high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Locality Analysis for Characterizing Applications Based on Sparse Matrices

Noboru Tanabe, Sonoko Tomimori, Masami Takata, Kazuki Joe

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

December 9, 2013 by hgpu

Dense Real-Time Mapping of Object-Class Semantics from RGB-D Video

Jorg Stuckler, Benedikt Waldvogel, Hannes Schulz, Sven Behnke

View

Download (PDF)

Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 675 M, nVidia GeForce GTX Titan

December 9, 2013 by hgpu

Advanced ultrasound beam forming using GPGPU technology

Yannick van Bavel

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 660 Ti, Thesis, Ultrasound

December 9, 2013 by hgpu

Partial Parallelization of the Successive Projections Algorithm using Compute Unified Device Architecture

Lauro Cassio Martins de Paula, Anderson da Silva Soares, Telma Woerle de Lima, Wellington Santos Martins, Arlindo Rodrigues Galvao Filho, Clarimar Jose Coelho

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 550 Ti

December 8, 2013 by hgpu

A GPU-based Multiresolution Pipeline for Compressed Volume Rendering

Julian Lamas-Rodriguez, Francisco Arguello, Dora B. Heras

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Rendering, Visualization

December 8, 2013 by hgpu

Waste Not… Efficient Co-Processing of Relational Data

Holger Pirk, Stefan Manegold, Martin Kersten

View

Download (PDF)

Tags: Algorithms, Computer science, Databases, nVidia, nVidia GeForce GTX 680, OpenCL

December 8, 2013 by hgpu

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

Alexander Schluter, Adrian Willenbucher, Charlotte Kuhn

View

Download (PDF)

Tags: Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla C2075

December 8, 2013 by hgpu

A Distributed Data Mining Framework Accelerated with Graphics Processing Units

Nam-Luc Tran, Quentin Dugauthier, Sabri Skhiri

View

Download (PDF)

Tags: Clustering, Computer science, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, Tesla K20

December 6, 2013 by hgpu

A Quantitative Comparison of Emulated Shared Memory Architectures to Current Multicore CPUs and GPUs

Erik Hansson, Erik Alnervik, Christoph Kessler, Martti Forsell

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance, Tesla M2050

December 6, 2013 by hgpu

Parallel tree-ensemble algorithms for GPUs using CUDA

Karl Jansson, Hakan Sundell, Henrik Bostrom

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Tesla K20

December 6, 2013 by hgpu

Speeding up the small progress measures algorithm for parity games using the GPU

P.J.A. Bootsma

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GT 555 M, nVidia GeForce GTX 660 Ti, Thesis

December 6, 2013 by hgpu

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Ricardo Javier Barrientos Rojel

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Search strategies, Tesla C1060, Tesla M2070, Thesis

December 6, 2013 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

Applications

Locality Analysis for Characterizing Applications Based on Sparse Matrices

Dense Real-Time Mapping of Object-Class Semantics from RGB-D Video

Advanced ultrasound beam forming using GPGPU technology

Partial Parallelization of the Successive Projections Algorithm using Compute Unified Device Architecture

A GPU-based Multiresolution Pipeline for Compressed Volume Rendering

Waste Not… Efficient Co-Processing of Relational Data

GPU-Accelerated Crack Path Computation Based on a Phase Field Approach for Brittle Fracture

A Distributed Data Mining Framework Accelerated with Graphics Processing Units

A Quantitative Comparison of Emulated Shared Memory Architectures to Current Multicore CPUs and GPUs

Parallel tree-ensemble algorithms for GPUs using CUDA

Speeding up the small progress measures algorithm for parity games using the GPU

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

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)