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Batched Matrix Computations on Hardware Accelerators Based on GPUs

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

January 15, 2015 by hgpu

High Performance GPU-based Fourier Volume Rendering

Marwan Abdellah, Ayman Eldeib, Amr Sharawi

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia Quadro K5000, OpenGL, Rendering, Visualization

January 15, 2015 by hgpu

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Chapa Martell Mario Alberto, Hiroyuki Sato

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Tags: Computer science, nVidia, nVidia GeForce GTX 660, OpenCL, Performance

January 13, 2015 by hgpu

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

Shinichi Yamagiwa, Guyue Wang, Koichi Wada

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Tags: Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 13, 2015 by hgpu

A Time Optimal Parallel Algorithm for the Dynamic Programming on the Hierarchical Memory Machine

Koji Nakano

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 680

January 13, 2015 by hgpu

Thorough Evaluation of GPU Shared Memory Load and Store Instructions

Satoshi Okamoto, Yasuaki Ito, Koji Nakano, Jacir L. Bordim

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 780 Ti, Performance, PTX

January 13, 2015 by hgpu

Face Recognition: A Tutorial on Computational Aspects

Alexander Alling, Nathaniel Powers, Tolga Soyata

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 760, nVidia GeForce GTX 780, Tutorial

January 10, 2015 by hgpu

Dynamic Feature-Adaptive Subdivision

H. Schafer, J. Raab, B. Keinert, M. Meyer, M. Stamminger, M. Niessner

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Tags: Computational Geometry, Computer science, DirectX, Interactive application, nVidia, nVidia GeForce GTX 980, Rendering

January 10, 2015 by hgpu

Exploring GPU Memory Performance Using Digital Image Processing Algorithms

Puya Memarzia, Farshad Khunjush

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Tags: Benchmarking, Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 570

January 10, 2015 by hgpu

Image Super-Resolution Using Deep Convolutional Networks

Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang

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Tags: CNN, Computer science, CUDA, Machine learning, Neural networks, nVidia, Package

January 10, 2015 by hgpu

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

Geoffrey Ndu, Mikel Lujan, Javier Navaridas

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package

January 8, 2015 by hgpu

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Leonard Truong, Chick Markley, Armando Fox

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Tags: Code generation, Computer science, OpenCL, Python

January 8, 2015 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Batched Matrix Computations on Hardware Accelerators Based on GPUs

High Performance GPU-based Fourier Volume Rendering

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

A Time Optimal Parallel Algorithm for the Dynamic Programming on the Hierarchical Memory Machine

Thorough Evaluation of GPU Shared Memory Load and Store Instructions

Face Recognition: A Tutorial on Computational Aspects

Dynamic Feature-Adaptive Subdivision

Exploring GPU Memory Performance Using Digital Image Processing Algorithms

Image Super-Resolution Using Deep Convolutional Networks

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

An Extensible Framework for Composing Stencils with Common Scientific Computing Patterns

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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