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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

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

Performance Evaluation of Deep Learning Tools in Docker Containers

Pengfei Xu, Shaohuai Shi, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Package, Performance

November 12, 2017 by hgpu

ChainerMN: Scalable Distributed Deep Learning Framework

Takuya Akiba, Keisuke Fukuda, Shuji Suzuki

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Python

November 5, 2017 by hgpu

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

Michel Muller, Takayuki Aoki

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Tags: Earth and Space Sciences, Fortran, nVidia, OpenACC, OpenMP, Package, Tesla K20, Tesla P100, Weather prediction, Weather Prediction Model

October 29, 2017 by hgpu

GooFit 2.0

Henry Schreiner, Christoph Hasse, Bradley Hittle, Himadri Pandey, Michael Sokoloff, Karen Tomko

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Tags: Computer science, CUDA, Mathematical Software, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia GeForce GTX 1080 Ti, Package, Probability, Tesla K40, Tesla P100

October 29, 2017 by hgpu

Parallel Computing for the Inverse of SPD matrix

Yan Shen, Yuxing Dai, Zhiliang Zhu

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Tags: AMD Radeon R9 290, ATI, Computer science, Factorization, Linear Algebra, OpenCL, Package

October 24, 2017 by hgpu

Wilson and Domainwall Kernels on Oakforest-PACS

Issaku Kanamori, Hideo Matsufuru

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Tags: HEP, High Energy Physics - Lattice, Intel Xeon Phi, Mathematical Software, MPI, OpenMP, Package, Physics, QCD

October 21, 2017 by hgpu

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

Adam Stooke, Pieter Abbeel

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Tags: Computer science, CUDA, Data parallelism, Deep learning, nVidia, nVidia DGX-1, Package, Tesla P100, Theano

October 15, 2017 by hgpu

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

Holger Homann, Francois Laenen

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Tags: Benchmarking, Computational Physics, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 755 M, Package, Performance, Physics, Tesla M2050

October 15, 2017 by hgpu

Computing Treewidth on the GPU

Tom C. van der Zanden, Hans L. Bodlaender

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Tags: Algorithms, Bloom filter, Computer science, Graph theory, nVidia, nVidia GeForce GTX 1060, OpenCL, Package

October 3, 2017 by hgpu

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

Carlos Arango, Remy Dernat, John Sanabria

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, Operating systems, Package, Performance, Tesla K20, Virtualization

October 3, 2017 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

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high performance computing on graphics processing units: hgpu.org

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

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

Performance Evaluation of Deep Learning Tools in Docker Containers

ChainerMN: Scalable Distributed Deep Learning Framework

Hybrid Fortran: High Productivity GPU Porting Framework Applied to Japanese Weather Prediction Model

GooFit 2.0

Parallel Computing for the Inverse of SPD matrix

Wilson and Domainwall Kernels on Oakforest-PACS

Synkhronos: a Multi-GPU Theano Extension for Data Parallelism

SoAx: A generic C++ Structure of Arrays for handling Particles in HPC Codes

Computing Treewidth on the GPU

Performance Evaluation of Container-based Virtualization for High Performance Computing Environments

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

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