high performance computing on graphics processing units: hgpu.org

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Solving diffractive optics problems using graphics processing units

D. L. Golovashkin, N. L. Kasanskiy

Tags: Algorithms, ATI, ATI FireStream, Brook, Cg, CUDA, FDTD, Finite-difference time-domain, nVidia, OpenGL, Optics, Overview, Physics, Raytracing, Review

September 11, 2011 by hgpu

Enabling multiple accelerator acceleration for Java/OpenMP

Ronald Veldema, Thorsten Blass, Michael Philippsen

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Tags: Benchmarking, Computer science, CUDA, Java, nVidia, OpenCL, OpenMP, OpenMPI, Tesla M1060

September 9, 2011 by hgpu

CUDACS: securing the cloud with CUDA-enabled secure virtualization

Flavio Lombardi, Roberto Di Pietro

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Tags: Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8400 M, nVidia GeForce GT 220, Security, Virtualization

September 9, 2011 by hgpu

Experiences with Mapping Non-linear Memory Access Patterns into GPUs

Eladio Gutierrez, Sergio Romero, Maria A. Trenas, Oscar Plata

Tags: Computer science, CUDA, Memory, nVidia, Optimization, Programming techniques

September 8, 2011 by hgpu

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

Florian Stock, Andreas Koch

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Tags: Cell processor, Conjugate gradient solver, CUDA, FPGA, Image processing, Image reconstruction, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, Optimization, Sparse matrix

September 8, 2011 by hgpu

Programming Many-Core Chips

Andras Vajda

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Programming techniques

September 8, 2011 by hgpu

GPU Computation in Bioinspired Algorithms: A Review

M. G. Arenas, A. M. Mora, G. Romero and P. A. Castillo

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Tags: Algorithms, ATI, Bioinformatics, Biology, Computational biology, CUDA, nVidia, OpenCL, Overview, Review

September 8, 2011 by hgpu

Towards GPGPU Assisted Computing in Virtualized Environments

Thilo Schmitt, Alexander Weggerle, Christian Himpel, Peter Schulthess

Tags: ATI, ATI Stream, Computer science, CUDA, nVidia, OpenCL, Review, Virtualization

September 8, 2011 by hgpu

Implementing Independent Component Analysis in General-Purpose GPU Architectures

Jacquelyne Forgette, Renata Wachowiak-Smolikova, Mark Wachowiak

Tags: Algorithms, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 260, OpenCL, Signal processing

September 8, 2011 by hgpu

Pegasus: coordinated scheduling for virtualized accelerator-based systems

Vishakha Gupta, Karsten Schwan, Niraj Tolia, Vanish Talwar, Parthasarathy Ranganathan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GTX, Operating systems, Task scheduling, Virtualization

September 7, 2011 by hgpu

Automatic CPU-GPU communication management and optimization

Thomas B. Jablin, Prakash Prabhu, James A. Jablin, Nick P. Johnson, Stephen R. Beard, David I. August

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Programming techniques

September 7, 2011 by hgpu

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

John E. Stone, Jan Saam, David J. Hardy, Kirby L. Vandivort, Wen-mei W. Hwu, Klaus Schulten

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Tags: Algorithms, Chemistry, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, Programming techniques, Rendering, Visualization

September 7, 2011 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

Solving diffractive optics problems using graphics processing units

Enabling multiple accelerator acceleration for Java/OpenMP

Experiences with Mapping Non-linear Memory Access Patterns into GPUs

A Fast GPU Implementation for Solving Sparse Ill-Posed Linear Equation Systems

Programming Many-Core Chips

GPU Computation in Bioinspired Algorithms: A Review

Towards GPGPU Assisted Computing in Virtualized Environments

Implementing Independent Component Analysis in General-Purpose GPU Architectures

Pegasus: coordinated scheduling for virtualized accelerator-based systems

Automatic CPU-GPU communication management and optimization

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

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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