high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Bonsai: A GPU Tree-Code

Jeroen Bedorf, Evghenii Gaburov, Simon Portegies Zwart

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, MPI, N-body simulation, nVidia, nVidia GeForce GTX 480, Package

April 12, 2012 by hgpu

Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods

Nathan Bell, Steven Dalton, Luke N. Olson

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Tags: Algorithms, CUDA, Mathematics, nVidia, Package, Sparse matrix, Tesla C2050

April 11, 2012 by hgpu

Dynamic Programming with CUDA – Part II

Robert Hochberg

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Tags: Algorithms, Computer science, CUDA, Distributed computing, nVidia, Package, Review

April 10, 2012 by hgpu

Tiled Shading

Ola Olsson, Ulf Assarsson

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, GLSL, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenGL, Package

April 9, 2012 by hgpu

Efficient computational noise in GLSL

Ian McEwan, David Sheets, Stefan Gustavson, Mark Richardson

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Tags: 3D Graphics and Realism, ATI, ATI Radeon HD 3650, ATI Radeon HD 4850, ATI Radeon HD 5870, Computer science, GLSL, nVidia, nVidia GeForce 7600 GS, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package

April 9, 2012 by hgpu

An Efficient Parallel GPU Evaluation of Small Angle X-Ray Scattering Profiles

Lubomir D. Antonov, Christian Andreetta, Thomas Hamelryck

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Tags: Algorithms, Medicine, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Package

April 7, 2012 by hgpu

A High-Performance Brownian Bridge for GPUs: Lessons for Bandwidth Bound Applications

Jacques Du Toit

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Tags: Computer science, CUDA, nVidia, Package, Pseudo-random number generators, Tesla C2050

April 4, 2012 by hgpu

Nested Data-Parallelism on the GPU

Lars Bergstrom, John Reppy

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Tags: Algorithms, Compilers, Computer science, CUDA, Data parallelism, nVidia, Package, Programming Languages, Tesla C2050

March 31, 2012 by hgpu

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

Weibin Sun, Robert Ricci, Matthew L. Curry

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Tags: Computer science, CUDA, Data recovery, nVidia, nVidia GeForce GTX 480, Package, Security, Storage system

March 26, 2012 by hgpu

Multi-platform Linear Algebra

E. Ketelaer, D. Lukarski

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Tags: Computer science, CUDA, Differential equations, Distributed data structures, Linear Algebra, nVidia, Package, Partial differential equations, PDEs

March 16, 2012 by hgpu

Performance analysis and optimization of the OP2 framework on many-core architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, nVidia, OpenMP, Optimization, Package, Performance, Tesla C2050

March 15, 2012 by hgpu

A Spiking Neural P system simulator based on CUDA

Francis Cabarle, Henry Adorna, Miguel A. Martinez-del-Amor

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Tags: Algorithms, Computer science, CUDA, Membrane computing, nVidia, nVidia GeForce 9400 M, Package

March 15, 2012 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

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high performance computing on graphics processing units: hgpu.org

Applications

Bonsai: A GPU Tree-Code

Exposing Fine-Grained Parallelism in Algebraic Multigrid Methods

Dynamic Programming with CUDA – Part II

Tiled Shading

Efficient computational noise in GLSL

An Efficient Parallel GPU Evaluation of Small Angle X-Ray Scattering Profiles

A High-Performance Brownian Bridge for GPUs: Lessons for Bandwidth Bound Applications

Nested Data-Parallelism on the GPU

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

Multi-platform Linear Algebra

Performance analysis and optimization of the OP2 framework on many-core architectures

A Spiking Neural P system simulator based on CUDA

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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