high performance computing on graphics processing units: hgpu.org

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A Qualitative Comparison Study Between Common GPGPU Frameworks

Adam Soderstrom

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Tags: Computer science, CUDA, DirectCompute, DirectX, N-body simulation, nVidia, nVidia GeForce GTX 1050, OpenCL, Thesis

August 26, 2018 by hgpu

GPU Pro 7: Advanced Rendering

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, nVidia, OpenGL, Package, Rendering, Visualization

November 26, 2017 by hgpu

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Torbjorn Sorman

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Tags: AMD Radeon R7 260X, ATI, Benchmarking, Computer science, DirectCompute, DirectX, nVidia, nVidia GeForce GTX 670, OpenCL, OpenGL, Performance, Thesis

March 22, 2016 by hgpu

GPU Pro 6: Advanced Rendering Techniques

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, Games, nVidia, OpenCL, OpenGL, Rendering, Visualization

August 12, 2015 by hgpu

Supporting Iteration in a Heterogeneous Data Flow Engine

Jon Currey, Simon Baker, Christopher J. Rossbach

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Tags: Algorithms, Computer science, Computer vision, DirectCompute, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 580, Optical flow

April 18, 2013 by hgpu

Volume Raycasting Performance Using DirectCompute

Hakan Johansson

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Tags: Algorithms, ATI, ATI Radeon HD 5850, Computer science, DirectCompute, DirectX, Medicine, Rendering, Thesis, Tomography

March 18, 2013 by hgpu

High-precision molecular dynamics simulation of UO2-PuO2: Anion self-diffusion in UO2

S.I. Potashnikov, A.S. Boyarchenkov, K.A. Nekrasov, A.Ya. Kupryazhkin

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Tags: Condensed matter, CUDA, DirectCompute, HLSL, Materials Science, Molecular dynamics, nVidia, Package

June 21, 2012 by hgpu

GPGPU Processing in CUDA Architecture

Jayshree Ghorpade, Jitendra Parande, Madhura Kulkarni, Amit Bawaskar

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Tags: Computer science, CUDA, Data parallelism, DirectCompute, nVidia, OpenCL, Review

February 21, 2012 by hgpu

Practical examples of GPU computing optimization principles

Goorts, Patrik; Rogmans, Sammy; Vanden Eynde, Steven; Bekaert, Philippe;

Tags: Computer science, CUDA, DirectCompute, nVidia, OpenCL, Programming techniques

April 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

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high performance computing on graphics processing units: hgpu.org

A Qualitative Comparison Study Between Common GPGPU Frameworks

GPU Pro 7: Advanced Rendering

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

GPU Pro 6: Advanced Rendering Techniques

Supporting Iteration in a Heterogeneous Data Flow Engine

Volume Raycasting Performance Using DirectCompute

High-precision molecular dynamics simulation of UO2-PuO2: Anion self-diffusion in UO2

GPGPU Processing in CUDA Architecture

Practical examples of GPU computing optimization principles

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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