high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

A Virtual Machine Model for Accelerating Relational Database Joins using a General Purpose GPU

Kevin Angstadt, Ed Harcourt

View

Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 760

February 24, 2015 by hgpu

Accelerating Lagrangian Particle Dispersion in the Atmosphere with OpenCL across Multiple Platforms

Paul Harvey, Saji Hameed, Wim Vanderbauwhede

View

Tags: AMD Radeon R9 290X, ATI, CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, OpenCL, Tesla C2075, Tesla K20, Weather prediction

February 24, 2015 by hgpu

High Performance Computing of Meshless Time Domain Method on Multi-GPU Cluster

Soichiro Ikuno, Susumu Nakata, Yuta Hirokawa, Taku Itoh

View

Tags: CUDA, FDTD, Finite difference, Finite-difference time-domain, GPU cluster, MPI, Numerical simulation, nVidia, Physics, Tesla M2090

February 23, 2015 by hgpu

Document Image Binarization Using Image Segmentation Algorithm in Parallel Environment

Prakash N Ekhande, Sharad A Rumane, Mayur A Ahire

View

Tags: Algorithms, CUDA, Image processing, nVidia, OpenCV

February 23, 2015 by hgpu

Characterising Bipartite Graph Matching Algorithms on GPUs

Stanley Tsang

View

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla K20, Thesis

February 23, 2015 by hgpu

Investigation of the OpenCL SYCL Programming Model

Angelos Trigkas

View

Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Thesis

February 23, 2015 by hgpu

Asynchronous OpenCL/MPI numerical simulations of conservation laws

Philippe Helluy, Thomas Strub, Michel Massaro, Malcolm Roberts

View

Tags: ATI, ATI Radeon HD 7970, MPI, Numerical simulation, nVidia, OpenCL, Physics, Tesla K20

February 23, 2015 by hgpu

Stochastic Gradient Descent on GPUs

Rashid Kaleem, Sreepathi Pai, Keshav Pingali

View

Tags: Algorithms, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla K40

February 22, 2015 by hgpu

High performance methods for frequent pattern mining

Lan Vu

View

Tags: Computer science, CUDA, Data mining, Databases, nVidia, Tesla C2050, Thesis

February 22, 2015 by hgpu

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut

View

Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenCL, Performance, Python, Sparse matrix, Tesla K20

February 22, 2015 by hgpu

QPACE 2 and Domain Decomposition on the Intel Xeon Phi

Paul Arts, Jacques Bloch, Peter Georg, Benjamin Glaessle, Simon Heybrock, Yu Komatsubara, Robert Lohmayer, Simon Mages, Bernhard Mendl, Nils Meyer, Alessio Parcianello, Dirk Pleiter, Florian Rappl, Mauro Rossi, Stefan Solbrig, Giampietro Tecchiolli, Tilo Wettig, Gianpaolo Zanier

View

Tags: Benchmarking, Computational Physics, Computer science, High Energy Physics - Lattice, Intel Xeon Phi

February 22, 2015 by hgpu

RSVDPACK: Subroutines for computing partial singular value decompositions via randomized sampling on single core, multi core, and GPU architectures

Sergey Voronin, Per-Gunnar Martinsson

View

Tags: Algorithms, CUDA, CULA, Mathematical Software, Mathematics, Matrix decomposition, Numerical Analysis, nVidia, Package, Tesla M2070

February 22, 2015 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

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

mt4g: Memory Topology 4 GPUs

MT4G: A Tool for Reliable Auto-Discovery of NVIDIA and AMD GPU Compute and Memory Topologies

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

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

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

See all packages

* * *

* * *

HGPU group © 2010-2025 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: