high performance computing on graphics processing units: hgpu.org

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Finite Volume Errors in B_K

Jangho Kim, Hyung-Jin Kim, Weonjong Lee, Chulwoo Jung, Stephen R. Sharpe

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Tags: CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 480, Physics

November 2, 2011 by hgpu

Multi GPU Performance of Conjugate Gradient Solver with Staggered Fermions in Mixed Precision

Yong-Chull Jang, Hyung-Jin Kim, Weonjong Lee

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Tags: Algorithms, Cg, Computational Physics, Conjugate gradient solver, CUDA, High Energy Physics - Lattice, Mixed precision, nVidia, nVidia GeForce GTX 480, Physics

November 2, 2011 by hgpu

Optimal Control of the Process Systems Using Graphic Processing Unit

Arash Sadrieh, Parisa A. Bahri

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

October 31, 2011 by hgpu

Rapid Performance of a Generalized Distance Calculation

Scott Fisackerly, Eric Chu, David L. Foster

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C1060

October 31, 2011 by hgpu

Fast Speaker Diarization Using a High-Level Scripting Language

Ekaterina Gonina, Gerald Friedland, Henry Cook, Kurt Keutzer

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Tags: Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Python, Speech recognition

October 31, 2011 by hgpu

Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

Alin Murarasu, Josef Weidendorfer, Arndt Bode

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Tags: Compression, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Task scheduling, Tesla C2050

October 31, 2011 by hgpu

High-performance software rasterization on GPUs

Samuli Laine, Tero Karras

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Source codes

Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Rasterization

October 31, 2011 by hgpu

Efficient Implementation of the eta_T Pairing on GPU

Yosuke Katoh, Yun-Ju Huang, Chen-Mou Cheng, Tsuyoshi Takagi

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Security, Tesla C1060, Tesla C2050

October 30, 2011 by hgpu

Using GPUs to Accelerate Installed Antenna Performance Simulations

Tod Courtney, John E. Stone, Bob Kipp

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Tags: CUDA, Electrodynamics, nVidia, nVidia GeForce GTX 480, Raytracing

October 29, 2011 by hgpu

Techniques to maximize memory bandwidth on the Rigel compute accelerator

William J. Tuohy

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Tags: ATI, ATI Radeon HD 5870, Computer science, Memory, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10, Thesis

October 27, 2011 by hgpu

A Memory Efficient and Fast Sparse Matrix Vector Product on a GPU

A. Dziekonski, A. Lamecki, M. Mrozowski

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Tags: Computer science, CUDA, Electrodynamics, FEM, Finite element method, nVidia, nVidia GeForce GTX 480, Performance, Sparse matrix

October 26, 2011 by hgpu

Hand Tracking based on Hierarchical Clustering of Range Data

Roberto Cespi, Andreas Kolb, Marvin Lindner

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Tags: Algorithms, Clustering, Computer science, Computer vision, Hierarchical clustering, nVidia, nVidia GeForce GTX 480, Pattern recognition

October 26, 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

Finite Volume Errors in B_K

Multi GPU Performance of Conjugate Gradient Solver with Staggered Fermions in Mixed Precision

Optimal Control of the Process Systems Using Graphic Processing Unit

Rapid Performance of a Generalized Distance Calculation

Fast Speaker Diarization Using a High-Level Scripting Language

Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation

High-performance software rasterization on GPUs

Efficient Implementation of the eta_T Pairing on GPU

Using GPUs to Accelerate Installed Antenna Performance Simulations

Techniques to maximize memory bandwidth on the Rigel compute accelerator

A Memory Efficient and Fast Sparse Matrix Vector Product on a GPU

Hand Tracking based on Hierarchical Clustering of Range Data

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)