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GPU Virtualization and Scheduling Methods: A Comprehensive Survey

Cheol-Ho Hong, Ivor Spence, Dimitrios S. Nikolopoulos

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Tags: Cloud, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Review, Virtualization

June 9, 2018 by hgpu

Fast Locality Sensitive Hashing for Beam Search on GPU

Xing Shi, Shizhen Xu, Kevin Knight

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Data Structures and Algorithms, Hashing, NLP, nVidia, Tesla K20

June 9, 2018 by hgpu

Marian: Cost-effective High-Quality Neural Machine Translation in C++

Marcin Junczys-Dowmunt, Kenneth Heafield, Hieu Hoang, Roman Grundkiewicz, Anthony Aue

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Tags: Computer science, CUDA, Machine learning, NLP, nVidia, Package

June 2, 2018 by hgpu

Learning to Optimize Tensor Programs

Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

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Tags: ARM, Computer science, CUDA, Deep learning, Matrix multiplication, nVidia, nVidia GeForce GTX Titan X

May 26, 2018 by hgpu

Glow: Graph Lowering Compiler Techniques for Neural Networks

Nadav Rotem, Jordan Fix, Saleem Abdulrasool, Summer Deng, Roman Dzhabarov, James Hegeman, Roman Levenstein, Bert Maher, Satish Nadathur, Jakob Olesen, Jongsoo Park, Artem Rakhov, Misha Smelyanskiy

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Tags: Code generation, Compilers, Computer science, CUDA, Deep learning, Heterogeneous systems, Linear Algebra, Machine learning, Neural networks, nVidia, Package

May 20, 2018 by hgpu

Neural Multi-scale Image Compression

Ken Nakanishi, Shin-ichi Maeda, Takeru Miyato, Daisuke Okanohara

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Tags: Compression, Computer vision, CUDA, Deep learning, Image processing, Machine learning, nVidia

May 20, 2018 by hgpu

Deep Neural Machine Translation with Weakly-Recurrent Units

Mattia Antonino Di Gangi, Marcello Federico

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Tags: Computer science, CUDA, NLP, nVidia, nVidia GeForce GTX 1080, Package, RNN, Tesla K80, Torch

May 20, 2018 by hgpu

Modeling and Evaluation of Synchronous Stochastic Gradient Descent in Distributed Deep Learning on Multiple GPUs

Shaohuai Shi, Qiang Wang, Xiaowen Chu, Bo Li

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, Package, Performance, Tesla K80

May 12, 2018 by hgpu

Tiramisu: A Code Optimization Framework for High Performance Systems

Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane, Emanuele Del Sozzo, Patricia Suriana, Shoaib Kamil, Saman Amarasinghe

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Tags: Algorithms, Code generation, Computer science, CUDA, Distributed computing, FPGA, Heterogeneous systems, Linear Algebra, LLVM, MPI, nVidia, OpenMPI, Tesla K40

May 5, 2018 by hgpu

A Comparative Study on Exact Triangle Counting Algorithms on the GPU

Leyuan Wang, Yangzihao Wang, Carl Yang, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Filtering, Graph theory, nVidia, Sparse matrix, Tesla K40

April 28, 2018 by hgpu

Accelerating Blockchain Search of Full Nodes Using GPUs

Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 980 Ti

April 28, 2018 by hgpu

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

Adam G.M. Lewis, Harald P. Pfeiffer

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Tags: Benchmarking, Code generation, Computer science, CUDA, General Relativity and Quantum Cosmology, nVidia, Tesla K80, Tesla M2090, Tesla P100

April 28, 2018 by hgpu

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

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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high performance computing on graphics processing units: hgpu.org

Fast Locality Sensitive Hashing for Beam Search on GPU

Marian: Cost-effective High-Quality Neural Machine Translation in C++

Learning to Optimize Tensor Programs

Glow: Graph Lowering Compiler Techniques for Neural Networks

Neural Multi-scale Image Compression

Deep Neural Machine Translation with Weakly-Recurrent Units

Modeling and Evaluation of Synchronous Stochastic Gradient Descent in Distributed Deep Learning on Multiple GPUs

Tiramisu: A Code Optimization Framework for High Performance Systems

A Comparative Study on Exact Triangle Counting Algorithms on the GPU

Accelerating Blockchain Search of Full Nodes Using GPUs

Automatic generation of CUDA code performing tensor manipulations using C++ expression templates

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

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

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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