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Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Joao Paulo Tarasconi Ruschel

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, OpenCL, OpenMP, Package, Performance, Tesla K80, Thesis

January 26, 2017 by hgpu

A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Rui Fan, Ke Xu, Jichang Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980, Package

January 26, 2017 by hgpu

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean

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Tags: Algorithms, Computer science, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, TensorFlow, Tesla K40

January 26, 2017 by hgpu

Deep Learning for Computational Chemistry

Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu

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Tags: Algorithms, Chemistry, Computational chemistry, Computer science, Deep learning, Machine learning, Neural networks, Review

January 19, 2017 by hgpu

Xeon Phi: A comparison between the newly introduced MIC architecture and a standard CPU through three types of problems

Joakim Kristiansen

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Tags: Algorithms, Computer science, Intel Xeon Phi, Package, Sorting, Thesis

January 19, 2017 by hgpu

Parallelizing Exact and Approximate String Matching via Inclusive Scan on a GPU

Yasuaki Mitani, Fumihiko Ino, Kenichi Hagihara

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Package, String matching

January 19, 2017 by hgpu

Light Loss-Less Data Compression, with GPU Implementation

Shunji Funasaka, Koji Nakano, Yasuaki Ito

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080

January 19, 2017 by hgpu

Application of GPU Computing to Some Urban Traffic Problems

Walid Abdala Rfaei Jradi

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Tags: Algorithms, AMD Radeon R9 290X, ATI, Computer science, OpenCL, Thesis, Vehicular traffic

January 16, 2017 by hgpu

An N log N Parallel Fast Direct Solver for Kernel Matrices

Chenhan D. Yu, William B. March, George Biros

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Tags: Algorithms, Computational Complexity, Computer science, Factorization, Intel Xeon Phi, Machine learning, Package, Performance

January 16, 2017 by hgpu

Decoding with Finite-State Transducers on GPUs

Arturo Argueta, David Chiang

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Tags: Algorithms, Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX Titan X, Package, Speech recognition, Tesla K40, Tesla P100

January 16, 2017 by hgpu

Parallelization of BVH and BSP on the GPU

Martin Imre

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, Raytracing, Rendering, Sorting, Thesis, Visualization

January 10, 2017 by hgpu

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Daniel George, E. A. Huerta

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Tags: Algorithms, Artificial intelligence, Astrophysics, CUDA, Deep learning, Filtering, Gravitation, Gravitational waves, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Physics, Signal processing, Tesla K40, Tesla P100

January 4, 2017 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

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Deep Learning for Computational Chemistry

Xeon Phi: A comparison between the newly introduced MIC architecture and a standard CPU through three types of problems

Parallelizing Exact and Approximate String Matching via Inclusive Scan on a GPU

Light Loss-Less Data Compression, with GPU Implementation

Application of GPU Computing to Some Urban Traffic Problems

An N log N Parallel Fast Direct Solver for Kernel Matrices

Decoding with Finite-State Transducers on GPUs

Parallelization of BVH and BSP on the GPU

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

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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