high performance computing on graphics processing units: hgpu.org

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Active thread compaction for GPU path tracing

Ingo Wald

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Presentation, Raytracing

September 29, 2011 by hgpu

Evolving CUDA PTX programs by quantum inspired linear genetic programming

Leandro F. Cupertino, Cleomar P. Silva, Douglas M. Dias, Marco Aurelio C. Pacheco, Cristiana Bentes

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Tags: Computer science, CUDA, Databases, Genetic programming, nVidia, Performance, PTX, Tesla C1060

September 29, 2011 by hgpu

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

L. Lin, Chung-Sang Ng, A. Bhattacharjee

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Tags: Astrophysics, Computational Physics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, nVidia, Plasma physics, Solar and Stellar Astrophysics, Spectral methods, Tesla C2050

September 29, 2011 by hgpu

Possible planet-forming regions on submillimetre images

Zsolt Regaly, A. Juhasz, Zs. Sandor, C. P. Dullemond

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Source codes

Tags: Astrophysics, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, Package, Solar and Stellar Astrophysics

September 29, 2011 by hgpu

Design space exploration towards a realtime and energy-aware GPGPU-based analysis of biosensor data

Constantin Timm, Frank Weichert, Peter Marwedel, Heinrich Muller

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Tags: Computer science, Design space exploration, Energy-efficient computing, Image processing, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTS 250, nVidia ION, OpenCL, Sensing

September 28, 2011 by hgpu

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Da-Qi Ren, Reiji Suda

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GTS, Optimization, Tesla C2050

September 28, 2011 by hgpu

Parallelizing fuzzy rule generation using GPGPU

Takesuke Uenishi, Tomoharu Nakashima and Noriyuki Fujimoto

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 295, Optimization, Performance

September 28, 2011 by hgpu

VoxelPipe: a programmable pipeline for 3D voxelization

Jacopo Pantaleoni

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing, Sorting, Voxelization

September 28, 2011 by hgpu

Thread Block Compaction for Efficient SIMT Control Flow

Wilson W. L. Fung, Tor M. Aamodt

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, Programming techniques

September 28, 2011 by hgpu

Parallel implementations of probabilistic latent semantic analysis on graphic processing units

Hang Chen

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Tags: Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Text mining, Thesis

September 27, 2011 by hgpu

Fast On-line Statistical Learning on a GPGPU

FangZhou Xiao, Eric McCreath, Christfried Webers

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 200, nVidia GeForce GTX 295, Stochastic simulation

September 27, 2011 by hgpu

Intelligent GPGPU Classification in Volume Visualization: A framework based on Error-Correcting Output Codes

S. Escalera, A. Puig, O. Amoros, M. Salamo

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Tags: Algorithms, ATI, Computer science, Machine learning, nVidia, nVidia GeForce GTX 470, OpenCL, Rendering, Visualization

September 27, 2011 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

Active thread compaction for GPU path tracing

Evolving CUDA PTX programs by quantum inspired linear genetic programming

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

Possible planet-forming regions on submillimetre images

Design space exploration towards a realtime and energy-aware GPGPU-based analysis of biosensor data

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Parallelizing fuzzy rule generation using GPGPU

VoxelPipe: a programmable pipeline for 3D voxelization

Thread Block Compaction for Efficient SIMT Control Flow

Parallel implementations of probabilistic latent semantic analysis on graphic processing units

Fast On-line Statistical Learning on a GPGPU

Intelligent GPGPU Classification in Volume Visualization: A framework based on Error-Correcting Output Codes

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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