high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia

Compositional Compilation for Sparse, Irregular Data Parallelism

Adam Harries, Michel Steuwer, Murray Cole, Alan Gray, Christophe Dubach

View

Download (PDF)

Tags: Computer science, Data parallelism, nVidia, OpenCL, Sparse matrix, Tesla K40

January 26, 2016 by hgpu

Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

View

Download (PDF)

Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

Heterogeneous (CPU+GPU) Working-set Hash Tables

Ziaul Choudhury, Suresh Purini

View

Download (PDF)

Tags: Computer science, CUDA, Hashing, Heterogeneous systems, nVidia, Tesla K20

January 22, 2016 by hgpu

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

Alexander Matz, Mark Hummel, Holger Froning

View

Download (PDF)

Tags: Computer science, CUDA, LLVM, nVidia, OpenCL, Tesla K80

January 22, 2016 by hgpu

GPU Multisplit

Saman Ashkiani, Andrew Davidson, Ulrich Meyer, John D. Owens

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 750 Ti, Tesla K40

January 22, 2016 by hgpu

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

Mohammed Abdelrahim

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, LSTM, Machine learning, nVidia, nVidia GeForce GTX 770, OpenMP, Thesis

January 19, 2016 by hgpu

A framework for efficient execution on GPU and CPU+GPU systems

Jean-Francois Dollinger

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Thesis

January 19, 2016 by hgpu

LHCb GPU acceleration project

A. Badalov, D. Campora, N. Neufeld, X. Vilasis-Cardona

View

Download (PDF)

Tags: CUDA, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 680, Physics

January 16, 2016 by hgpu

Homomorphic Autocomplete

Gizem S. Cetin, Wei Dai, Yarkin Doroz, Berk Sunar

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 690, Security

January 16, 2016 by hgpu

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

Marco Cali, Valeria Di Mauro

View

Download (PDF)

Tags: CUDA, Edge detection, Image processing, nVidia, nVidia GeForce GTX 845 M, OpenGL, Performance

January 16, 2016 by hgpu

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

Issam Said

View

Download (PDF)

Tags: APU, Computer science, Geophysics, Geoscience, GPU cluster, MPI, nVidia, OpenCL, Tesla K40, Thesis

January 16, 2016 by hgpu

Odyssey: A Public GPU-Based Code for General-Relativistic Radiative Transfer in Kerr Spacetime

Hung-Yi Pu, Kiyun Yun, Ziri Younsi, Suk-Jin Yoon

View

Download (PDF)

Source codes

Tags: Astrophysics, CUDA, High Energy Astrophysical Phenomena, MPI, nVidia, nVidia GeForce GTX 780 Ti, Package, Raytracing

January 14, 2016 by hgpu

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

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Compositional Compilation for Sparse, Irregular Data Parallelism

Parallel Explicit FEM Algorithms Using GPU’s

Heterogeneous (CPU+GPU) Working-set Hash Tables

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

GPU Multisplit

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

A framework for efficient execution on GPU and CPU+GPU systems

LHCb GPU acceleration project

Homomorphic Autocomplete

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

Odyssey: A Public GPU-Based Code for General-Relativistic Radiative Transfer in Kerr Spacetime

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

Most viewed papers (last 30 days)