high performance computing on graphics processing units: hgpu.org

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Effect And Analysis of Elastic Fidelity Computing On GPUs

Chetan Arvind Patil, Georgios Tziantzioulis, Nikos Hardavellas

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, nVidia, nVidia GeForce GTX 480, OpenCL

June 26, 2014 by hgpu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

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Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 2014 by hgpu

A Case Against Small Data Types on GPGPUs

Ahmad Lashgar, Amirali Baniasadi

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance

June 18, 2014 by hgpu

GPU Implementation of Bayesian Neural Network Construction for Data-Intensive Applications

Michelle Perry, Harrison B. Prosper, Anke Meyer-Baese

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Tags: Bayesian, CUDA, Neural networks, nVidia, nVidia GeForce GTX 480, Physics, Review

June 17, 2014 by hgpu

GPPE: a GPU-based Parallel Processing Environment for Large Scale Concurrent Data Streams

Jianwei Cao, Qingkui Chen, Songlin Zhuang

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Tags: Cloud, Clustering, Computer science, CUDA, GPU cluster, H.264/AVC, MPI, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480

June 12, 2014 by hgpu

Intersecting two families of sets on the GPU

Marta Fort, J. Antoni Sellares, Nacho Valladares

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480

June 11, 2014 by hgpu

GASPP: A GPU-Accelerated Stateful Packet Processing Framework

Giorgos Vasiliadis, Lazaros Koromilas, Michalis Polychronakis, Sotiris Ioannidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Security

May 26, 2014 by hgpu

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

Andrea Manconi, Alessandro Orro, Emanuele Manca, Giuliano Armano, Luciano Milanesi

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Source codes

Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 480, Package, Python, Sequence alignment, Tesla K10, Tesla K20

May 25, 2014 by hgpu

An Extensible Component-based Approach to Simulation Systems on Heterogeneous Clusters

Roger Viet Hoang

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570, Performance, Tesla C2050, Thesis, Virtual reality

May 23, 2014 by hgpu

A Comparison of Massively Parallel Programming Models Through Applications in Sound Propagation and Jitter Measurement

Torbjorn Panton Loken

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Tags: Acoustics, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenGL, Thesis, Thrust

May 23, 2014 by hgpu

Vector Quantization: A Many-Core Approach

Rita Silva, Telmo Marques, Jorge Desirat, Patricio Domingues

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Vector quantization

May 21, 2014 by hgpu

A performance/cost evaluation for a GPU-based drug discovery application on volunteer computing

Gines David Guerrero Hernandez, Baldomero Imbernon, Horacio Perez-Sanchez, Francisco Sanz, Jose M. Garcia, Jose M. Cecilia

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Tags: Bioinformatics, Biology, CUDA, Medicine, nVidia, nVidia GeForce 7300 GT, nVidia GeForce GTX 465, nVidia GeForce GTX 480, nVidia GeForce GTX 590, Tesla C2070, Tesla K20

May 21, 2014 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Effect And Analysis of Elastic Fidelity Computing On GPUs

Feature Generation for Quantification of Visual Similarity

A Case Against Small Data Types on GPGPUs

GPU Implementation of Bayesian Neural Network Construction for Data-Intensive Applications

Intersecting two families of sets on the GPU

GASPP: A GPU-Accelerated Stateful Packet Processing Framework

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

An Extensible Component-based Approach to Simulation Systems on Heterogeneous Clusters

A Comparison of Massively Parallel Programming Models Through Applications in Sound Propagation and Jitter Measurement

Vector Quantization: A Many-Core Approach

A performance/cost evaluation for a GPU-based drug discovery application on volunteer computing

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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