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Medical imaging using CUDA

Thomas Kovac

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Tags: CUDA, Image registration, Medicine, MRI, nVidia, Thesis

October 25, 2014 by hgpu

CUVLE: Variable-Length Encoding on CUDA

Jose M Gonzalez-Linares, Antonio Fuentes-Alventosa, Juan Gomez-Luna, Nicolas Guil

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 550 Ti

October 25, 2014 by hgpu

cufftShift: High Performance CUDA-accelerated FFT-shift Library

Marwan Abdellah

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Tags: Algorithms, CUDA, FFT, Image processing, nVidia, nVidia GeForce GTX 580, Package

October 24, 2014 by hgpu

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Piotr Przymus

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Tags: Algorithms, Compression, Computer science, CUDA, Data mining, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, Tesla C2070, Tesla M2070, Thesis

October 24, 2014 by hgpu

Monitoring Large-scale Microblog on GPUs

Yunpeng Cao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9400 GT, String matchning

October 24, 2014 by hgpu

Improved Integral Histogram Algorithm for Big Sized Images in CUDA Environment

Chang Won Lee, Tae-Young Choe

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 670

October 24, 2014 by hgpu

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 22, 2014 by hgpu

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Jing Wu

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Tags: Computer science, CUDA, FFT, Heterogeneous systems, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Poisson equation, Tesla C1060, Tesla C2050, Thesis

October 22, 2014 by hgpu

Performance Engineering of the Kernel Polynomial Method on Large-Scale CPU-GPU Systems

Moritz Kreutzer, Georg Hager, Gerhard Wellein, Andreas Pieper, Andreas Alvermann, Holger Fehske

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Tags: Computational Engineering, CUDA, Finance, Mesoscale and Nanoscale Physics, nVidia, Tesla K20

October 22, 2014 by hgpu

A Performance Comparison of Sort and Scan Libraries for GPUs

Bruce Merry

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Tags: Algorithms, AMD Radeon R9 270, ATI, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting, Tesla K40

October 20, 2014 by hgpu

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

M. P. Wachowiak, B. B. Sarlo, A. E. Lambe Foster

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Tags: Computational Physics, CUDA, Heterogeneous systems, nVidia, Particle swarm optimization, Physics, Tesla S1070

October 20, 2014 by hgpu

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Kato Mivule, Benjamin Harvey, Crystal Cobb, Hoda El Sayed

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Tags: Computer science, CUDA, MapReduce, nVidia, Overview, Pthreads, Review, Tesla K20

October 18, 2014 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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high performance computing on graphics processing units: hgpu.org

Programming

Medical imaging using CUDA

CUVLE: Variable-Length Encoding on CUDA

cufftShift: High Performance CUDA-accelerated FFT-shift Library

Query Optimization in Heterogeneous CPU/GPU Environment for Time Series Databases

Monitoring Large-scale Microblog on GPUs

Improved Integral Histogram Algorithm for Big Sized Images in CUDA Environment

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Optimization Techniques for Mapping Algorithms and Applications onto CUDA GPU Platforms and CPU-GPU Heterogeneous Platforms

Performance Engineering of the Kernel Polynomial Method on Large-Scale CPU-GPU Systems

A Performance Comparison of Sort and Scan Libraries for GPUs

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

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