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Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Sergio Bernabe, Sergio Sanchez, Antonio Plaza, Sebastian Lopez, Jon Atli Benediktsson, Roberto Sarmiento

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Tags: Algorithms, CUBLAS, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, Tesla C1060

March 26, 2013 by hgpu

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Junjie Lai, Andre Seznec

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Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 680, Optimization, Performance

February 22, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

Numerical computations in Java with CUDA

Bogdan Oancea, Tudorel Andrei, Andreea Iluzia Iacob

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Tags: Computer science, CUBLAS, CUDA, Java, Linear Algebra, nVidia, nVidia GeForce 9500 GT

January 7, 2013 by hgpu

Task-based Conjugate-Gradient for multi-GPUs platforms

Emmanuel Agullo, Luc Giraud, Abdou Guermouche, Stojce Nakov, Jean Roman

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2070

December 25, 2012 by hgpu

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Peter Richtarik, Martin Takac, Selin Damla Ahipasaoglu

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Source codes

Tags: CUBLAS, CUDA, Machine learning, nVidia, Package, Statistics

December 18, 2012 by hgpu

Matrix-Matrix Multiplications on GPUs for Accelerating a Parallel Fluid Dynamics Code

Kenneth Webster

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Tags: CUBLAS, CUDA, Fluid dynamics, Matrix multiplication, nVidia, Tesla M2070, Thesis

December 12, 2012 by hgpu

Implementing QR Factorization Updating Algorithms on GPUs

Robert Andrew, Nicholas Dingle

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, Linear Algebra, Numerical Analysis, nVidia, Tesla M2050

December 10, 2012 by hgpu

Use of CUDA for the Continuous Space Language Model

Elizabeth A. Thompson, Timothy Anderson

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Tags: CUBLAS, CUDA, nVidia, nVidia Quadro FX 2700 M, Signal processing

November 16, 2012 by hgpu

Adapting Irregular Computations to Large CPU-GPU Clusters in the MADNESS Framework

Vlad Slavici, Raghu Varier, Gene Cooperman, Robert J. Harrison

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Tags: Chemistry, Computational chemistry, Computer science, CUBLAS, CUDA, GPU cluster, nVidia, Tesla M2090

November 6, 2012 by hgpu

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Paola Arce, Cristian Maureira, Roberto Bonvallet, Cesar Fernandez

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Tags: Algorithms, CUBLAS, CUDA, Finance, Linear Algebra, Machine learning, Neural networks, nVidia, Tesla M2050

September 20, 2012 by hgpu

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2070

September 13, 2012 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

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Performance Upper Bound Analysis and Optimization of SGEMM on Fermi and Kepler GPUs

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Numerical computations in Java with CUDA

Task-based Conjugate-Gradient for multi-GPUs platforms

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Matrix-Matrix Multiplications on GPUs for Accelerating a Parallel Fluid Dynamics Code

Implementing QR Factorization Updating Algorithms on GPUs

Use of CUDA for the Continuous Space Language Model

Adapting Irregular Computations to Large CPU-GPU Clusters in the MADNESS Framework

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

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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