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Efficient Probabilistic Latent Semantic Indexing using Graphics Processing Unit

Eli Koffi Kouassi, Toshiyuki Amagasaa, Hiroyuki Kitagawa

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Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, Semantic indexing, Tesla C2050

October 26, 2011 by hgpu

Accelerating data mining workloads: current approaches and future challenges in system architecture design

Alok N. Choudhary, Daniel Honbo, Prabhat Kumar, Berkin Ozisikyilmaz, Sanchit Misra, Gokhan Memik

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Tags: Computer science, CUDA, Data mining, FPGA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT

September 30, 2011 by hgpu

Fast Frequent Itemset Mining from Uncertain Databases using GPGPU

Yusuke Kozawa, Toshiyuki Amagasa, Hiroyuki Kitagawa

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, nVidia Quadro FX 4800

September 27, 2011 by hgpu

GPU-based cloud performance for LiDAR data processing

Ramanathan Sugumaran, Dossay Oryspayev, Paul Gray

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Tags: Algorithms, Cloud, Computer science, CUDA, Data mining, Databases, Earth and Space Sciences, nVidia, Performance

September 21, 2011 by hgpu

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Amol Ghoting, Prabhanjan Kambadur, Edwin Pednault, Ramakrishnan Kannan

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Tags: Algorithms, Computer science, Data mining, Machine learning, MapReduce, MPI, OpenCL, Performance, Software Engineering

September 16, 2011 by hgpu

Data-intensive document clustering on graphics processing unit (GPU) clusters

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, GPU cluster, nVidia, nVidia GeForce GTX 280, Tesla C1060

September 13, 2011 by hgpu

Challenges of medical image processing

Ingrid Scholl, Til Aach, Thomas M. Deserno, Torsten Kuhlen

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Tags: Algorithms, Data mining, Grid, Image processing, Medicine, Review, Virtual reality, Visualization

September 11, 2011 by hgpu

Hyperfast Perspective Cone–Beam Backprojection

M. Kachelriess, M. Knaup, O. Bockenbach

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Tags: Algorithms, Cell processor, Computer science, Data mining, Distributed computing, FPGA, Image reconstruction, Nearest neighbour, nVidia, nVidia GeForce FX 5900

August 31, 2011 by hgpu

A new method for GPU based irregular reductions and its application to k-means clustering

Balaji Dhanasekaran, Norman Rubin

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computer science, Data mining, Heterogeneous systems, OpenCL, Performance, Programming techniques

August 21, 2011 by hgpu

Multi- and many-core data mining with adaptive sparse grids

Alexander Heinecke, Dirk Pfluger

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Tags: Algorithms, Computer science, Data mining, Mathematical Software, nVidia, nVidia GeForce GTX 470, OpenCL, Performance, Presentation

August 21, 2011 by hgpu

Approaches for parallelizing reductions on modern GPUs

Xin Huo, V.T. Ravi, Wenjing Ma, G. Agrawal

Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, Nearest neighbour, nVidia

August 10, 2011 by hgpu

Hyperfast Parallel–Beam Backprojection

Marc Kachelriess, Michael Knaup, Olivier Bockenbach

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Tags: Algorithms, Cell processor, Computer science, Data mining, Distributed computing, Image reconstruction, Nearest neighbour, Performance, Tomography

August 2, 2011 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

Efficient Probabilistic Latent Semantic Indexing using Graphics Processing Unit

Accelerating data mining workloads: current approaches and future challenges in system architecture design

Fast Frequent Itemset Mining from Uncertain Databases using GPGPU

NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce

Data-intensive document clustering on graphics processing unit (GPU) clusters

Challenges of medical image processing

Hyperfast Perspective Cone–Beam Backprojection

A new method for GPU based irregular reductions and its application to k-means clustering

Multi- and many-core data mining with adaptive sparse grids

Approaches for parallelizing reductions on modern GPUs

Hyperfast Parallel–Beam Backprojection

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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