high performance computing on graphics processing units: hgpu.org

hgpu.org » CUDA

Parallel Worldline Numerics: Implementation and Error Analysis

Dan Mazur, Jeremy S. Heyl

View

Download (PDF)

Tags: CUDA, High Energy Physics - Theory, nVidia, Physics, Tesla C1060

July 29, 2014 by hgpu

Mixed-precision orthogonalization scheme and its case studies with CA-GMRES on a GPU

Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Mixed precision, nVidia, Tesla K20, Tesla K40, Tesla M2090

July 29, 2014 by hgpu

GPU Computing to Improve Game Engine Performance

Abu Asaduzzaman, Hin Y. Lee

View

Download (PDF)

Tags: Computer science, CUDA, Data parallelism, Games, Image processing, nVidia, nVidia GeForce 8800 GTX, Performance

July 28, 2014 by hgpu

Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the System

Chaitanya P. Chandgude, P. M. Chawan

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, nVidia

July 28, 2014 by hgpu

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Albert Saa-Garriga, David Castells-Rufas, Jordi Carrabina

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2075, Tesla K20, Tesla M2050

July 28, 2014 by hgpu

Understanding the ISA impact on GPU Architecture

Mayank Vinodbhai Kothiya

View

Download (PDF)

Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, PTX, Tesla, Thesis

July 28, 2014 by hgpu

Agent-based crowd simulation using GPU computing

Sean Patrick O'Reilly

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Rendering, Thesis

July 28, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

Brian Hamilton, Stefan Bilbao, Craig J. Webb

View

Download (PDF)

Tags: Acoustics, CUDA, Finite difference, Navier-Stokes equations, NSEs, nVidia, Physics, Tesla K20, Wave equation

July 28, 2014 by hgpu

CUDT: A CUDA Based Decision Tree Algorithm

Win-Tsung Lo, Yue-Shan Chang, Ruey-Kai Sheu, Chun-Chieh Chiu, Shyan-Ming Yuan

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 9800 GT

July 28, 2014 by hgpu

Towards fast and certified multiple-precision libraries

Valentina Popescu

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Extended precision, nVidia, Tesla C2075, Thesis

July 26, 2014 by hgpu

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

S.A. Arul Shalom, Manoranjan Dash

View

Download (PDF)

Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 8800 GTS

July 26, 2014 by hgpu

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

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Parallel Worldline Numerics: Implementation and Error Analysis

Mixed-precision orthogonalization scheme and its case studies with CA-GMRES on a GPU

GPU Computing to Improve Game Engine Performance

Ship Detection from SAR Imagery Using CUDA and Performance Analysis of the System

OMP2HMPP: HMPP Source Code Generation from Programs with Pragma Extensions

Understanding the ISA impact on GPU Architecture

Agent-based crowd simulation using GPU computing

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Improved Finite Difference Schemes for a 3-D Viscothermal Wave Equation on a GPU

CUDT: A CUDA Based Decision Tree Algorithm

Towards fast and certified multiple-precision libraries

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

Most viewed papers (last 30 days)