high performance computing on graphics processing units: hgpu.org

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Parallel Level set algorithm with MPI and accelerated on GPU

Zhenlin Wang

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Tags: Computational Physics, CUDA, Finite difference, MPI, nVidia, Package, PDEs, Physics

December 17, 2016 by hgpu

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Florencio Balboa Usabiaga, Blaise Delmotte, Aleksandar Donev

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Tags: Condensed matter, CUDA, nVidia, Package, Physics, pyCUDA, Soft Condensed Matter

December 6, 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

GeantV: from CPU to accelerators

G. Amadio, A. Ananya, J. Apostolakis, A. Arora, M. Bandieramonte, A. Bhattacharyya, C. Bianchini, R. Brun, P. Canal, F. Carminati, L. Duhem, D. Elvira, A. Gheata, M. Gheata, I. Goulas, R. Iope, S. Jun, G. Lima, A. Mohanty, T. Nikitina, M. Novak, W. Pokorski, A. Ribon, R. Sehgal, O. Shadura, S. Vallecorsa, S. Wenzel, Y. Zhang

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Tags: CUDA, HEP, High Energy Physics - Phenomenology, Intel Xeon Phi, nVidia, Physics, Tesla K20

December 3, 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 and Evaluation of VLPL-S Particle-in-cell Code on Knights Landing

Dandi Ding, Minhua Wen, Shan Zhou, Min Chen, James Lin

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Tags: Intel Xeon Phi, MPI, OpenMP, Particle-in-cell methods, Physics, Plasma physics

November 23, 2016 by hgpu

Celeris: A GPU-accelerated open source software with a Boussinesq-type wave solver for real-time, interactive simulation and visualization

Sasan Tavakkol, Patrick Lynett

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Tags: cfd, DirectX, Finite difference, Fluid dynamics, HLSL, nVidia, nVidia Quadro K600, Package, Physics, Rendering, Visualization

November 22, 2016 by hgpu

GPU-accelerated Red Blood Cells Simulations with Transport Dissipative Particle Dynamics

Ansel L. Blumers, Yu-Hang Tang, Zhen Li, Xuejin Li, George E. Karniadakis

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Tags: Biological Physics, Computational Physics, CUDA, MPI, nVidia, Package, Physics, Tesla K20

November 22, 2016 by hgpu

Lattice QCD simulations using the OpenACC platform

Pushan Majumdar

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Tags: CUDA, HEP, High Energy Physics - Lattice, nVidia, OpenACC, Physics, QCD, Tesla X2090

November 19, 2016 by hgpu

Data Acquisition with GPUs: The DAQ for the Muon g-2 Experiment at Fermilab

W. Gohn

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Tags: CUDA, Data acquisition, nVidia, Physics, Tesla K40

November 16, 2016 by hgpu

Performance Portability of the Aeras Atmosphere Model to Next Generation Architectures using Kokkos

Jerry Watkins, Irina Tezaur

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Tags: CUDA, Earth and Space Sciences, MPI, nVidia, OpenMP, performance portability, Physics, Tesla K20, Tesla K80

November 8, 2016 by hgpu

grim: A Flexible, Conservative Scheme for Relativistic Fluid Theories

Mani Chandra, Francois Foucart, Charles F. Gammie

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Tags: Astrophysics, Magnetohydrodynamics, nVidia, OpenCL, Package, Physics, Tesla K20

November 5, 2016 by hgpu

Deep Learning for Compilers

PyMatting: A Python Library for Alpha Matting

vilib: CUDA Visual Library by RPG

Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO

Error-bounded Lossy Data Compressor (for floating-point/integer datasets)

Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: a Python library for energy-based machine learning models

Learnergy: Energy-based Machine Learners

Towards automated kernel selection in machine learning systems: A SYCL case study

CLFuzz

Automated test generation for OpenCL kernels using fuzzing and constraint solving

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel Level set algorithm with MPI and accelerated on GPU

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

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

GeantV: from CPU to accelerators

A Real-time Single Pulse Detection Algorithm for GPUs

Optimization and Evaluation of VLPL-S Particle-in-cell Code on Knights Landing

Celeris: A GPU-accelerated open source software with a Boussinesq-type wave solver for real-time, interactive simulation and visualization

GPU-accelerated Red Blood Cells Simulations with Transport Dissipative Particle Dynamics

Lattice QCD simulations using the OpenACC platform

Data Acquisition with GPUs: The DAQ for the Muon g-2 Experiment at Fermilab

Performance Portability of the Aeras Atmosphere Model to Next Generation Architectures using Kokkos

grim: A Flexible, Conservative Scheme for Relativistic Fluid Theories

Recent source codes

Deep Learning for Compilers

PyMatting: A Python Library for Alpha Matting

vilib: CUDA Visual Library by RPG

Error-bounded Lossy Data Compressor (for floating-point/integer datasets)

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: a Python library for energy-based machine learning models

Towards automated kernel selection in machine learning systems: A SYCL case study

CLFuzz

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Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019