high performance computing on graphics processing units: hgpu.org

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Exact diagonalization of quantum lattice models on coprocessors

Topi Siro, Ari Harju

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Tags: Condensed matter, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, OpenMP, Physics, Tesla K40

November 4, 2015 by hgpu

Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

Vahid Noormofidi, Susan R. Atlas, Huaiyu Duan

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Tags: Astrophysics, Computer science, Intel Xeon Phi, MPI, OpenMP, Performance

October 11, 2015 by hgpu

Parallel Graph Algorithms on the Xeon Phi Coprocessor

Dennis Felsing

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Tags: Algorithms, Computer science, Graph theory, Intel Xeon Phi, OpenMP, Thesis, Visualization

October 6, 2015 by hgpu

The Dynamical Kernel Scheduler – Part 1

Andreas Adelmann, Uldis Locans, Andreas Suter

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Tags: Algorithms, Computational Physics, CUDA, FFT, Intel Xeon Phi, Monte Carlo simulation, nVidia, OpenCL, OpenMP, Physics

September 29, 2015 by hgpu

Parallel waveform extraction algorithms for the Cherenkov Telescope Array Real-Time Analysis

Andrea Zoli, Andrea Bulgarelli, Adriano De Rosa, Alessio Aboudan, Valentina Fioretti, Giovanni De Cesare, Ramin Marx

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Tags: Astrophysics, FPGA, nVidia, OpenCL, OpenMP, Tesla K40

September 9, 2015 by hgpu

A Performance Comparison of Algebraic Multigrid Preconditioners on CPUs, GPUs, and Xeon Phis

K. Rupp, J. Weinbub, F. Rudolf, A. Morhammer, T. Grasser, A. Jungel

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Tags: AMD FirePro W9100, ATI, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, OpenMP, Performance, Tesla K20

September 9, 2015 by hgpu

Accelerating Multiple Compound Comparison Using LINGO-based Load-Balancing Strategies on Multi-GPUs

Chun-Yuan Lin, Chung-Hung Wang, Che-Lun Hung, Yu-Shiang Lin

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Tags: Computer science, CUDA, load balancing, nVidia, OpenMP, Tesla K20

September 8, 2015 by hgpu

Accelerated Deep Learning using Intel Xeon Phi

Andre Viebke

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Tags: Computer science, Computer vision, Deep learning, Intel Xeon Phi, Machine learning, Neural networks, OpenMP, Thesis

August 27, 2015 by hgpu

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

Andre Eliasson, Pontus Franzen

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Tags: Algorithms, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 970, nVidia Quadro K4000, OpenMP, Thesis

August 12, 2015 by hgpu

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Terry Cojean, Abdou Guermouche, Andra Hugo, Raymond Namyst, Pierre-Andre Wacrenier

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, OpenMP, Task scheduling, Tesla K40

August 5, 2015 by hgpu

Optimized Event-Driven Runtime Systems for Programmability and Performance

Sagnak Tasrlar

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Tags: Computer science, Intel Xeon Phi, OpenMP, Performance, Thesis

August 3, 2015 by hgpu

Multi-GPU Parallel Computing and Task Scheduling under Virtualization

Yujie Zhang, Jiabin Yuan, Xiangwen Lu, Xingfang Zhao

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Tags: Computer science, CUDA, nVidia, OpenMP, Task scheduling, Tesla C2050, Virtualization

August 3, 2015 by hgpu

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

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high performance computing on graphics processing units: hgpu.org

Exact diagonalization of quantum lattice models on coprocessors

Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

Parallel Graph Algorithms on the Xeon Phi Coprocessor

The Dynamical Kernel Scheduler – Part 1

Parallel waveform extraction algorithms for the Cherenkov Telescope Array Real-Time Analysis

A Performance Comparison of Algebraic Multigrid Preconditioners on CPUs, GPUs, and Xeon Phis

Accelerating Multiple Compound Comparison Using LINGO-based Load-Balancing Strategies on Multi-GPUs

Accelerated Deep Learning using Intel Xeon Phi

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

Exploiting two-level parallelism by aggregating computing resources in task-based applications over accelerator-based machines

Optimized Event-Driven Runtime Systems for Programmability and Performance

Multi-GPU Parallel Computing and Task Scheduling under Virtualization

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

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