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A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

Peng Chen, Mohamed Wahib, Shinichiro Takizawa, Ryousei Takano, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla P100, Tesla V100

July 21, 2019 by hgpu

A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition

Wei Zhang, Xiaodong Cui, Ulrich Finkler, George Saon, Abdullah Kayi, Alper Buyuktosunoglu, Brian Kingsbury, David Kung, Michael Picheny

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Tags: Algorithms, Computer science, CUDA, Deep learning, Distributed computing, GPU cluster, nVidia, OpenMPI, Speech recognition, Tesla V100

July 21, 2019 by hgpu

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan

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Tags: AI, Algorithms, Computer science, CUDA, Factorization, Machine learning, nVidia, Package, Tesla M40

July 21, 2019 by hgpu

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

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Tags: AMD FirePro S9150, ATI, Compilers, Computer science, CUDA, FPGA, nVidia, OpenCL, Package, performance portability, Tesla K80

July 14, 2019 by hgpu

HashGraph – Scalable Hash Tables Using A Sparse Graph Data Structure

Oded Green

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Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, nVidia Quadro GV100

July 14, 2019 by hgpu

Implementation of high speed hash function Keccak on GPU

Thuong Nguyen Dat, Keisuke Iwai, Takashi Matsubara, Takakazu Kurokawa

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 1080, Security

July 14, 2019 by hgpu

Profiling based Out-of-core Hybrid Method for Large Neural Networks

Yuki Ito, Haruki Imai, Tung Le Duc, Yasushi Negishi, Kiyokuni Kawachiya, Ryo Matsumiya, Toshio Endo

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Performance, Tesla V100

July 14, 2019 by hgpu

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

Roberto Cavicchioli, Nicola Capodieci, Marco Solieri, Marko Bertogna

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Vulkan

July 7, 2019 by hgpu

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Axel Hübl

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Tags: CUDA, HPC, nVidia, Package, Particle-in-cell methods, Physics, Tesla P100, Thesis

July 4, 2019 by hgpu

Automated Generation of OpenCL Programs Based on Algebra-Algorithmic Approach

Anatoliy Doroshenko, Oleksii Beketov, Mykola Bondarenko, Olena Yatsenko

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 840 M, OpenCL

June 30, 2019 by hgpu

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Philippe Tillet, H. T. Kung, David Cox

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Tags: Compilers, Computer science, CUDA, Deep learning, High-level Languages, LLVM, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1070, Package

June 30, 2019 by hgpu

ReSYCLator: Transforming CUDA C++ source code into SYCL

Tobias Stauber, Peter Sommerlad

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, SYCL

June 27, 2019 by hgpu

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

blockgmf: Block based approaches to Matrix Factorization

Block based Singular Value Decomposition approach to matrix factorization for recommender systems

CU2CL: A prototype CUDA-to-OpenCL source-to-source translator

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

GPU-based Parallel Computation Support for Stan

GPU-based Parallel Computation Support for Stan

PANNA: Properties from Artificial Neural Network Architectures

PANNA: Properties from Artificial Neural Network Architectures

Artifact Evaluation for Novel methodologies for predictable CPU-to-GPU command offloading

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

tvm: Open deep learning compiler stack for cpu, gpu and specialized accelerators

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

picongpu: Particle-in-Cell Simulations for the Exascale Era

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

WCCV: Warp-coherent Condition Vectorization(on top of RV)

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

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2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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