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DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng

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Tags: Computer science, Computer vision, CUDA, Deep learning, Image recognition, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X

June 30, 2016 by hgpu

A GPU Accelerated Continuous and Discontinuous Galerkin Non-hydrostatic Atmospheric Model

Daniel S. Abdi, Lucas C. Wilcox, Timothy Warburton, Francis X. Giraldo

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Tags: Algorithms, CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan Black, OCCA, OpenCL, Tesla K20

May 30, 2016 by hgpu

Polly-ACC: Transparent compilation to heterogeneous hardware

Tobias Grosser, Torsten Hoefler

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, LLVM, nVidia, nVidia GeForce GT 730 M, nVidia GeForce GTX Titan Black

May 3, 2016 by hgpu

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

Pascal Vincent, Alexandre de Brebisson, Xavier Bouthillier

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Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black, Package

March 25, 2016 by hgpu

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

Benjamin Chretien, Adrien Escande, Abderrahmane Kheddar

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Tags: Computer science, CUDA, Nonlinear optimization, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan Black, Robotics, Tesla C2070

February 25, 2016 by hgpu

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Weifeng Liu

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Tags: Algorithms, AMD Radeon R9 290X, ATI, Benchmarking, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan Black, OpenCL, Sparse matrix, Thesis

February 16, 2016 by hgpu

Performance Portable GPU Code Generation for Matrix Multiplication

Toomas Remmelg, Thibaut Lutz, Michel Steuwer, Christophe Dubach

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan Black, OpenCL

February 10, 2016 by hgpu

FPGA Based Implementation of Deep Neural Networks Using On-chip Memory Only

Jinhwan Park, Wonyong Sung

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Tags: Computer science, Deep learning, FPGA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black

February 6, 2016 by hgpu

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

Philipp Kainz, Michael Pfeiffer, Martin Urschler

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Tags: Algorithms, CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black

November 29, 2015 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

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Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 2015 by hgpu

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Andrea Miele

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan Black, Security

July 1, 2015 by hgpu

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

* * *

high performance computing on graphics processing units: hgpu.org

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

A GPU Accelerated Continuous and Discontinuous Galerkin Non-hydrostatic Atmospheric Model

Polly-ACC: Transparent compilation to heterogeneous hardware

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Performance Portable GPU Code Generation for Matrix Multiplication

FPGA Based Implementation of Deep Neural Networks Using On-chip Memory Only

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

GPU-accelerated adjoint algorithmic differentiation

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Recent source codes

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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