high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Performance improvements of real-time crowd simulations

Guillermo Vigueras, Juan M. Orduna, Miguel Lozano

View

Download (PDF)

Tags: Algorithms, Computer science, Rendering

July 17, 2011 by hgpu

Using Graphics Processor Units (GPUs) for Automatic Video Structuring

Peter Kehoe, Alan F. Smeaton

View

Download (PDF)

Tags: Algorithms, Cg, Image processing, nVidia, nVidia GeForce 7800 GT, OpenGL

July 17, 2011 by hgpu

hiCUDA: High-Level GPGPU Programming

Tianyi David Han, Tarek S. Abdelrahman

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8800 GT, Package, Presentation

July 17, 2011 by hgpu

Highly parallel decoding of space-time codes on graphics processing units

Kalyana C. Bollapalli, Yiyue Wu, Kanupriya Gulati, Sunil Khatri, A. Robert Calderbank

View

Download (PDF)

Tags: CUDA, nVidia, nVidia GeForce GTX 280, Signal processing, Tesla C1060, Wireless baseband architecture

July 17, 2011 by hgpu

H- and C-level WFST-based large vocabulary continuous speech recognition on Graphics Processing Units

Jungsuk Kim, Kisun You, Wonyong Sung

View

Download (PDF)

Tags: CUDA, nVidia, nVidia GeForce GTX 285, Signal processing, Speech recognition

July 17, 2011 by hgpu

Feature-based speed limit sign detection using a graphics processing unit

Vladimir Glavtchev, Pinar Muyan-Ozcelik, Jeffrey M. Ota, John D. Owens

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Image recognition, nVidia, nVidia GeForce 9400 M GS, OpenGL, Rendering

July 17, 2011 by hgpu

Mars: Accelerating MapReduce with Graphics Processors

Wenbin Fang, Bingsheng He, Qiong Luo, N.K. Govindaraju

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 280, Package, Presentation

July 17, 2011 by hgpu

Parallel implementation of endmember extraction algorithms using NVidia graphical processing units

Antonio Plaza, Javier Plaza, Sergio Sanchez

View

Download (PDF)

Tags: CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, Sensing, Spectral methods

July 17, 2011 by hgpu

Quality comparison and acceleration for digital hologram generation method based on segmentation

Hoonjong Kang, Fahri Yaras, Levent Onural

View

Download (PDF)

Tags: Computer holography, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX 280

July 17, 2011 by hgpu

Uniform partitioning of Monte Carlo radiosity on GPUs

J. R. Sanjurjo, M. Amor, E. J. Padron, R. Doallo, M. Boo

Tags: Algorithms, CUDA, Image processing, nVidia

July 16, 2011 by hgpu

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Matthew J. Sottile, Craig E Rasmussen, Wayne N. Weseloh, Robert W. Robey, Daniel Quinlan, Jeffrey Overbey

View

Download (PDF)

Source codes

Tags: Computer science, Fortran, nVidia, OpenCL, Package, Programming Languages, Tesla C2050

July 14, 2011 by hgpu

Real-time, fast radio transient searches with GPU de-dispersion

Alessio Magro, Aris Karastergiou, Stefano Salvini, Benjamin Mort, Fred Dulwich, Kristian Zarb Adami

View

Download (PDF)

Tags: Astrophysics, CUDA, FFT, Instrumentation and Methods for Astrophysics, nVidia, Tesla C1060

July 14, 2011 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Performance improvements of real-time crowd simulations

Using Graphics Processor Units (GPUs) for Automatic Video Structuring

hiCUDA: High-Level GPGPU Programming

Highly parallel decoding of space-time codes on graphics processing units

H- and C-level WFST-based large vocabulary continuous speech recognition on Graphics Processing Units

Feature-based speed limit sign detection using a graphics processing unit

Mars: Accelerating MapReduce with Graphics Processors

Parallel implementation of endmember extraction algorithms using NVidia graphical processing units

Quality comparison and acceleration for digital hologram generation method based on segmentation

Uniform partitioning of Monte Carlo radiosity on GPUs

ForOpenCL: Transformations Exploiting Array Syntax in Fortran for Accelerator Programming

Real-time, fast radio transient searches with GPU de-dispersion

Recent source codes

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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

Most viewed papers (last 30 days)