high performance computing on graphics processing units: hgpu.org

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Distributed Massive Model Rendering

Revanth N R, P. J. Narayanan

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia Quadro FX 3700 M, Rendering, Tesla C2050, Tesla C2070, Tesla S1070

January 8, 2013 by hgpu

CUDA based iterative methods for linear systems

Bogdan Oancea

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

January 7, 2013 by hgpu

Automatic Code Generation for Stencil Computations on GPU Architectures

Justin Andrew Holewinski

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Tesla C2050, Tesla K10, Thesis

January 4, 2013 by hgpu

An Automatic Host and Device Memory Allocation Method for OpenMPC

Hiroaki Uchiyama, Tomoaki Tsumura, Hiroshi Matsuo

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenMP, Performance, Tesla C1060

December 20, 2012 by hgpu

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Shoaib Ashraf Kamil

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 16, 2012 by hgpu

Image Processing using Parallel Computing

Mohamed Khalifa

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Tags: Cluster computing, CUDA, Image processing, MPI, nVidia, nVidia GeForce GTX 280

December 15, 2012 by hgpu

Improving the Performance of the Linear Systems Solvers Using CUDA

Bogdan Oancea, Tudorel Andrei, Raluca Mariana Dragoescu

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 280

November 24, 2012 by hgpu

Auto-tuning on the macro scale: high level algorithmic auto-tuning for scientific applications

Cy P Chan

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Tags: Algorithms, Code generation, Computer science, nVidia, nVidia GeForce GTX 280, Optimization, Thesis

November 23, 2012 by hgpu

High Dimensional Spaces and Modelling in the task of Speaker Recognition

Lukas Machlica

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Tags: Acoustics, CUDA, nVidia, nVidia GeForce GTX 280, Signal processing, Speech recognition, Thesis

November 15, 2012 by hgpu

SPH Based Fluid Animation Using CUDA Enabled GPU

Uday A. Nuli, P. J. Kulkarni

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GTX 280

November 8, 2012 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 by hgpu

Characterization and Exploitation of GPU Memory Systems

Kenneth Sydney Lee

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Tags: AMD Fusion, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, Memory model, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla C2075, Thesis

October 30, 2012 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

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high performance computing on graphics processing units: hgpu.org

Distributed Massive Model Rendering

CUDA based iterative methods for linear systems

Automatic Code Generation for Stencil Computations on GPU Architectures

An Automatic Host and Device Memory Allocation Method for OpenMPC

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

Image Processing using Parallel Computing

Improving the Performance of the Linear Systems Solvers Using CUDA

Auto-tuning on the macro scale: high level algorithmic auto-tuning for scientific applications

High Dimensional Spaces and Modelling in the task of Speaker Recognition

SPH Based Fluid Animation Using CUDA Enabled GPU

GPU Virtualization

Characterization and Exploitation of GPU Memory Systems

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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