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AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros

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Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia, OpemMP, Package, Tesla K20

June 30, 2015 by hgpu

Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs

Liang-Tsung Huang, Chao-Chin Wu, Lien-Fu Lai, Yun-Ju Li

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Tags: Bioinformatics, Biology, CUDA, Databases, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C1060, Tesla K20

June 30, 2015 by hgpu

Concurrent Task Execution on the Intel Xeon Phi

Yucheng Zhu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Intel Xeon Phi, nVidia, OpenMP, Sequence alignment, Smith-Waterman algorithm, Tesla K20, Thesis

June 22, 2015 by hgpu

Autotuning Tensor Contraction Computations on GPUs

Axel Rivera, Mary Hall, Paul D. Hovland, Elizabeth Jessup, Thomas Nelson, Boyana Norris

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Tags: Benchmarking, Code generation, Computer science, CUDA, Matrix multiplication, nVidia, OpenACC, Tesla C2050, Tesla K20

June 19, 2015 by hgpu

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Naveen Anand Subramaniam, Omkar Deshmukh, Vennila Megavannan, Dan Negrut

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20, Tesla K40

June 19, 2015 by hgpu

Automatic Data Layout Optimizations for GPUs

Klaus Kofler, Biagio Cosenza, Thomas Fahringer

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Tags: Algorithms, AMD FirePro S9000, ATI, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, OpenCL, Optimization, Tesla K20

June 17, 2015 by hgpu

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Unnikrishnan C, Y N Srikant, Rupesh Nasre

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Tags: Compilers, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, OpenMP, Tesla C2050, Tesla C2075, Tesla K20

June 16, 2015 by hgpu

Automatic Selection of Sparse Matrix Representation on GPUs

Naser Sedaghati, Te Mu, Louis-Noel Pouchet, Srinivasan Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Physics, Sparse matrix, Tesla K20, Tesla K40

June 14, 2015 by hgpu

Cryptanalysis of the McEliece Cryptosystem on GPGPUs

Louis Fogel, Hnin Pwint Phyu

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Tags: Computer science, CUDA, nVidia, Security, Tesla K20, Thesis

June 8, 2015 by hgpu

Accelerated Nodal Discontinuous Galerkin Simulations for Reverse Time Migration with Large Clusters

Axel Modave, Amik St-Cyr, Wim A. Mulder, Tim Warburton

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Tags: ATI, ATI Radeon HD 7970, Computational Physics, CUDA, Geophysics, MPI, nVidia, nVidia GeForce GTX 980, OpenCL, Physics, Tesla K20, Tesla K40

June 5, 2015 by hgpu

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

Pall Szilard, Mark James Abraham, Carsten Kutzner, Berk Hess, Erik Lindahl

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Tags: Algorithms, Biomolecules, Computer science, CUDA, Heterogeneous systems, Molecular dynamics, Molecular simulation, MPI, nVidia, Tesla C2070, Tesla K20

June 5, 2015 by hgpu

Genetically Improved BarraCUDA

W. B. Langdon, Brian Yee Hong Lam

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Tags: Algorithms, Benchmarking, Biology, CUDA, Genomics, nVidia, nVidia GeForce GT 730, Package, Tesla K20, Tesla K40, Tesla K80

June 1, 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

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs

Concurrent Task Execution on the Intel Xeon Phi

Autotuning Tensor Contraction Computations on GPUs

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Automatic Data Layout Optimizations for GPUs

Falcon: A Graph Manipulation Language for Heterogeneous Systems

Automatic Selection of Sparse Matrix Representation on GPUs

Cryptanalysis of the McEliece Cryptosystem on GPGPUs

Accelerated Nodal Discontinuous Galerkin Simulations for Reverse Time Migration with Large Clusters

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

Genetically Improved BarraCUDA

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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