high performance computing on graphics processing units: hgpu.org

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Accelerating Lattice QCD Multigrid on GPUs Using Fine-Grained Parallelization

M. A. Clark, Balint Joo, Alexei Strelchenko, Michael Cheng, Arjun Gambhir, Richard Brower

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Tags: Algorithms, Computational Physics, CUDA, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla K20

December 26, 2016 by hgpu

Streaming GPU Singular Value and Dynamic Mode Decompositions

Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton

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Tags: Algorithms, Computer vision, CUDA, Mathematics, Matrix multiplication, Numerical Analysis, nVidia, Sparse matrix, Tesla K40

December 26, 2016 by hgpu

Performance Optimisation of Smoothed Particle Hydrodynamics Algorithms for Multi/Many-Core Architectures

Fabio Baruffa, Luigi Iapichino, Nicolay J. Hammer, Vasileios Karakasis

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Tags: Algorithms, Astrophysics, Computational Physics, Computer science, Instrumentation and Methods for Astrophysics, Intel Xeon Phi, OpenMP, Performance, Physics

December 20, 2016 by hgpu

gpuSPHASE – A shared memory caching implementation for 2D SPH using CUDA

Daniel Winkler, Michael Meister, Massoud Rezavand, Wolfgang Rauch

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, Physics

December 20, 2016 by hgpu

Efficient Realization of Householder Transform through Algorithm-Architecture Co-design for Acceleration of QR Factorization

Farhad Merchant, Tarun Vatwani, Anupam Chattopadhyay, Soumyendu Raha, S K Nandy, Ranjani Narayan

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Tags: Algorithms, Computer science, CUDA, Factorization, FPGA, Linear Algebra, Mathematical Software, Matrix multiplication, nVidia, Performance, Tesla C2050

December 17, 2016 by hgpu

Toward Automatic Translation: From OpenACC to OpenMP 4

Nawrin Sultana

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Tags: Algorithms, Code generation, Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla K40, Thesis

December 17, 2016 by hgpu

Speedup for quantum optimal control from GPU-based automatic differentiation

Nelson Leung, Mohamed Abdelhafez, Jens Koch, David I. Schuster

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Source codes

Tags: Algorithms, CUDA, Deep learning, Mesoscale and Nanoscale Physics, Numerical simulation, nVidia, Package, Physics, Python, Quantum Physics, TensorFlow, Tesla K40

December 17, 2016 by hgpu

GPU-accelerated algorithms for many-particle continuous-time quantum walks

Enrico Piccinini, Claudia Benedetti, Ilaria Siloi, Matteo G. A. Paris, Paolo Bordone

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Tags: Algorithms, Benchmarking, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 980, OpenMP, Physics, Quantum computing, Quantum Physics, Quantum walks, Tesla K40, Tesla K80, Tesla M2050

December 6, 2016 by hgpu

A Real-time Single Pulse Detection Algorithm for GPUs

Karel Adamek, Wesley Armour

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Tags: Algorithms, Astrophysics, CUDA, Filtering, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan X, Package, Signal processing

December 3, 2016 by hgpu

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Pedro Miguel Marques Pereira

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, ATI Radeon HD 7970, Compression, Computer science, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570 M, nVidia GeForce GTX 680, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan Black, nVidia Jetson TK1, OpenCL, OpenMP, Thesis

November 30, 2016 by hgpu

dMath: Distributed Linear Algebra for DL

Steven Eliuk, Cameron Upright, Hars Vardhan, Stephen Walsh, Trevor Gale

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Tags: Algorithms, Computer science, CUDA, Deep learning, Linear Algebra, Matrix multiplication, MPI, Neural networks, nVidia, Tesla K80

November 25, 2016 by hgpu

High performance pattern matching and data remanence on graphics processing units

X. Bellekens

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Tags: Aho Corasick, Algorithms, amazon, BMH, CUDA, Digital Forensic, forensic, GPU, pattern matching, PFAC, remanence, Sequence matching, String matching, Suffix Tree, Tesla K20, Tesla K20c

November 22, 2016 by xhgpu

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

Programming

Accelerating Lattice QCD Multigrid on GPUs Using Fine-Grained Parallelization

Streaming GPU Singular Value and Dynamic Mode Decompositions

Performance Optimisation of Smoothed Particle Hydrodynamics Algorithms for Multi/Many-Core Architectures

gpuSPHASE – A shared memory caching implementation for 2D SPH using CUDA

Efficient Realization of Householder Transform through Algorithm-Architecture Co-design for Acceleration of QR Factorization

Toward Automatic Translation: From OpenACC to OpenMP 4

Speedup for quantum optimal control from GPU-based automatic differentiation

GPU-accelerated algorithms for many-particle continuous-time quantum walks

A Real-time Single Pulse Detection Algorithm for GPUs

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

dMath: Distributed Linear Algebra for DL

High performance pattern matching and data remanence on graphics processing units

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

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