high performance computing on graphics processing units: hgpu.org

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Visualizing Trends on Twitter

Cheng Hau Tong

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Thesis, Visualization

March 13, 2014 by hgpu

Exploring High Performance SQL Databases with Graphics Processing Units

Glen Hordemann

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 680, Text mining, Thesis

March 7, 2014 by hgpu

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

Wei Chen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla C2070, Thesis

March 7, 2014 by hgpu

Computational Experiments in Markov Chain Monte Carlo

Alexander D. Kaiser

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Tags: Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 590, OpenCL, Probability, Thesis

March 4, 2014 by hgpu

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

Niklas Ulvinge

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Thesis

March 4, 2014 by hgpu

An Evaluation of the GAMA/StarPU Frameworks for Heterogeneous Platforms: the Progressive Photon Mapping Algorithm

Miguel Branco Palhas

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Heterogeneous systems, Memory model, nVidia, Rendering, Tesla K20, Tesla M2090, Thesis

February 25, 2014 by hgpu

X-ray CT on the GPU

Ravikiran Tadepalli

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Tags: Algorithms, CUDA, Medicine, nVidia, Tesla C1060, Thesis, Tomography

February 19, 2014 by hgpu

A Similarity-Based Analysis Tool for Scientific Application Porting

Wei Ding

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenMP, Performance, Portability, Tesla C2070, Thesis

February 17, 2014 by hgpu

Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

Carolin Wolf

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Tags: Computer science, CUDA, Java, nVidia, OpenMP, Tesla M1060, Thesis

February 12, 2014 by hgpu

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

Depth Map Based Superresolution Method in 3D Reconstruction

Gabriel Bernardino

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla C1060, Thesis

February 5, 2014 by hgpu

A Real-Time, GPU-Based, Non-Imaging Back-End for Radio Telescopes

Alessio Magro

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Tags: Astrophysics, Clustering, CUDA, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, nVidia, Tesla K20, Thesis

February 4, 2014 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

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

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Visualizing Trends on Twitter

Exploring High Performance SQL Databases with Graphics Processing Units

Dynamic Workload Division in GPU-CPU Heterogeneous Systems

Computational Experiments in Markov Chain Monte Carlo

Increasing programmability of an embedded domain specific language for GPGPU kernels using static analysis

An Evaluation of the GAMA/StarPU Frameworks for Heterogeneous Platforms: the Progressive Photon Mapping Algorithm

X-ray CT on the GPU

A Similarity-Based Analysis Tool for Scientific Application Porting

Transparent use of Java objects on the GPU in the JaMP/OpenMP framework

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Depth Map Based Superresolution Method in 3D Reconstruction

A Real-Time, GPU-Based, Non-Imaging Back-End for Radio Telescopes

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

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

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

Most viewed papers (last 30 days)