high performance computing on graphics processing units: hgpu.org

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Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

Mei Wen, Da-fei Huang, Chang-qing Xun, Dong Chen

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Performance

July 20, 2015 by hgpu

Adaptive parallelism mapping in dynamic environments using machine learning

Murali Krishna Emani

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Tags: Computer science, Machine learning, OpenMP, Performance, Thesis

July 15, 2015 by hgpu

Evaluating the capabilities of the Xeon Phi platform in the context of software-only, thread-level speculation

Alvaro Estebanez, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Benchmarking, Computer science, Intel Xeon Phi, Performance

July 13, 2015 by hgpu

Characterizing and Optimizing Irregular Applications on Graphics Processing Units

Tao Zhang

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance, Thesis

July 10, 2015 by hgpu

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Alexey Lastovetsky, Lukasz Szustak, Roman Wyrzykowski

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Tags: Computer science, Intel Xeon Phi, Performance

July 8, 2015 by hgpu

Autotuning OpenACC Work Distribution via Direct Search

Calvin Montgomery, Jeffrey L. Overbey, Xuechao Li

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Source codes

Tags: Computer science, MPI, nVidia, OpenACC, Package, Performance, Python, Tesla K20

July 8, 2015 by hgpu

Sorting and Permuting without Bank Conflicts on GPUs

Peyman Afshani, Nodari Sitchinava

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Tags: Algorithms, Computer science, Performance, Sorting

July 8, 2015 by hgpu

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

Carsten Kutzner, Szilard Pall, Martin Fechner, Ansgar Esztermann, Bert L. de Groot, Helmut Grubmuller

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Tags: Benchmarking, Biological Physics, Biomolecules, Computational Physics, Computer science, Molecular dynamics, Molecular simulation, MPI, nVidia, Package, Performance, Tesla K20, Tesla K40

July 6, 2015 by hgpu

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

David Couturier, Michel R. Dagenais

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Tags: Computer science, Intel HD 4600, OpenCL, Performance

July 6, 2015 by hgpu

Texture Cache Approximation on GPUs

Mark Sutherland, Joshua San Miguel, Natalie Enright Jerger

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Performance

July 3, 2015 by hgpu

Accelerating DNA Sequence Analysis using Intel Xeon Phi

Suejb Memeti, Sabri Pllana

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

July 1, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

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

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Improving performance portability for GPU-specific OpenCL kernels on multi-core/many-core CPUs by analysis-based transformations

Adaptive parallelism mapping in dynamic environments using machine learning

Evaluating the capabilities of the Xeon Phi platform in the context of software-only, thread-level speculation

Characterizing and Optimizing Irregular Applications on Graphics Processing Units

Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing

Autotuning OpenACC Work Distribution via Direct Search

Sorting and Permuting without Bank Conflicts on GPUs

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

Texture Cache Approximation on GPUs

Accelerating DNA Sequence Analysis using Intel Xeon Phi

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Recent source codes

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

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

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