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GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Mishal Almazrooie, Mogana Vadiveloo, Rosni Abdullah

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla C2050

January 7, 2016 by hgpu

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

Phillipe A. Pereira, Higo F. Albuquerque, Hendrio M. Marques, Isabela S. Silva, Celso B. Carvalho, Lucas C. Cordeiro

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Source codes

Tags: Computer science, CUDA, nVidia, Package

January 7, 2016 by hgpu

DeepLearningKit – an Open Source Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Amund Tvei, Torbjorn Morland, Thomas Brox Rost

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Source codes

Tags: Computer science, Deep learning, Machine learning, Neural networks, OpenCL, Package, Vulkan

January 7, 2016 by hgpu

Faster GPU Based Genetic Programming Using A Two Dimensional Stack

Darren M. Chitty

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 670

January 7, 2016 by hgpu

Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Judit Planas Carbonell

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OmpSs, Task scheduling, Tesla K20, Tesla K40, Tesla M2090, Thesis

January 4, 2016 by hgpu

Automatic Performance Tuning of Stencil Computations on Graphics Processing Units

Joseph D. Garvey

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Tags: Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Stencil computation, Thesis

January 4, 2016 by hgpu

Accelerating Binary Genetic Algorithm Driven Missile Design Optimization Routine with a CUDA Coded Six Degrees-Of-Freedom Simulator

Daniel Benton

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570

January 4, 2016 by hgpu

A Comparison of the performance of HPC Accelerators

Xiao Li

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Tags: AMD FirePro W9100, ATI, Computer science, nVidia, OpenCL, Performance, Tesla K40, Thesis

December 31, 2015 by hgpu

Study of basic vector operations on Intel Xeon Phi and NVIDIA Tesla using OpenCL

Edoardo Coronado, Guillermo Indalecio, Antonio Garcia-Loureiro

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Tags: Computer science, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Performance, Tesla S2050

December 31, 2015 by hgpu

A Deep Generative Deconvolutional Image Model

Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin

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Tags: Bayesian, Caffe, Computer science, Computer vision, CUDA, Deep learning, Image generation, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

December 31, 2015 by hgpu

Parallel 3D Fast Wavelet Transform comparison on CPUs and GPUs

Gregorio Bernabe

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Tags: Computer science, CUDA, FFT, nVidia, OpenCL, OpenMP, Pthreads, Tesla C2050

December 31, 2015 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Verifying CUDA Programs using SMT-Based Context-Bounded Model Checking

DeepLearningKit – an Open Source Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Faster GPU Based Genetic Programming Using A Two Dimensional Stack

Batched Linear Algebra Problems on GPU Accelerators

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Automatic Performance Tuning of Stencil Computations on Graphics Processing Units

Accelerating Binary Genetic Algorithm Driven Missile Design Optimization Routine with a CUDA Coded Six Degrees-Of-Freedom Simulator

A Comparison of the performance of HPC Accelerators

Study of basic vector operations on Intel Xeon Phi and NVIDIA Tesla using OpenCL

A Deep Generative Deconvolutional Image Model

Parallel 3D Fast Wavelet Transform comparison on CPUs and GPUs

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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