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Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Azzam Haidar, Panruo Wu, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Artificial intelligence, BLAS, Computer science, Linar Algebra, Mixed precision, Neural networks, nVidia, Tesla P100

December 10, 2017 by hgpu

STAR-RT: Visual attention for real-time video game playing

Iuliia Kotseruba, John K. Tsotsos

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Tags: AMD FirePro W7000, Artificial intelligence, ATI, Computer science, Games, GLSL, OpenCL, OpenGL

December 3, 2017 by hgpu

fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs

Stylianos I. Venieris, Christos-Savvas Bouganis

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Neural networks

November 30, 2017 by hgpu

Device Placement Optimization with Reinforcement Learning

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, Neural networks, nVidia, TensorFlow, Tesla K80

June 17, 2017 by hgpu

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Mark W. Lewis

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Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTS 780 Ti

June 5, 2017 by hgpu

Block-Parallel IDA* for GPUs

Satoru Horie, Alex Fukunaga

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GRID K520, Package

May 11, 2017 by hgpu

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data

Lukas Cavigelli, Philippe Degen, Luca Benini

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1

April 17, 2017 by hgpu

Improving the Neural GPU Architecture for Algorithm Learning

Karlis Freivalds, Renars Liepins

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Tags: Algorithms, Artificial intelligence, Computer science, Deep learning, Memory model, nVidia, Package, Python, TensorFlow, Tesla K40

March 5, 2017 by hgpu

DeepBach: a Steerable Model for Bach chorales generation

Gaetan Hadjeres, Francois Pachet

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Keras, nVidia, nVidia GeForce GTX 980 Ti, Package

January 23, 2017 by hgpu

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Daniel George, E. A. Huerta

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Tags: Algorithms, Artificial intelligence, Astrophysics, CUDA, Deep learning, Filtering, Gravitation, Gravitational waves, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Physics, Signal processing, Tesla K40, Tesla P100

January 4, 2017 by hgpu

Neural Network Computing Using On-Chip Accelerators

Schuyler Eldridge

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, Neural networks, Package, Thesis

October 12, 2016 by hgpu

Comprehensive Evaluation of OpenCL-based Convolutional Neural Network Accelerators in Xilinx and Altera FPGAs

R. Tapiador, A. Rios-Navarro, A. Linares-Barranco, Minkyu Kim, Deepak Kadetotad, Jae-sun Seo

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Tags: Artificial intelligence, Caffe, Computer science, Deep learning, FPGA, Neural networks, OpenCL

September 30, 2016 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

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

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

STAR-RT: Visual attention for real-time video game playing

fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs

Device Placement Optimization with Reinforcement Learning

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Block-Parallel IDA* for GPUs

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data

Improving the Neural GPU Architecture for Algorithm Learning

DeepBach: a Steerable Model for Bach chorales generation

Deep Neural Networks to Enable Real-time Multimessenger Astrophysics

Neural Network Computing Using On-Chip Accelerators

Comprehensive Evaluation of OpenCL-based Convolutional Neural Network Accelerators in Xilinx and Altera FPGAs

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

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

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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