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Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Qualcomm Technologies, Inc

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Tags: Computer science, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

2D Image Convolution using Three Parallel Programming Models on the Xeon Phi

Ashkan Tousimojarad, Wim Vanderbauwhede, W Paul Cockshott

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenCL, OpenMP, Programming Languages

November 30, 2017 by hgpu

Intel FPGA SDK for OpenCL

Intel Corporation

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Tags: Computer science, FPGA, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Shaohuai Shi, Xiaowen Chu

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Tags: Algorithms, Benchmarking, Caffe, Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Package, Performance, TensorFlow, Tesla P40, Torch

November 26, 2017 by hgpu

High Performance Streaming Smith-Waterman Implementation with Implicit Synchronization on Intel FPGA using OpenCL

Ernst Joachim Houtgast, Vlad-Mihai Sima, Zaid Al-Ars

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Tags: Algorithms, Bioinformatics, Biology, FPGA, OpenCL, Smith-Waterman algorithm

November 26, 2017 by hgpu

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Ricardo Jorge Ferreira Nobre

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Tags: Code generation, Compilers, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 480, OpenCL, PTX, Thesis

November 26, 2017 by hgpu

GPU Pro 7: Advanced Rendering

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, nVidia, OpenGL, Package, Rendering, Visualization

November 26, 2017 by hgpu

A survey on graphic processing unit computing for large-scale data mining

Alberto Cano

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Tags: Computer science, CUDA, Data mining, Distributed computing, Machine learning, nVidia

November 21, 2017 by hgpu

Compiling and Optimizing OpenMP 4.X Programs to OpenCL and SPIR

Marcio M. Pereira, Rafael C. F. Sousa, Guido Araujo

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Tags: ARM, Code generation, Compilers, Computer science, FPGA, Heterogeneous systems, LLVM, nVidia, OpenCL, OpenMP, Package, Tesla K40

November 21, 2017 by hgpu

Bitmap Filter: Speeding up Exact Set Similarity Joins with Bitwise Operations

Edans F. O. Sandes, George Teodoro, Alba C. M. A. Melo

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Tags: Algorithms, Computer science, CUDA, Databases, Filtering, nVidia, nVidia GeForce GTX 980 Ti

November 21, 2017 by hgpu

GPU Parallelization for Unstructured Sparse Matrix Problems with OpenMP 4.5 and OpenACC

Stefan Rosenberger, Gundolf Haase

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 1060, OpenACC, OpenMP, Sparse matrix

November 21, 2017 by hgpu

Unified Deep Learning with CPU, GPU, and FPGA Technologies

Allen Rush, Ashish Sirasao, Mike Ignatowski

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Machine learning, OpenCL

November 21, 2017 by hgpu

Neural Query Language: A Knowledge Base Query Language for Tensorflow

Neural Query Language: A Knowledge Base Query Language for Tensorflow

NMODL: Code Generation Framework For NEURON MODeling Language

An optimizing multi-platform source-to-source compiler framework for the NEURON MODeling Language

TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolbox

cuda-benches: collection of small CUDA benchmarking programs

Performance Engineering for a Tall & Skinny Matrix Multiplication Kernel on GPUs

Simulee: Charactering and Detecting CUDA Program Bugs

Charactering and Detecting CUDA Program Bugs

TensorNetwork: A TensorFlow library for easy and efficient manipulation of tensor networks

TensorNetwork: A Library for Physics and Machine Learning

jive

Principles, Techniques, and Tools for Explicit and Automatic Parallelization

caffe-mc-opencl: Caffe Deep Learning Software with Model Compression by Sparse Coding (Backend: OpenCL)

Compressed Learning of Deep Neural Networks for OpenCL-Capable Embedded Systems

Full-stack Optimization for Accelerating CNNs with FPGA Validation

Full-stack Optimization for Accelerating CNNs with FPGA Validation

AdaNet: Fast and flexible AutoML with learning guarantees

AdaNet: A Scalable and Flexible Framework for Automatically Learning Ensembles

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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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