high performance computing on graphics processing units: hgpu.org

hgpu.org » Optimization

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

Timothy D. R. Hartley

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5600, Optimization, Performance, Thesis

October 22, 2011 by hgpu

GPU performance prediction using parametrized models

Andreas Resios

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 460, Optimization, Performance, Thesis

October 22, 2011 by hgpu

Low-Impact Profiling of Streaming, Heterogeneous Applications

Joseph Marion Lancaster

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Tags: Algorithms, Computer science, Heterogeneous systems, Optimization, Performance, Thesis

October 22, 2011 by hgpu

Mapping Iterative Medical Imaging Algorithm on Cell Accelerator

Meilian Xu, Parimala Thulasiraman

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Tags: Algorithms, Cell processor, Heterogeneous systems, Image processing, Image recognition, Medicine, Optimization, Tomography

October 22, 2011 by hgpu

Analysis and Implementation of eSTREAM and SHA-3 Cryptographic Algorithms

Deian Stefan

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Optimization, Security, Stream Ciphers, Thesis

October 21, 2011 by hgpu

DOPA: GPU-based protein alignment using database and memory access optimizations

Laiq Hasan, Marijn Kentie, Zaid Al-Ars

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Tags: Algorithms, Bioinformatics, Biology, Computational Complexity, CUDA, Databases, nVidia, nVidia GeForce GTX 275, Optimization, Package, Sequence alignment, Smith-Waterman algorithm

October 21, 2011 by hgpu

Automatic program analysis for data parallel kernels

Calin Juravle

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Programming techniques, Thesis

October 20, 2011 by hgpu

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 19, 2011 by hgpu

10×10: A General-purpose Architectural Approach to Heterogeneity and Energy Efficiency

Andrew A. Chien, Allan Snavely, Mark Gahagan

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Tags: Clustering, Computer science, Heterogeneous systems, Optimization

October 19, 2011 by hgpu

A Code Transformation Framework for Scientific Applications on Structured Grids

Pei-Hung Lin, Jagan Jayaraj, Paul Woodward, Pen-chung Yew

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Tags: Compilers, Computer science, Fluid dynamics, Optimization, Performance, Programming techniques

October 19, 2011 by hgpu

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

Alcides Fonseca

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Tags: Compilers, Computer science, Java, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Package, Thesis

October 19, 2011 by hgpu

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 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

Accelerating Component-Based Dataflow Middleware with Adaptivity and Heterogeneity

GPU performance prediction using parametrized models

Low-Impact Profiling of Streaming, Heterogeneous Applications

Mapping Iterative Medical Imaging Algorithm on Cell Accelerator

Analysis and Implementation of eSTREAM and SHA-3 Cryptographic Algorithms

DOPA: GPU-based protein alignment using database and memory access optimizations

Automatic program analysis for data parallel kernels

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

10×10: A General-purpose Architectural Approach to Heterogeneity and Energy Efficiency

A Code Transformation Framework for Scientific Applications on Structured Grids

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

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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