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A parallel method for tuning Fuzzy TSK Systems with CUDA

Bruno B. Ferreira, Adriano J. O. Cruz

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 550 Ti, nVidia GeForce GTX 590, Tesla C2070

November 11, 2012 by hgpu

Sigma*: Symbolic Learning of Input-Output Specifications

Matko Botincan, Domagoj Babic

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Programming Languages

November 10, 2012 by hgpu

Efficient Dynamic Derived Field Generation on Many-Core Architectures Using Python

Cyrus Harrison, Paul Navratil, Maysam Moussalem, Ming Jiang, Hank Childs

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Tags: Computer science, nVidia, OpenCL, Python, Tesla M2050, Visualization

November 10, 2012 by hgpu

Architectural Considerations for Compiler-guided Unroll-and-Jam of CUDA Kernels

Apan Qasem

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Tags: Compilers, Computer science, CUDA, Memory model, nVidia, nVidia GeForce 9800 GT, Tesla C2050

November 8, 2012 by hgpu

Flexible N-Way MIMO Detector on GPU

Michael Wu, Bei Yin, Joseph R. Cavallaro

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Tags: Computer science, CUDA, MIMO, nVidia, nVidia GeForce GTX 560 Ti

November 8, 2012 by hgpu

Reusable OpenCL FPGA Infrastructure

Stephen Alexander Chin

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL, Thesis

November 8, 2012 by hgpu

SPH Based Fluid Animation Using CUDA Enabled GPU

Uday A. Nuli, P. J. Kulkarni

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GTX 280

November 8, 2012 by hgpu

Study of Convolution Algorithms using CPU and Graphics Hardware

Matz Johansson Bergstrom

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 570, Thesis

November 7, 2012 by hgpu

A GPU-Based Transient Stability Simulation Using Runge-Kutta Integration Algorithm

Zhijun Qin, Yunhe Hou

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 580, Sparse direct solvers

November 7, 2012 by hgpu

GPU Virtualization

Kristoffer Robin Stokke

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Source codes

Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro NVS 295, Package, Python, Thesis, Virtualization

November 7, 2012 by hgpu

Connectivity-Based Segmentation for GPU-Accelerated Mesh Decompression

Jie-Yi Zhao, Min Tang, Ruo-Feng Tong

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Geodesic Distances, nVidia, nVidia GeForce GTX 580

November 7, 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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

A parallel method for tuning Fuzzy TSK Systems with CUDA

Sigma*: Symbolic Learning of Input-Output Specifications

Efficient Dynamic Derived Field Generation on Many-Core Architectures Using Python

Architectural Considerations for Compiler-guided Unroll-and-Jam of CUDA Kernels

Flexible N-Way MIMO Detector on GPU

Reusable OpenCL FPGA Infrastructure

SPH Based Fluid Animation Using CUDA Enabled GPU

Study of Convolution Algorithms using CPU and Graphics Hardware

A GPU-Based Transient Stability Simulation Using Runge-Kutta Integration Algorithm

GPU Virtualization

Connectivity-Based Segmentation for GPU-Accelerated Mesh Decompression

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

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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