high performance computing on graphics processing units: hgpu.org

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Returning control to the programmer: SIMD intrinsics for virtual machines

Jonathan Parri, Daniel Shapiro, Miodrag Bolic, Voicu Groza

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Tags: Computer science, Java, Optimization, Programming Languages

September 16, 2011 by hgpu

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Amol Ghoting, Prabhanjan Kambadur, Edwin Pednault, Ramakrishnan Kannan

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Tags: Algorithms, Computer science, Data mining, Machine learning, MapReduce, MPI, OpenCL, Performance, Software Engineering

September 16, 2011 by hgpu

Programmable and Scalable Architecture for Graphics Processing Units

Carlos S. de La Lama, Pekka Jaaskelainen, Jarmo Takala

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Tags: Computer science, GLSL, nVidia, nVidia GeForce 9400 M, OpenCL, OpenGL, Performance, Programming techniques

September 16, 2011 by hgpu

Searching for Concurrent Design Patterns in Video Games

Micah J. Best, Alexandra Fedorova, Ryan Dickie, Andrea Tagliasacchi, Alex Couture-Beil, Craig Mustard, Shane Mottishaw, Aron Brown, Zhi Feng Huang, Xiaoyuan Xu, Nasser Ghazali, Andrew Brownsword

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Tags: Algorithms, Computer science, Games, Performance

September 16, 2011 by hgpu

A Light-Weight Approach to Dynamical Runtime Linking Supporting Heterogenous, Parallel, and Reconfigurable Architectures

Rainer Buchty, David Kramer, Mario Kicherer, Wolfgang Karl

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Tags: Algorithms, Computer science, Heterogeneous systems, Programming techniques

September 16, 2011 by hgpu

Optimizations and Performance of a Robotics Grasping Algorithm Described in Geometric Algebra

Florian Worsdorfer, Florian Stock, Eduardo Bayro-Corrochano, Dietmar Hildenbrand

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Source codes

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Optimization, Package, Performance

September 16, 2011 by hgpu

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

Maraike Schellmann, Sergei Gorlatch, Dominik Meilander, Thomas Kosters, Klaus Schafers, Frank Wubbeling, Martin Burger

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Tags: Algorithms, Cell processor, Grid, Image reconstruction, Medicine, PET, PET scanning, Tomography

September 16, 2011 by hgpu

A Generic Approach to Topic Models

Gregor Heinrich

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Tags: Algorithms, Bayesian, Computer science

September 16, 2011 by hgpu

Implicit and dynamic trees for high performance rendering

Nathan Andrysco, Xavier Tricoche

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 480, Raytracing, Rendering

September 16, 2011 by hgpu

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Xun Jia, Hao Yan, Xuejun Gu, Steve B. Jiang

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Tags: Computed tomography, CT, CUDA, Heterogeneous systems, Medical Physics, Medicine, Monte Carlo simulation, nVidia, Physics, Tesla C2050, Tomography

September 16, 2011 by hgpu

Analytical motion blur rasterization with compression

Carl Johan Gribel, Michael Doggett, Tomas Akenine-Moller

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Tags: Algorithms, Compression, Image processing, Performance, Rasterization

September 15, 2011 by hgpu

Processing data streams with hard real-time constraints on heterogeneous systems

Uri Verner, Assaf Schuster, Mark Silberstein

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Tags: AES, Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Performance, Security, Task scheduling

September 15, 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

Applications

Returning control to the programmer: SIMD intrinsics for virtual machines

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Programmable and Scalable Architecture for Graphics Processing Units

Searching for Concurrent Design Patterns in Video Games

A Light-Weight Approach to Dynamical Runtime Linking Supporting Heterogenous, Parallel, and Reconfigurable Architectures

Optimizations and Performance of a Robotics Grasping Algorithm Described in Geometric Algebra

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

A Generic Approach to Topic Models

Implicit and dynamic trees for high performance rendering

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Analytical motion blur rasterization with compression

Processing data streams with hard real-time constraints on heterogeneous systems

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

Most viewed papers (last 30 days)