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MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

S. J. Pennycook, S. A. Jarvis

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Tags: ATI, ATI FirePro V7800, ATI Radeon HD 6550, Benchmarking, Computer science, Molecular dynamics, nVidia, nVidia GeForce GTX 680, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

February 14, 2013 by hgpu

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

S. J. Pennycook, C. J. Hughes, M. Smelyanskiy, S. A. Jarvis

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Tags: Algorithms, Benchmarking, Computer science, Intel, Intel Phi, Molecular dynamics

February 14, 2013 by hgpu

Enhancing Performance of Meshfree Methods by Hybrid Computing

Yo-Ming Hsieh, Mao-Sen Pan

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Tags: Computer science, CUDA, FEM, Finite element method, Hybrid computing, nVidia, Tesla C2050

February 14, 2013 by hgpu

The Dual-Path Execution Model for Efficient GPU Control Flow

Minsoo Rhu, Mattan Erez

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance

February 14, 2013 by hgpu

Nonlinear dynamic finite element analysis with GPU

T. Bahcecioglu, O. Kurc

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Tags: Algorithms, Computer science, CUDA, Nonlinear analysis, nVidia, Tesla C2050

February 14, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

Evaluation of Standardized Password-based Key Derivation against Parallel Processing Platforms

Markus Durmuth, Tim Guneysu, Markus Kasper, Christof Paar, Tolga Yalcin, Ralf Zimmermann

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Tags: Computer science, CUDA, FPGA, GPU cluster, nVidia, Review, Security, Tesla C2070

February 14, 2013 by hgpu

Real-Time 3D Face Identification from a Depth Camera

Rui Min, Jongmoo Choi, Gerard Medioni, Jean-Luc Dugelay

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Tags: Computer science, Computer vision, CUDA, nVidia, Tesla C1060

February 14, 2013 by hgpu

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

Alessandro Giusti, Dan C. Ciresan, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Artificial intelligence, Computational Complexity, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX 580

February 12, 2013 by hgpu

Implementing an architecture for efficient network traffic processing on modern graphics hardware

Lazaros Koromilas

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

February 12, 2013 by hgpu

Accelerated Wide Baseline Matching using OpenCL

Jian Cao, Jie Liang, Xiao-fang Xie, Xun-qiang Hu

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Tags: Computer science, Computer vision, Image registration, nVidia, nVidia GeForce 8800 GT, OpenCL

February 12, 2013 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

MATLAB and Python for GPU Computing

Developing Performance-Portable Molecular Dynamics Kernels in OpenCL

Exploring SIMD for Molecular Dynamics, Using Intel Xeon Processors and Intel Xeon Phi Coprocessors

Enhancing Performance of Meshfree Methods by Hybrid Computing

The Dual-Path Execution Model for Efficient GPU Control Flow

Nonlinear dynamic finite element analysis with GPU

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Evaluation of Standardized Password-based Key Derivation against Parallel Processing Platforms

Real-Time 3D Face Identification from a Depth Camera

Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks

Implementing an architecture for efficient network traffic processing on modern graphics hardware

Accelerated Wide Baseline Matching using OpenCL

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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