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Methods for GPU Acceleration of Big Data Applications

Reza Mokhtari

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Tags: big data, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan Black, Thesis

December 3, 2017 by hgpu

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

Enzo Rucci, Armando De Giusti, Marcelo Naiouf

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Tags: All-Pairs Distance, Computer science, Intel Xeon Phi, OpenMP

December 3, 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

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

Implementing implicit OpenMP data sharing on GPUs

Gheorghe-Teodor Bercea, Carlo Bertolli, Arpith C. Jacob, Alexandre Eichenberger, Alexey Bataev, Georgios Rokos, Hyojin Sung, Tong Chen, Kevin O'Brien

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Tags: Computer science, CUDA, LLVM, Memory model, nVidia, OpenMP, Programming Languages, PTX, Tesla K40, Tesla P100

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

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

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

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

Maxence Reberol, Bruno Levy

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Tags: Computer science, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, Traingular meshes

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

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Methods for GPU Acceleration of Big Data Applications

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

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

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Implementing implicit OpenMP data sharing on GPUs

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

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

Intel FPGA SDK for OpenCL

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

GPU Pro 7: Advanced Rendering

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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