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A Practical Quicksort Algorithm for Graphics Processors

Daniel Cederman, Philippas Tsigas

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Sorting

November 6, 2010 by hgpu

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Samer Al-Kiswany, Abdullah Gharaibeh, Elizeu Santos-Neto, George Yuan, Matei Ripeanu

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 9800 GTX, Package, Storage system

November 6, 2010 by hgpu

Programming model for a heterogeneous x86 platform

Bratin Saha, Xiaocheng Zhou, Hu Chen, Ying Gao, Shoumeng Yan, Mohan Rajagopalan, Jesse Fang, Peinan Zhang, Ronny Ronen, Avi Mendelson

Tags: Computer science, Distributed data structures, Programming techniques

November 6, 2010 by hgpu

Maintaining constant frame rates in 3D texture-based volume rendering

D. Weiskopf, M. Weiler, T. Ertl

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Tags: 3D Graphics and Realism, ATI, ATI Radeon 9800 Pro, Computer science, nVidia, nVidia GeForce FX 5950 Ultra, OpenGL, Raytracing, Rendering

November 6, 2010 by hgpu

Fast scale invariant feature detection and matching on programmable graphics hardware

Nico Cornelis, Luc Van Gool

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8800 GTX

November 6, 2010 by hgpu

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Jayram M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alex Veidenbaum

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Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

November 6, 2010 by hgpu

Parallel view-dependent refinement of progressive meshes

Liang Hu, Pedro V. Sander, Hugues Hoppe

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Tags: Computer science, HLSL, nVidia, nVidia GeForce 8800 GTX, Triangular meshes, Visualization

November 6, 2010 by hgpu

PacketShader: a GPU-accelerated software router

Sangjin Han, Keon Jang, KyoungSoo Park, Sue Moon

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Tags: Computer science, CUDA, Network communications, nVidia, nVidia GeForce GTX 480, Software router

November 6, 2010 by hgpu

Multi-Level Graph Layout on the GPU

Yaniv Frishman, Ayellet Tal

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Tags: Cg, Computer science, Graph layout, nVidia, nVidia GeForce 8800 GTS, OpenGL

November 5, 2010 by hgpu

The GPU as numerical simulation engine

J. Bolz, I. Farmer, E. Grinspun, P. Schroder

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Tags: Computer science, Fluid simulation, Navier-Stokes equations, NSEs, Numerical simulation, nVidia, Sparse matrix

November 5, 2010 by hgpu

Using GPUs for Machine Learning Algorithms

Dave Steinkrau, Patrice Y. Simard, Ian Buck

Tags: Computer science, Neural networks, Pattern recognition

November 5, 2010 by hgpu

Clustering billions of data points using GPUs

Ren Wu, Bin Zhang, Meichun Hsu

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 280

November 5, 2010 by hgpu

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

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

A Practical Quicksort Algorithm for Graphics Processors

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Programming model for a heterogeneous x86 platform

Maintaining constant frame rates in 3D texture-based volume rendering

Fast scale invariant feature detection and matching on programmable graphics hardware

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Parallel view-dependent refinement of progressive meshes

PacketShader: a GPU-accelerated software router

Multi-Level Graph Layout on the GPU

The GPU as numerical simulation engine

Using GPUs for Machine Learning Algorithms

Clustering billions of data points using GPUs

Recent source codes

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

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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