high performance computing on graphics processing units: hgpu.org

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Co-processor acceleration of an unmodified parallel solid mechanics code with FEASTGPU

Dominik Goddeke, Hilmar Wobker, Robert Strzodka, Jamaludin Mohd-Yusof, Patrick McCormick, Stefan Turek

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Tags: CUDA, Finite element method, Heterogeneous systems, MPI, nVidia, nVidia Quadro FX 5600, Physics

March 1, 2011 by hgpu

Efficient Finite Element Geometric Multigrid Solvers for Unstructured Grids on GPUs

Markus Geveler, Dirk Ribbrock, Dominik Goddeke, Peter Zajac, Stefan Turek

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Tags: Cell processor, CUDA, Finite element method, Fluid dynamics, GPU cluster, MPI, nVidia, nVidia GeForce GTX 285, Package

March 1, 2011 by hgpu

Performance and accuracy of Lattice-Boltzmann kernels on multi- and manycore architectures

Dirk Ribbrock, Markus Geveler, Dominik Goddeke, Stefan Turek

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Tags: Cell processor, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Package

March 1, 2011 by hgpu

Lattice-Boltzmann Simulation of the Shallow-Water Equations with Fluid-Structure Interaction on Multi- and Manycore Processors

Markus Geveler, Dirk Ribbrock, Dominik Goddeke, and Stefan Turek

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Tags: Cell processor, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Package

March 1, 2011 by hgpu

A Simulation Suite for Lattice-Boltzmann based Real-Time CFD Applications Exploiting Multi-Level Parallelism on modern Multi- and Many-Core Architectures

Markus Geveler, Dirk Ribbrock, Sven Mallach, Dominik Goddeke

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Tags: Cell processor, CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Package

March 1, 2011 by hgpu

HORIZON: Accelerated General Relativistic Magnetohydrodynamics

Burkhard Zink

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Tags: Computational Physics, CUDA, General Relativity and Quantum Cosmology, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, nVidia, nVidia GeForce GTX 580, Tesla C2070

February 28, 2011 by hgpu

Handbook of open source tools

Sandeep Koranne

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, Pthreads

February 26, 2011 by hgpu

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Dana A. Jacobsen, Julien C. Thibault, Inanc Senocak

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Tags: CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Tesla C1060, Tesla C870, Tesla S1070, Tesla S870

February 24, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm

David Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, MPI, nVidia, Stochastic simulation, Tesla C870

February 21, 2011 by hgpu

Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

Kenneth P. Esler, Jeongnim Kim, David M. Ceperley

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Tags: CUDA, GPU cluster, Monte Carlo simulation, MPI, nVidia, Package, Physics, QMC, Tesla T10

February 18, 2011 by hgpu

Accelerating Cosmological Data Analysis with Graphics Processors

Dylan W. Roeh, Volodymyr V. Kindratenko, Robert J. Brunner

Tags: Astrophysics, Cosmology, CUDA, GPU cluster, MPI, nVidia, Physics, Programming techniques

February 15, 2011 by hgpu

Auto-Generation of Parallel Finite-Differencing Code for MPI, TBB and CUDA

D. P. Playne, K. A. Hawick

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Tags: Code generation, Computer science, CUDA, Finite difference, MPI, nVidia, nVidia GeForce GTX 480

February 13, 2011 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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

See all packages

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high performance computing on graphics processing units: hgpu.org

Co-processor acceleration of an unmodified parallel solid mechanics code with FEASTGPU

Efficient Finite Element Geometric Multigrid Solvers for Unstructured Grids on GPUs

Performance and accuracy of Lattice-Boltzmann kernels on multi- and manycore architectures

Lattice-Boltzmann Simulation of the Shallow-Water Equations with Fluid-Structure Interaction on Multi- and Manycore Processors

A Simulation Suite for Lattice-Boltzmann based Real-Time CFD Applications Exploiting Multi-Level Parallelism on modern Multi- and Many-Core Architectures

HORIZON: Accelerated General Relativistic Magnetohydrodynamics

Handbook of open source tools

An MPI-CUDA Implementation for Massively Parallel Incompressible Flow Computations on Multi-GPU Clusters

Accelerating the Stochastic Simulation Algorithm

Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

Accelerating Cosmological Data Analysis with Graphics Processors

Auto-Generation of Parallel Finite-Differencing Code for MPI, TBB and CUDA

Recent source codes

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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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