CUDA, Databases, nVidia, Optimization, Tesla C2070

August 9, 2012 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

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high performance computing on graphics processing units: hgpu.org

Performance Evaluation of Concurrent Lock-free Data Structures on GPUs

GPU Computing and CUDA technology used to accelerate a mesh generator application

A GPGPU Implementation of Approximate String Matching with Regular Expression Operators and Comparison with Its FPGA Implementation

A Portable High-Productivity Approach to Program Heterogeneous Systems

A GPU Support for Large Scale Quantum Chemistry Applications

High accuracy solutions to energy gradient flows from material science models

A GPU implementation of the Simulated Annealing Heuristic for the Quadratic Assignment Problem

Designing OP2 for GPU architectures

Compiler Optimizations for Industrial Unstructured Mesh CFD Applications on GPUs

OP2: An Active Library Framework for Solving Unstructured Mesh-based Applications on Multi-Core and Many-Core Architectures

Optimizing Memory-Bound Numerical Kernels on GPU Hardware Accelerators

Optimizing Data Warehousing Applications for GPUs Using Kernel Fusion/Fission

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)