high performance computing on graphics processing units: hgpu.org

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Ansor: Generating High-Performance Tensor Programs for Deep Learning

Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica

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Tags: ARM, Compilers, Computer science, CUDA, Deep learning, Neural networks, nVidia, Optimization, Search strategies, Tesla V100

June 21, 2020 by hgpu

Parallel Execution of the ASP Computation – an Investigation on GPUs

Agostino Dovier, Andrea Formisano, Enrico Pontelli, Flavio Vella

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 640, nVidia GeForce GTX Titan X, Search strategies, Tesla C2075, Tesla K20, Tesla K80

September 5, 2015 by hgpu

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Michael Vollmer, Bo Joel Svensson, Eric Holk, Ryan Newton

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Tags: Computer science, CUDA, nVidia, Performance, Search strategies, Tesla K40

June 7, 2015 by hgpu

Extended Dynamic Programming and Fast Multidimensional Search Algorithm for Energy Minization in Stereo and Motion

Mikhail G. Mozerov

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Tags: Algorithms, Computer science, Computer vision, Search strategies

October 31, 2014 by hgpu

An Improved Parallel Algorithm using GPU for Siting Observers on Terrain

Guilherme C. Pena, Marcus V. A. Andrade, Salles V. G. Magalhaes, W. R. Franklin, Chaulio R. Ferreira

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Tags: Algorithms, Computer science, CUDA, nVidia, Search strategies, Tesla K20

June 6, 2014 by hgpu

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Ricardo Javier Barrientos Rojel

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Source codes

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Search strategies, Tesla C1060, Tesla M2070, Thesis

December 6, 2013 by hgpu

Parallelizing General Histogram Application for CUDA Architectures

Ugljesa Milic, Isaac Gelado, Nikola Puzovic, Alex Ramirez, Milo Tomasevic

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Tags: Algorithms, CUDA, Image processing, nVidia, Search strategies, Tesla C2070, Tesla K20

June 17, 2013 by hgpu

Depth-First Search versus Jurema Search on GPU Branch-and-Bound Algorithms: a case study

Tiago Carneiro, Ricardo Nobre, Marcos Negreiros

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Optimization, Search strategies

March 23, 2013 by hgpu

Parallel one-versus-rest SVM training on the GPU

Sander Dieleman, Aaron van den Oord, Benjamin Schrauwen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 540 M, nVidia GeForce GTX 560 Ti, Search strategies, Tesla C1060

January 4, 2013 by hgpu

Large scale parallel state space search utilizing graphics processing units and solid state disks

Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Probabilistic model checking, Search strategies, Thesis

May 11, 2012 by hgpu

Automatic Discovery of Algorithms for Multi-Agent Systems

Sjors van Berkel, Daniel Turi, Andrei Pruteanu, Stefan Dulman

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Search strategies

May 9, 2012 by hgpu

Multi Agent Navigation on the GPU

Avi Bleiweiss

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Tags: Artificial intelligence, Computer science, CUDA, Games, Hashing, nVidia, nVidia GeForce GTX 280, Search strategies

March 11, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Ansor: Generating High-Performance Tensor Programs for Deep Learning

Parallel Execution of the ASP Computation – an Investigation on GPUs

Meta-Programming and Auto-Tuning in the Search for High Performance GPU Code

Extended Dynamic Programming and Fast Multidimensional Search Algorithm for Energy Minization in Stereo and Motion

An Improved Parallel Algorithm using GPU for Siting Observers on Terrain

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Parallelizing General Histogram Application for CUDA Architectures

Depth-First Search versus Jurema Search on GPU Branch-and-Bound Algorithms: a case study

Parallel one-versus-rest SVM training on the GPU

Large scale parallel state space search utilizing graphics processing units and solid state disks

Automatic Discovery of Algorithms for Multi-Agent Systems

Multi Agent Navigation on the GPU

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

Most viewed papers (last 30 days)