high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

OCCA: A unified approach to multi-threading languages

David S Medina, Amik St-Cyr, T. Warburton

View

Tags: ATI, ATI Radeon HD 7970, ATI Radeon HD 7990, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX Titan, OpenCL, Spectral elements

March 6, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

Performance Analysis for GPU-based Ray-triangle Algorithms

Juan J. Jimenez, Carlos J. Ogayar, Jose M. Noguera, Felix Paulano

View

Download (PDF)

Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Performance, Raytracing

March 6, 2014 by hgpu

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K.A. Hawick, D.P.Playne

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

March 4, 2014 by hgpu

Computational Experiments in Markov Chain Monte Carlo

Alexander D. Kaiser

View

Download (PDF)

Tags: Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 590, OpenCL, Probability, Thesis

March 4, 2014 by hgpu

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Niklas Ulvinge

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Thesis

March 4, 2014 by hgpu

Performance Optimization of Clustering On GPU

Vijal D. Patel, Sumitra Menaria

View

Download (PDF)

Tags: Algorithms, Clustering, Computer science, CUDA, Hierarchical clustering, nVidia, nVidia GeForce GTX 480, Tesla C2070

March 4, 2014 by hgpu

Computational Optimization of a Time-Domain Beamforming Algorithm Using CPU and GPU

Johannes Stier, Christopher Hahn, Gero Zechel, Michael Beitelschmidt

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, nVidia Quadro FX 3800

March 3, 2014 by hgpu

Face Detection for Human Identification in Surveillance

S.G.Kartheeswari, B.Vijaya Lakshmi

View

Download (PDF)

Tags: Algorithms, Computer science, Computer vision, Optical flow

March 3, 2014 by hgpu

Increasing predictability of GPU’s

David Defour

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance

March 3, 2014 by hgpu

Reducing Beamforming Calculation Time with GPU Accelerated Algorithms

Steffen Schmidt

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 590, OpenCL

March 1, 2014 by hgpu

Comparison of Hybrid Sorting Algorithms Implemented on Different Parallel Hardware Platforms

Dominik Zurek, Marcin Pietron, Maciej Wielgosz, Kazimierz Wiatr

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, OpenMP, Sorting, Tesla M2090

March 1, 2014 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

* * *

high performance computing on graphics processing units: hgpu.org

OCCA: A unified approach to multi-threading languages

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

Performance Analysis for GPU-based Ray-triangle Algorithms

On-Demand Source Code Generation & Scheduling Optimised Parallel Applications on Heterogeneous Platforms

Computational Experiments in Markov Chain Monte Carlo

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Performance Optimization of Clustering On GPU

Computational Optimization of a Time-Domain Beamforming Algorithm Using CPU and GPU

Face Detection for Human Identification in Surveillance

Increasing predictability of GPU’s

Reducing Beamforming Calculation Time with GPU Accelerated Algorithms

Comparison of Hybrid Sorting Algorithms Implemented on Different Parallel Hardware Platforms

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

Most viewed papers (last 30 days)