high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

ClearPath: highly parallel collision avoidance for multi-agent simulation

Stephen J. Guy, Jatin Chhugani, Changkyu Kim, Nadathur Satish, Ming Lin, Dinesh Manocha, Pradeep Dubey

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Tags: Artificial intelligence, Computer science, Larrabee, Optimization

January 8, 2011 by hgpu

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

M. W. Hall, Y. Gil, R. F. Lucas

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Tags: Compilers, Computer science, FPGA, nVidia, Optimization, Performance

January 8, 2011 by hgpu

Data transformations enabling loop vectorization on multithreaded data parallel architectures

Byunghyun Jang, Perhaad Mistry, Dana Schaa, Rodrigo Dominguez, David Kaeli

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Tags: ATI, ATI Radeon HD 3870, ATI Stream, Brook, Code generation, Compilers, Computer science, Optimization

January 7, 2011 by hgpu

Parallel evolutionary algorithms on graphics processing unit

Man-Leung Wong, Tien-Tsin Wong, Ka-Ling Fok

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Tags: Artificial intelligence, Computer science, nVidia, nVidia GeForce 6800 Ultra, Optimization, Shaders

January 5, 2011 by hgpu

Source-to-Source Optimization of CUDA C for GPU Accelerated Cardiac Cell Modeling

Fred V. Lionetti, Andrew D. McCulloch, Scott B. Baden

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Tags: Computational biology, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 295, Optimization

December 29, 2010 by hgpu

GPU-based parallel particle swarm optimization

You Zhou, Ying Tan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, Optimization

December 21, 2010 by hgpu

SIMD Optimization of Linear Expressions for Programmable Graphics Hardware

Chandrajit Bajaj, Insung Ihm, Jungki Min, Jinsang Oh

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce FX 5900 Ultra, OpenGL, Optimization

December 19, 2010 by hgpu

GPU-based Island Model for Evolutionary Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talb

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Tags: Algorithms, CUDA, Mathematics, nVidia, nVidia GeForce GTX 280, Optimization

December 18, 2010 by hgpu

GPU-accelerated differential evolutionary Markov Chain Monte Carlo method for multi-objective optimization over continuous space

Weihang Zhu, Yaohang Li

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Tags: Mathematics, nVidia, nVidia GeForce GTX 280, Optimization

December 17, 2010 by hgpu

Optimizing Monte Carlo radiosity on graphics hardware

J. Sanjurjo, M. Amor, M. Boo, R. Doallo, J. Casares

Tags: Computer science, CUDA, Monte Carlo simulation, nVidia, Optimization, Rendering

December 15, 2010 by hgpu

SWPS3 – fast multi-threaded vectorized Smith-Waterman for IBM Cell/B.E. and x86/SSE2

Adam Szalkowski, Christian Ledergerber, Philipp Kraehenbuehl, Christophe Dessimoz

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Tags: Biology, Cell processor, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Package, Sequence alignment, Smith-Waterman algorithm

December 12, 2010 by hgpu

Multiscale texture synthesis

Charles Han, Eric Risser, Ravi Ramamoorthi, Eitan Grinspun

Tags: Computer science, Image generation, Optimization

December 12, 2010 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

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high performance computing on graphics processing units: hgpu.org

ClearPath: highly parallel collision avoidance for multi-agent simulation

Self-Configuring Applications for Heterogeneous Systems: Program Composition and Optimization Using Cognitive Techniques

Data transformations enabling loop vectorization on multithreaded data parallel architectures

Parallel evolutionary algorithms on graphics processing unit

Source-to-Source Optimization of CUDA C for GPU Accelerated Cardiac Cell Modeling

GPU-based parallel particle swarm optimization

SIMD Optimization of Linear Expressions for Programmable Graphics Hardware

GPU-based Island Model for Evolutionary Algorithms

GPU-accelerated differential evolutionary Markov Chain Monte Carlo method for multi-objective optimization over continuous space

Optimizing Monte Carlo radiosity on graphics hardware

SWPS3 – fast multi-threaded vectorized Smith-Waterman for IBM Cell/B.E. and x86/SSE2

Multiscale texture synthesis

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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