high performance computing on graphics processing units: hgpu.org

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Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Jianyu Huang, Chenhan D. Yu, Robert A. van de Geijn

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Package, Tesla V100

September 2, 2018 by hgpu

A study of integer sorting on multicores

Alexandros V. Gerbessiotis

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Tags: Algorithms, Computer science, MPI, Package, Performance, Sorting

September 2, 2018 by hgpu

Kernel Tuner: A search-optimizing GPU code auto-tuner

Ben van Werkhoven

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Tags: AMD Radeon Vega Frontier Edition, ATI, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenCL, Optimization, Package

August 19, 2018 by hgpu

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Daina Moise, Simon J. Pennycook, Kristyn Maschoff, Jason Sewall, Nalini Kumar, Shirley Ho, Mike Ringenburg, Prabhat, Victor Lee

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Tags: Astrophysics, Cosmology, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Package, TensorFlow, Tesla P100

August 19, 2018 by hgpu

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke

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Tags: Computer science, Deep learning, Intel Xeon Phi, OpenMP, Package, Performance

August 19, 2018 by hgpu

Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

Wei Tan, Shiyu Chang, Liana Fong, Cheng Li, Zijun Wang, Liangliang Cao

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Tags: Algorithms, Compression, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan X, Package

August 19, 2018 by hgpu

libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms

Daniel Hanlon, Hamidreza Khalighzadeh, Ravi Reddy Manumachu, Alexey Lastovetsky

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Tags: Cloud, Computer science, CUDA, FPGA, Hybrid computing, Intel Xeon Phi, Matrix multiplication, nVidia, OpenCL, Package

August 19, 2018 by hgpu

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

Leonardo Solis-Vasquez, Andreas Koch

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Tags: Chemistry, FPGA, Molecular dynamics, OpenCL, Package

August 11, 2018 by hgpu

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Raul Puri, Robert Kirby, Nikolai Yakovenko, Bryan Catanzaro

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Tags: Computer science, CUDA, Deep learning, LSTM, Mixed precision, Neural networks, nVidia, Package, Tesla V100, Torch

August 11, 2018 by hgpu

Parallax: Automatic Data-Parallel Training of Deep Neural Networks

Soojeong Kim, Gyeong-In Yu, Hojin Park, Sungwoo Cho, Eunji Jeong, Hyeonmin Ha, Sanha Lee, Joo Seong Jeong, Byung-Gon Chun

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan XP, OpenMPI, Package

August 11, 2018 by hgpu

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

Federico Simmross-Wattenberg, Manuel Rodriguez-Cayetano, Javier Royuela-del-Val, Elena Martin-Gonzalez, Elisa Moya-Saez, Marcos Martin-Fernandez, Carlos Alberola-Lopez

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Tags: Heterogeneous systems, Image processing, Medicine, OpenCL, Package

August 5, 2018 by hgpu

Spatial: A Language and Compiler for Application Accelerators

David Koeplinger, Matthew Feldman, Raghu Prabhakar, Yaqi Zhang, Stefan Hadjis, Ruben Fiszel, Tian Zhao, Luigi Nardi, Ardavan Pedram, Christos Kozyrakis, Kunle Olukotun

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Tags: Compilers, Computer science, Deep learning, DSL, FPGA, HLS, Machine learning, Package, Scala

July 21, 2018 by hgpu

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high performance computing on graphics processing units: hgpu.org

Packages

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

A study of integer sorting on multicores

Kernel Tuner: A search-optimizing GPU code auto-tuner

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Parallax: Automatic Data-Parallel Training of Deep Neural Networks

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

Spatial: A Language and Compiler for Application Accelerators

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