high performance computing on graphics processing units: hgpu.org

hgpu.org » Intel Xeon Phi

Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction

Michael Driscoll, Benjamin Brock, Frank Ong, Jonathan Tamir, Hsiou-Yuan Liu, Michael Lustig, Armando Fox, Katherine Yelick

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Tags: CUDA, FFT, Image processing, Image reconstruction, Intel Xeon Phi, Magnetic resonance imaging, Microscopy, MRI, nVidia, nVidia GeForce GTX Titan X, Package

June 13, 2018 by hgpu

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang

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Tags: Computer science, Intel Xeon Phi, Machine learning, OpenMP, Performance, Sparse matrix

June 9, 2018 by hgpu

One machine, one minute, three billion tetrahedra

Celestin Marot, Jeanne Pellerin, Jean-Francois Remacle

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Tags: Computational Geometry, Computer science, Graphics, Intel Xeon Phi, Package

May 26, 2018 by hgpu

Highly Efficient 8-bit Low Precision Inference of Convolutional Neural Networks with IntelCaffe

Jiong Gong, Haihao Shen, Guoming Zhang, Xiaoli Liu, Shane Li, Ge Jin, Niharika Maheshwari, Evarist Fomenko, Eden Segal

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Tags: Caffe, Cloud, Computer science, Deep learning, Intel Xeon Phi, Neural networks, Package

May 26, 2018 by hgpu

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

Beau Johnston, Josh Milthorpe

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Tags: AMD FirePro S9150, AMD Radeon HD 7970, AMD Radeon R9 290X, AMD Radeon R9 Fury X, AMD Radeon RX 480, ATI, Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, OpenCL, Tesla K20, Tesla K40

May 12, 2018 by hgpu

EngineCL: Usability and Performance in Heterogeneous Computing

Raul Nozal, Jose Luis Bosque, Ramon Beivide

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Tags: AMD Radeon R7, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, performance portability, Tesla K20

May 12, 2018 by hgpu

Auto-tuning Streamed Applications on Intel Xeon Phi

Peng Zhang, Jianbin Fang, Tao Tang, Canqun Yang, Zheng Wang

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Tags: Computer science, Intel Xeon Phi, Machine learning, Package, Performance

May 5, 2018 by hgpu

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

Ludomir Oteski, Guillaume De Verdiere, Sylvain Contassot-Vivier, Stephane Vialle, Juliet Ryan

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Tags: Computer science, CUDA, Fluid dynamics, Intel Xeon Phi, nVidia, Tesla K20, Tesla P100

April 15, 2018 by hgpu

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

Yusuke Nagasaka, Satoshi Matsuoka, Ariful Azad, Aydin Buluc

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Tags: Algorithms, Computer science, Intel Xeon Phi, Matrix multiplication, Sparse matrix

April 7, 2018 by hgpu

Optimization of Hierarchical Matrix Computation on GPU

Satoshi Ohshima, Ichitaro Yamazaki, Akihiro Ida, Rio Yokota

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Tags: Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenMP, Tesla P100

March 25, 2018 by hgpu

The VOLNA-OP2 Tsunami Code (Version 1.0)

Istvan Z Reguly, Devaraj Gopinathan, Joakim H Beck, Michael B Giles, Serge Guillas, Frederic Dias

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Tags: CUDA, Earth and Space Sciences, Intel Xeon Phi, nVidia, Package, Tesla P100

March 22, 2018 by hgpu

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Moritz Kreutzer, Georg Hager, Dominik Ernst, Holger Fehske, Alan R. Bishop, Gerhard Wellein

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Tags: Chemistry, Computational Physics, Computer science, CUDA, Intel Xeon Phi, nVidia, OpenMP, Package, Performance, Physics, Quantum Physics, Tesla P100

March 10, 2018 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

One machine, one minute, three billion tetrahedra

Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

EngineCL: Usability and Performance in Heterogeneous Computing

Auto-tuning Streamed Applications on Intel Xeon Phi

Towards a Unified CPU-GPU code hybridization: A GPU Based Optimization Strategy Efficient on Other Modern Architectures

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

Optimization of Hierarchical Matrix Computation on GPU

The VOLNA-OP2 Tsunami Code (Version 1.0)

Chebyshev Filter Diagonalization on Modern Manycore Processors and GPGPUs

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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