high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

SIMD Divergence Optimization through Intra-Warp Compaction

Aniruddha S. Vaidya, Anahita Shayesteh, Dong Hyuk Woo, Roy Saharoy, Mani Azimi

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Tags: Computer science, Hardware Architecture, OpenCL, OpenGL, Performance

July 12, 2013 by hgpu

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Nouredine Melab, The van Luong, Karima Boufaras, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package, Performance, Search

July 8, 2013 by hgpu

Optimize Overall System Performance Through Workload Sequencing for GPUs Data Offloading

Wei Liu, Jian-Jia Chen, Qingxu Deng, Tei-Wei Kuo, Xue Liu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 630 M, Performance

July 5, 2013 by hgpu

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

Qingyu Meng, Alan Humphrey, John Schmidt, Martin Berzins

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi, Performance

July 2, 2013 by hgpu

GPU-CC: a Reconfigurable GPU Architecture with Communicating Cores

Gert-Jan van den Braak, Henk Corporaal

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 470, Performance

June 28, 2013 by hgpu

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

Paul Rosen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Wavelet

June 24, 2013 by hgpu

Provably Efficient GPU Algorithms

Nodari Sitchinava, Volker Weichert

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Sorting

June 24, 2013 by hgpu

Exploring GPGPUs Workload Characteristics and Power Consumption

Sohan Lal, Jan Lucas, Mauricio Alvarez-Mesa, Ahmed Elhossini, Ben Juurlink

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, nVidia, nVidia GeForce GTX 580, Performance

June 22, 2013 by hgpu

Auto-Tunning of Data Communication on Heterogeneous Systems

Marc Jorda, Ivan Tanasic, Javier Cabezas, Lluis Vilanova, Isaac Gelado, Nacho Navarro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C2050, Tesla C2070, Tesla M2090

June 17, 2013 by hgpu

Performance Analysis on Energy Efficient High-Performance Architectures

Roman Iakymchuk, Francois Trahay

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Tags: ARM, Computer science, CUDA, Energy-efficient computing, nVidia, Performance

June 16, 2013 by hgpu

A comprehensive study of Dynamic Memory Management in OpenCL kernels

Roy Spliet

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Tags: Algorithms, ATI, Computer science, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance, Tesla C2050, Tesla K20, Thesis

June 6, 2013 by hgpu

A Reliable Throughput Gain on GPUs

Paolo Rech, Luigi Carro

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance

June 6, 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

SIMD Divergence Optimization through Intra-Warp Compaction

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Optimize Overall System Performance Through Workload Sequencing for GPUs Data Offloading

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

GPU-CC: a Reconfigurable GPU Architecture with Communicating Cores

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

Provably Efficient GPU Algorithms

Exploring GPGPUs Workload Characteristics and Power Consumption

Auto-Tunning of Data Communication on Heterogeneous Systems

Performance Analysis on Energy Efficient High-Performance Architectures

A comprehensive study of Dynamic Memory Management in OpenCL kernels

A Reliable Throughput Gain on 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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