high performance computing on graphics processing units: hgpu.org

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PATUS: A Code Generation and Autotuning Framework For Parallel Iterative Stencil Computations on Modern Microarchitectures

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, Java, nVidia, Optimization, Package, Tesla C2050

November 21, 2011 by hgpu

Soft Error Resilient QR Factorization for Hybrid System

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Fault tolerance, Hybrid computing, Linear Algebra, nVidia, Tesla C2050, Tesla M2070

November 20, 2011 by hgpu

Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs

Rajib Nath, Stanimire Tomov, Tingxing "Tim" Dong, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package, Performance, Tesla C2050

November 20, 2011 by hgpu

Optimizing the multipole-to-local operator in the fast multipole method for graphical processing units

Toru Takahashi1, Cris Cecka, William Fong, Eric Darve

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Tags: Algorithms, CUDA, Fast multipole method, nVidia, Package, Physics, Tesla C1060, Tesla C2050

November 18, 2011 by hgpu

Dax Toolkit: A Proposed Framework for Data Analysis and Visualization at Extreme Scale

Kenneth Moreland, Utkarsh Ayachit, Berk Geveci, Kwan-Liu Ma

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Tags: Algorithms, Computer science, CUDA, nVidia, Programming techniques, Tesla C2050, Visualization

November 17, 2011 by hgpu

Design of MILC Lattice QCD Application for GPU Clusters

Guochun Shi, Steven Gottlieb, Aaron Torok, Volodymyr Kindratenko

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Tags: Conjugate gradient solver, CUDA, GPU cluster, High Energy Physics - Lattice, High Energy Physics - Phenomenology, nVidia, OpenMPI, Physics, QCD, Tesla C1060, Tesla C2050

November 15, 2011 by hgpu

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Data parallelism, GPU cluster, nVidia, Tesla C2050

November 15, 2011 by hgpu

Large Scale Plane Wave Pseudopotential Density Functional Theory Calculations on GPU Clusters

Long Wang, Weile Jia, Xuebin Chi, Yue Wu, Weiguo Gao, Lin-Wang Wang

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Tags: Algorithms, Computational chemistry, CUDA, GPU cluster, MPI, nVidia, Performance, Physics, Tesla C2050

November 14, 2011 by hgpu

Multi GPU Implementation of the Simplex Algorithm

Mohamed Esseghir Lalami, Didier El-Baz, Vincent Boyer

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Hybrid computing, nVidia, nVidia GeForce GTX 260, Tesla C2050

November 14, 2011 by hgpu

GPU-accelerated power pattern synthesis of aperiodic linear arrays

A. Capozzoli, A. Breglia, C. Curcio, A. Liseno

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Tags: Algorithms, CUDA, Electrodynamics, FFT, nVidia, Tesla C2050

November 14, 2011 by hgpu

Comprehensive Performance Monitoring for GPU Cluster Systems

K. Furlinger, N.J. Wright, D. Skinner

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

November 13, 2011 by hgpu

Efficiently Computing Tensor Eigenvalues on a GPU

Grey Ballard, Tamara Kolda, Todd Plantenga

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Tags: Algorithms, CUDA, Mathematics, nVidia, Tesla C2050

November 12, 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

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high performance computing on graphics processing units: hgpu.org

PATUS: A Code Generation and Autotuning Framework For Parallel Iterative Stencil Computations on Modern Microarchitectures

Soft Error Resilient QR Factorization for Hybrid System

Optimizing Symmetric Dense Matrix-Vector Multiplication on GPUs

Optimizing the multipole-to-local operator in the fast multipole method for graphical processing units

Dax Toolkit: A Proposed Framework for Data Analysis and Visualization at Extreme Scale

Design of MILC Lattice QCD Application for GPU Clusters

GStream: A General-Purpose Data Streaming Framework on GPU Clusters

Large Scale Plane Wave Pseudopotential Density Functional Theory Calculations on GPU Clusters

Multi GPU Implementation of the Simplex Algorithm

GPU-accelerated power pattern synthesis of aperiodic linear arrays

Comprehensive Performance Monitoring for GPU Cluster Systems

Efficiently Computing Tensor Eigenvalues on a GPU

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

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