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Mr. Scan: Extreme Scale Density-Based Clustering using a Tree-Based Network of GPGPU Nodes

Benjamin Welton, Evan Samanas, Barton P. Miller

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, Tesla K20

April 30, 2013 by hgpu

Astrophysical data mining with GPU. A case study: genetic classification of globular clusters

Stefano Cavuoti, Mauro Garofalo, Massimo Brescia, Maurizio Paolillo, Antonio Pescape', Giuseppe Longo, Giorgio Ventre

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Tags: Algorithms, Astrophysics, CUDA, Data mining, Globular clusters, nVidia, nVidia GeForce GT 540 M

April 3, 2013 by hgpu

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Stephen Won

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Tags: Computer vision, CUDA, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, SIFT, Signal processing, Thesis

February 12, 2013 by hgpu

Efficient Weighted Histogramming on GPUs with CUDA

Mo Xu, Ningyi Xu, Chunshui Zhao, Feng-Hsiung Hsu

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, nVidia GeForce GTX 580

January 8, 2013 by hgpu

Performance study of using the Direct Compute API for implementing Support vector machines on GPUs

Karl Jansson

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Source codes

Tags: Algorithms, Computer science, CUDA, Data mining, DirectX, nVidia, nVidia GeForce GTX 460, OpenCL, Package, Thesis

December 15, 2012 by hgpu

A computationally efficient and scalable approach for privacy preserving kNN classification

Sairam Ravu, P. R. Neelakandan, M. R. Gorai, R. Mukkamala, P. K. Baruah

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Tags: Algorithms, Bloom filter, Computer science, CUDA, Data mining, nVidia, Tesla M2070

December 8, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

Efficient similarity search on multimedia databases

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GTX 330 M, nVidia GeForce GTX 470, nVidia GeForce GTX 550 Ti

November 14, 2012 by hgpu

Empirical analysis of a parallel data mining algorithm on a graphic processor

Davide Berdin

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Tags: Computer science, CUDA, Data mining, Data parallelism, nVidia, nVidia GeForce GTX 580, Thesis

October 20, 2012 by hgpu

Visualization of large multidimensional data sets by using multi-core CPU, GPU and MPI cluster

Piotr Pawliczek, Witold Dzwinel, David A. Yuen

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Tags: Algorithms, Computer science, CUDA, Data mining, MPI, Multidimensional scaling, nVidia, nVidia GeForce 8500 GT, nVidia GeForce 8800 Ultra, nVidia GeForce 9500 GT, nVidia GeForce 9800 GT, nVidia GeForce GT 330 M, nVidia GeForce GTX 260, nVidia GeForce GTX 460, nVidia GeForce GTX 480, Tesla M2050, Visualization

October 6, 2012 by hgpu

A Map-Reduce-Like System for Programming and Optimizing Data-Intensive Computations on Emerging Parallel Architectures

Wei Jiang

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Tags: Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, MapReduce, MPI, nVidia, Tesla C2050, Thesis

September 1, 2012 by hgpu

CUDA-Accelerated Data-Mining for Putative Heteromeric Transcription Factors and Target Genes Using Microarray Gene Expression Profiles

Edward A. Salinas, Amitava Karmaker

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Tags: Algorithms, Biology, Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 590

August 31, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Mr. Scan: Extreme Scale Density-Based Clustering using a Tree-Based Network of GPGPU Nodes

Astrophysical data mining with GPU. A case study: genetic classification of globular clusters

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Efficient Weighted Histogramming on GPUs with CUDA

Performance study of using the Direct Compute API for implementing Support vector machines on GPUs

A computationally efficient and scalable approach for privacy preserving kNN classification

Accelerating MapReduce on a coupled CPU-GPU architecture

Efficient similarity search on multimedia databases

Empirical analysis of a parallel data mining algorithm on a graphic processor

Visualization of large multidimensional data sets by using multi-core CPU, GPU and MPI cluster

A Map-Reduce-Like System for Programming and Optimizing Data-Intensive Computations on Emerging Parallel Architectures

CUDA-Accelerated Data-Mining for Putative Heteromeric Transcription Factors and Target Genes Using Microarray Gene Expression Profiles

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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