high performance computing on graphics processing units: hgpu.org

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Parle: parallelizing stochastic gradient descent

Pratik Chaudhari, Carlo Baldassi, Riccardo Zecchina, Stefano Soatto, Ameet Talwalkar

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Tags: Algorithms, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Performance, Torch

July 5, 2017 by hgpu

GPU-acceleration for Large-scale Tree Boosting

Huan Zhang, Si Si, Cho-Jui Hsieh

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Tags: Algorithms, AMD Radeon RX 480, ATI, Computer science, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

July 2, 2017 by hgpu

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Yuechao Lu, Fumihiko Ino, Yasuyuki Matsushita

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Tags: Algorithms, Computer science, Computer vision, CUDA, Linear Algebra, Machine learning, nVidia, Tesla P100

June 25, 2017 by hgpu

Rgtsvm: Support Vector Machines on a GPU in R

Zhong Wang, Tinyi Chu, Lauren A Choate, Charles G Danko

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Tags: Computer science, CUDA, Machine learning, nVidia, Package, R, Tesla K20

June 21, 2017 by hgpu

Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

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Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

CLBlast: A Tuned OpenCL BLAS Library

Cedric Nugteren

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Tags: AMD Radeon R9 M370X, ARM, ATI, BLAS, Computer science, Intel HD 5100, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan X, OpenCL, Package

May 18, 2017 by hgpu

Real-Time Adaptive Image Compression

Oren Rippel, Lubomir Bourdev

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Tags: Algorithms, Compression, Computer science, Computer vision, Machine learning, nVidia, nVidia GeForce GTX 980 Ti

May 18, 2017 by hgpu

Deep Learning in the Automotive Industry: Applications and Tools

Andre Luckow, Matthew Cook, Nathan Ashcraft, Edwin Weill, Emil Djerekarov, Bennie Vorster

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Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia GRID K520, Performance

May 2, 2017 by hgpu

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Ben Taylor, Vicent Sanz Marco, Zheng Wang

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Tags: ARM, Computer science, Energy-efficient computing, Heterogeneous systems, Machine learning, OpenCL

April 30, 2017 by hgpu

Parallel Multi Channel Convolution using General Matrix Multiplication

Aravind Vasudevan, Andrew Anderson, David Gregg

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Tags: Algorithms, ARM, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia Tegra TX1, Performance

April 17, 2017 by hgpu

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Yusuf Guven Toprakkiran

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Thesis

April 11, 2017 by hgpu

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

Yuan Wen, Michael F.P. O'Boyle

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Tags: AMD Radeon HD 7970, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 780, OpenCL

April 3, 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

Parle: parallelizing stochastic gradient descent

GPU-acceleration for Large-scale Tree Boosting

High-Performance Out-of-core Block Randomized Singular Value Decomposition on GPU

Rgtsvm: Support Vector Machines on a GPU in R

Implementing Efficient, Portable Computations for Machine Learning

CLBlast: A Tuned OpenCL BLAS Library

Real-Time Adaptive Image Compression

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Parallel Multi Channel Convolution using General Matrix Multiplication

Machine Learning from Streaming Data in Heterogeneous Computing Environments

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

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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