high performance computing on graphics processing units: hgpu.org

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Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 by hgpu

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

Alfred J. Park, Kalyan S. Perumalla

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Tags: Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla X2090

August 20, 2013 by hgpu

GPU Implementation of the DP code

F. Sottile, C. Roedl, V. Slavnic, P. Jovanovic, D. Stankovic, P. Kestener, F. Houssen

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Tags: Computer science, CUBLAS, CUDA, nVidia, Tesla M2090

June 23, 2013 by hgpu

Making the case of GPUs in courses on computational physics

Knut Skogstrand Gjerden

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Tags: Computational Physics, CUBLAS, CUDA, Education, FFT, Mathematical Software, nVidia, nVidia GeForce GTX 320 M, Physics, Tesla C2050

May 17, 2013 by hgpu

Optimizing CUDA Code By Kernel Fusion – Application on BLAS

Jiri Filipovic, Matus Madzin, Jan Fousek, Ludek Matyska

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Tags: BLAS, Code generation, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 480

May 7, 2013 by hgpu

Batched Kronecker product for 2-D matrices and 3-D arrays on NVIDIA GPUs

Chetan Jhurani

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Tags: BLAS, CUBLAS, CUDA, Kronecker product, nVidia, Tesla K20

April 10, 2013 by chetan.jhurani

A GEMM interface and implementation on NVIDIA GPUs for multiple small matrices

Chetan Jhurani, Paul Mullowney

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Tags: BLAS, CUBLAS, CUDA, Dense linear algebra, GEMM, Linear Algebra, nVidia, Parallel programming, Tesla K20

April 9, 2013 by chetan.jhurani

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Boyang Gao, Emmanuel Dellandrea, Liming Chen

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Tags: Clustering, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

March 26, 2013 by hgpu

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Sergio Bernabe, Sergio Sanchez, Antonio Plaza, Sebastian Lopez, Jon Atli Benediktsson, Roberto Sarmiento

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Tags: Algorithms, CUBLAS, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, Tesla C1060

March 26, 2013 by hgpu

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Junjie Lai, Andre Seznec

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 680, Optimization, Performance

February 22, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

Numerical computations in Java with CUDA

Bogdan Oancea, Tudorel Andrei, Andreea Iluzia Iacob

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Tags: Computer science, CUBLAS, CUDA, Java, Linear Algebra, nVidia, nVidia GeForce 9500 GT

January 7, 2013 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

Resource Centered Computing delivering high parallel performance

Efficient Heterogeneous Execution on Large Multicore and Accelerator Platforms: Case Study Using a Block Tridiagonal Solver

GPU Implementation of the DP code

Making the case of GPUs in courses on computational physics

Optimizing CUDA Code By Kernel Fusion – Application on BLAS

Batched Kronecker product for 2-D matrices and 3-D arrays on NVIDIA GPUs

A GEMM interface and implementation on NVIDIA GPUs for multiple small matrices

Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Numerical computations in Java with CUDA

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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