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Extending Lyapack for the Solution of Band Lyapunov Equations on Hybrid CPU-GPU Platforms

Peter Benner, Ernesto Dufrechou, Pablo Ezzatti, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: CUDA, Linear Algebra, Mathematics, nVidia, Tesla K20, Tesla S2070

August 3, 2014 by hgpu

Accelerating Band Linear Algebra Operations on GPUs with Application in Model Reduction

Peter Benner, Ernesto Dufrechou, Pablo Ezzatti, Pablo Igounet, Enrique S. Quintana-Orti, Alfredo Remon

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse matrix, Tesla S2070

June 23, 2014 by hgpu

Environment Segmentation in Service Robotics

Matthew S. Roscoe, Paul G Ploger

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla S2070

October 31, 2011 by hgpu

The Lattice Boltzmann Simulation on Multi-GPU Systems

Thor Kristian Valderhaug

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Tags: ATI, ATI Radeon HD 5870, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, OpenCL, Tesla C1060, Tesla C2070, Tesla S2070, Tesla T10, Thesis

October 17, 2011 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

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

BoltzGen:Toward Universal Binder Design

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

Extending Lyapack for the Solution of Band Lyapunov Equations on Hybrid CPU-GPU Platforms

Accelerating Band Linear Algebra Operations on GPUs with Application in Model Reduction

Environment Segmentation in Service Robotics

The Lattice Boltzmann Simulation on Multi-GPU Systems

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

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

BoltzGen:Toward Universal Binder Design

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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