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Bitmap Filter: Speeding up Exact Set Similarity Joins with Bitwise Operations

Edans F. O. Sandes, George Teodoro, Alba C. M. A. Melo

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Tags: Algorithms, Computer science, CUDA, Databases, Filtering, nVidia, nVidia GeForce GTX 980 Ti

November 21, 2017 by hgpu

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Stefan Rosenberger, Gundolf Haase

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, OpenACC, OpenMP, Sparse matrix

November 21, 2017 by hgpu

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Allen Rush, Ashish Sirasao, Mike Ignatowski

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Machine learning, OpenCL

November 21, 2017 by hgpu

Hydra: a C++11 framework for data analysis in massively parallel platforms

A. A. Alves Junior, M. D. Sokoloff

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Tags: Computational Physics, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

November 16, 2017 by hgpu

Launch-time Optimization of OpenCL Kernels

Andrew Siu Doug Lee

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Tags: Computer science, LLVM, nVidia, nVidia GeForce GTX 780, OpenCL, Performance, Thesis

November 16, 2017 by hgpu

Deep learning for galaxy surface brightness profile fitting

D. Tuccillo, M. Huertas-Company, E. Decenciere, S. Velasco-Forero, H. Dominguez Sanchez, P. Dimauro

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Tags: Astrophysics, Deep learning, Keras, nVidia, nVidia GeForce GTX Titan X

November 16, 2017 by hgpu

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Wim Vanderbauwhede, Gavin Davidson

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Tags: Compilers, Computer science, Fortran, Heterogeneous systems, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Package

November 16, 2017 by hgpu

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

Peter Boyle, Michael Chuvelev, Guido Cossu, Christopher Kelly, Christoph Lehner, Lawrence Meadows

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Machine learning, MPI, OpenMP, Package, Performance, Physics

November 16, 2017 by hgpu

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Przemyslaw Stpiczynski

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Tags: Algorithms, Computer science, Intel Xeon Phi, Monte Carlo integration, nVidia, OpenACC, OpenMP, Pseudo-random number generators, Tesla K40

November 12, 2017 by hgpu

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Leiming Yu, Fanny Nina-Paravecino, David Kaeli, Qianqian Fang

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Tags: Algorithms, AMD R9 Nano, AMD Radeon RX 480, ATI, Computational Physics, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 590, nVidia GeForce GTX 980 Ti, nVidia GeForce GTX Titan X, OpenCL, Package, Physics

November 12, 2017 by hgpu

Best Practice Guide – GPGPU

Momme Allalen, Vali Codreanu, Nevena Ilieva-Litova, Alan Gray, Anders Sjostrom, Volker Weinberg

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Tags: Computer science, CUDA, OpenACC, OpenCL, OpenMP, Review

November 12, 2017 by hgpu

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Gaurav Mitra

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Tags: ARM, Benchmarking, Computer science, DSP, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Jetson TK1, nVidia Tegra TX1, OpenCL, SoC, Thesis

November 12, 2017 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

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

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

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high performance computing on graphics processing units: hgpu.org

Applications

Bitmap Filter: Speeding up Exact Set Similarity Joins with Bitwise Operations

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Hydra: a C++11 framework for data analysis in massively parallel platforms

Launch-time Optimization of OpenCL Kernels

Deep learning for galaxy surface brightness profile fitting

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

Accelerating HPC codes on Intel(R) Omni-Path Architecture networks: From particle physics to Machine Learning

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

Best Practice Guide – GPGPU

Low-power System-on-Chip Processors for Energy Efficient High Performance Computing: The Texas Instruments Keystone II

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

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

PyOMP: OpenMP for Python in Numba

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