high performance computing on graphics processing units: hgpu.org

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PARIS: A Parallel RSA-Prime Inspection Tool

Joseph White

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, RSA, Security, Tesla K20, Thesis

August 19, 2013 by hgpu

Fast and Flexible: Parallel Packet Processing with GPUs and Click

Weibin Sun, Robert Ricci

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Software router, String matching

August 18, 2013 by hgpu

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

Benedikt Waldvogel

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Tags: Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, Package, Tesla K20, Thesis

August 16, 2013 by hgpu

The Yin and Yang of Processing Data Warehousing Queries on GPU Devices

Yuan Yuan, Rubao Lee, Xiaodong Zhang

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Tags: Analytical model, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package

August 14, 2013 by hgpu

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

Christian Schulz, Geir Hasle, Andre R. Brodtkorb, Trond R. Hagen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Andre R. Brodtkorb, Trond R. Hagen, Christian Schulz, Geir Hasley

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

Exploring Microcontrollers in GPUs

Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio, Shinpei Kato

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce GTX 480

August 7, 2013 by hgpu

Fast Morphological Image Processing on GPU using CUDA

Mugdha A. Rane

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 480, Thesis

August 7, 2013 by hgpu

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

C. Ouwehand, P. Hijma, W.J. Fokkink

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Tags: Computer science, CUDA, Haskell, Matrix multiplication, nVidia, nVidia GeForce GTX 480

August 6, 2013 by hgpu

Real-Time Electroholography Using a Multi-GPU Environmental PC

Naoki Takada, Hiroaki Niwase, Hiromitsu Araki, Hirotaka Nakayama, Atsushi Sugiyama, Takashi Kakue, Tomoyoshi Shimobaba, Tomoyoshi Ito

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Tags: Computer holography, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenGL

August 2, 2013 by hgpu

NOVA: A Functional Language for Data Parallelism

Alexander Collins, Dominik Grewe, Vinod Grover, Sean Lee, Adriana Susnea

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Tags: Compilers, Computer science, CUDA, Data parallelism, High-level Languages, nVidia, nVidia GeForce GTX 480

August 1, 2013 by hgpu

Real-time 3D semi-local surface patch extraction using GPGPU

Sergio Orts-Escolano, Vicente Morell, Jose Garcia-Rodriguez, Miguel Cazorla, Robert B. Fisher

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTX 480

July 29, 2013 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

PARIS: A Parallel RSA-Prime Inspection Tool

Fast and Flexible: Parallel Packet Processing with GPUs and Click

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

The Yin and Yang of Processing Data Warehousing Queries on GPU Devices

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Exploring Microcontrollers in GPUs

Fast Morphological Image Processing on GPU using CUDA

GPU Programming in Functional Languages: A Comparison of Haskell GPU Embedded Domain Specific Languages

Real-Time Electroholography Using a Multi-GPU Environmental PC

NOVA: A Functional Language for Data Parallelism

Real-time 3D semi-local surface patch extraction using GPGPU

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)