high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Importance-Driven Isosurface Decimation for Visualization of Large Simulation Data Based on OpenCL

Yi Peng, Li Chen, Jun-Hai Yong

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GT 555 M, OpenCL, Visualization

January 12, 2014 by hgpu

GPU-Accelerated parallel FDTD on Distributed Heterogeneous Platform

Ronglin Jiang, Shugang Jiang, Yu Zhang, Ying Xu, Lei Xu, Dandan Zhang

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Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Fortran, Heterogeneous systems, MPI, nVidia, Tesla K20

January 12, 2014 by hgpu

Toward a Generic Hybrid CPU-GPU Parallelization of Divide-and-Conquer Algorithms

Alejandro Lopez-Ortiz, Alejandro Salinger, Robert Suderman

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Tags: Algorithms, ATI, ATI Radeon HD 5970, ATI Radeon HD 6530, Computer science, Heterogeneous systems, Hybrid computing, OpenCL

January 11, 2014 by hgpu

Achieving TeraCUPS on Longest Common Subsequence Problem using GPGPUs

Adnan Ozsoy, Arun Chauhan, Martin Swany

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 690, Sequence alignment, Sequence matching, Tesla C2075, Tesla M2090

January 2, 2014 by hgpu

Developing a High Performance Software Library with MPI and CUDA for Matrix Computations

Bogdan Oancea, Tudorel Andrei

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, Memory model, MPI, nVidia, nVidia GeForce GTX 280

December 29, 2013 by hgpu

Calculation of Stochastic Heating and Emissivity of Cosmic Dust Grains with Optimization for the Intel Many Integrated Core Architecture

Troy A. Porter, Andrey E. Vladimirov

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Tags: Astrophysics, Heterogeneous systems, Instrumentation and Methods for Astrophysics, Intel Xeon Phi

December 29, 2013 by hgpu

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Tetsuya Odajima, Taisuke Boku, Mitsuhisa Sato, Toshihiro Hanawa, Yuetsu Kodama, Raymond Namyst, Samuel Thibault, Olivier Aumage

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Performance, Task scheduling, Tesla M2090

December 25, 2013 by hgpu

Design and Optimization of OpenFOAM-based CFD Applications for Modern Hybrid and Heterogeneous HPC Platforms

Amani AlOnazi

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Tags: Algorithms, Conjugate gradient solver, CUDA, Fluid dynamics, Heterogeneous systems, Laplace and Poisson equation, Linear Algebra, MPI, Numerical simulation, nVidia, Tesla C2050, Thesis

December 21, 2013 by hgpu

Towards global composition of performance-aware components for GPU-based systems

Usman Dastgeer, Christoph Kessler

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Tags: Computer science, CUDA, Flow analysis, Heterogeneous systems, nVidia, Task scheduling, Tesla C2050

December 20, 2013 by hgpu

Heterogeneous Programming with Single Operation Multiple Data

Herve Paulino, Eduardo Marques

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Java, nVidia, nVidia GeForce GT 320 M, Tesla C2050

December 19, 2013 by hgpu

OpenCL Accelerated Multi-GPU Cone-Beam Reconstruction

Marc Kaseberg, Steffen Melnik, Erwin Keeve

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Tags: Algorithms, ATI, ATI Radeon HD 5770, ATI Radeon HD 6970, Computed tomography, CT, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia Quadro 600, OpenCL, Tomography

December 17, 2013 by hgpu

Data Transfer Matters for GPU Computing

Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio, Shinpei Kato, Masato Edahiro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Package, Performance

December 13, 2013 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

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high performance computing on graphics processing units: hgpu.org

Importance-Driven Isosurface Decimation for Visualization of Large Simulation Data Based on OpenCL

GPU-Accelerated parallel FDTD on Distributed Heterogeneous Platform

Toward a Generic Hybrid CPU-GPU Parallelization of Divide-and-Conquer Algorithms

Achieving TeraCUPS on Longest Common Subsequence Problem using GPGPUs

Developing a High Performance Software Library with MPI and CUDA for Matrix Computations

Calculation of Stochastic Heating and Emissivity of Cosmic Dust Grains with Optimization for the Intel Many Integrated Core Architecture

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Design and Optimization of OpenFOAM-based CFD Applications for Modern Hybrid and Heterogeneous HPC Platforms

Towards global composition of performance-aware components for GPU-based systems

Heterogeneous Programming with Single Operation Multiple Data

OpenCL Accelerated Multi-GPU Cone-Beam Reconstruction

Data Transfer Matters for GPU Computing

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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