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Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

Flavio Vella, Giancarlo Carbone, Massimo Bernaschi

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Graph theory, nVidia, OpenMPI, Tesla K20, Tesla K80

February 3, 2016 by hgpu

Edge coloring in unstructured CFD codes

Andrew Giuliani, Lilia Krivodonova

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Tags: Algorithms, Computer science, Fluid dynamics, nVidia, nVidia GeForce GTX 580

February 3, 2016 by hgpu

Fast, Realistic Terrain Synthesis

Justin Crause

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 660 Ti, Thesis

February 2, 2016 by hgpu

Hardware Acceleration for Unstructured Big Data and Natural Language Processing

Prateek Tandon

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Tags: ASIC, big data, Computer science, FPGA, Hadoop, hardware acceleration, Machine learning, MapReduce, NLP, Thesis

February 2, 2016 by hgpu

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

Yifei Li

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Tags: Algorithms, Clustering, Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, OpenMP, Package, Thesis, Visualization

February 2, 2016 by hgpu

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

David Webb

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Tags: Bayesian, Computer science, Computer vision, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Jetson TK1, SoC, Thesis

February 2, 2016 by hgpu

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Raja H. Singh, Lee Barford, Frederick Harris Jr.

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 780

February 1, 2016 by hgpu

Deep learning review and its applications

Andoni Azkarate Saiz

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 660, Review, Thesis

February 1, 2016 by hgpu

A power-aware symbiotic scheduling algorithm for concurrent GPU kernels

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Task scheduling, Tesla K20

February 1, 2016 by hgpu

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

Benoit Liquet, Leonardo Bottolo, Gianluca Campanella, Sylvia Richardson, Marc Chadeau-Hyam

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Tags: Bayesian, Computer science, CUDA, CULA, nVidia, Package

February 1, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

High-Performance Tensor Contractions for GPUs

A. Abdelfattah, M. Baboulin, V. Dobrev, J. Dongarra, C. Earl, J. Falcou, A. Haidar, I. Karlin, Tz. Kolev, I. Masliah, S. Tomov

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Tags: Algorithms, Code generation, Computer science, CUDA, FEM, Finite element method, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Tesla K40

January 29, 2016 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Algorithms and Heuristics for Scalable Betweenness Centrality Computation on Multi-GPU Systems

Edge coloring in unstructured CFD codes

Fast, Realistic Terrain Synthesis

Hardware Acceleration for Unstructured Big Data and Natural Language Processing

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

Accelerating the Critical Line Algorithm for Portfolio Optimization Using GPUs

Deep learning review and its applications

A power-aware symbiotic scheduling algorithm for concurrent GPU kernels

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

High-Performance Tensor Contractions for GPUs

Recent source codes

tdg-benchs: benchmarks used to test the performance of taskgraph

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

Most viewed papers (last 30 days)