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Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Gang Mei, Hong Tian

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 640

February 21, 2014 by hgpu

Computing least squares condition numbers on hybrid multicore/GPU systems

Marc Baboulin, Jack Dongarra, Remi Lacroix

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Tesla C2075

February 21, 2014 by hgpu

Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

Jae-Hyeon Parq, Erik Sevre, Sang-Mook Lee

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Tags: Computer science, CUDA, MPI, nVidia, nVidia Quadro 4000

February 21, 2014 by hgpu

X-ray CT on the GPU

Ravikiran Tadepalli

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Tags: Algorithms, CUDA, Medicine, nVidia, Tesla C1060, Thesis, Tomography

February 19, 2014 by hgpu

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Jianting Zhang, Simin You

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, nVidia Quadro 6000, Tesla C2050

February 19, 2014 by hgpu

Using of GPUs for cluster analysis of large data by K-means method

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

Parallel algorithms for problems of cluster analysis with very large amount of data

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

Fast Hamiltonian Monte Carlo Using GPU Computing

Andrew L. Beam, Sujit K. Ghosh, Jon Doyle

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Tags: Algorithms, Bayesian, CUDA, CULA, Monte Carlo simulation, nVidia, Package, Python, Statistics, Tesla K20

February 19, 2014 by hgpu

Towards a Performance-Portable FFT Library for Heterogeneous Computing

Carlo del Mundo, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 6970, ATI Radeon HD 7970, FFT, nVidia, OpenCL, Signal processing, Spectral methods, Tesla C2075, Tesla K20

February 17, 2014 by hgpu

A Similarity-Based Analysis Tool for Scientific Application Porting

Wei Ding

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenMP, Performance, Portability, Tesla C2070, Thesis

February 17, 2014 by hgpu

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

Eike Hermann Muller, Robert Scheichl, Benson Muite, Eero Vainikko

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Numerical Analysis, nVidia, Partial differential equations, PDEs, Tesla K20, Tesla M2090

February 17, 2014 by hgpu

GPU Programming with CUDA: A brief overview

Filipo Novo Mor, Plauto de Abreu Neto

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Tags: Computer science, CUDA, nVidia, Overview

February 17, 2014 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

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high performance computing on graphics processing units: hgpu.org

Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Computing least squares condition numbers on hybrid multicore/GPU systems

Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

X-ray CT on the GPU

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Using of GPUs for cluster analysis of large data by K-means method

Parallel algorithms for problems of cluster analysis with very large amount of data

Fast Hamiltonian Monte Carlo Using GPU Computing

Towards a Performance-Portable FFT Library for Heterogeneous Computing

A Similarity-Based Analysis Tool for Scientific Application Porting

Petascale elliptic solvers for anisotropic PDEs on GPU clusters

GPU Programming with CUDA: A brief overview

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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