high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

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Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

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Tags: Caffe, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

E. Phipps, M. D'Elia, H. C. Edwards, M. Hoemmen, J. Hu, S. Rajamanickam

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Tags: Computer science, CUDA, Differential equations, nVidia, OpenMP, Partial differential equations, PDEs, Tesla K20

November 24, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 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

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Koki Nagano, Thomas Collins, Chi-An Chen, Aiichiro Nakano

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Tags: Algorithms, Computer science, GLSL, Particle swarm optimization, Rendering, Visualization

November 20, 2015 by hgpu

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Anton Lokhmotov

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Tags: ARM, Benchmarking, Computer science, Linear Algebra, Mathematical Software, Matrix multiplication, OpenCL, Package, Performance

November 13, 2015 by hgpu

Accelerating Recommender Systems using GPUs

Andre Valente Rodrigues, Alipio Jorge, Ines Dutra

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 580

November 13, 2015 by hgpu

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

Gang Mei, Liangliang Xu, Nengxiong Xu

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Tags: Algorithms, Computer science, CUDA, Geoscience, nVidia, nVidia GeForce GT 730 M

November 13, 2015 by hgpu

FIESTA 4: optimized Feynman integral calculations with GPU support

Alexander V. Smirnov

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Tags: CUDA, High Energy Physics - Phenomenology, Mathematical Software, nVidia, Package, Physics, Tesla X2070

November 12, 2015 by hgpu

Microlensing Observations Rapid Search for Exoplanets: MORSE code for GPUs

Alistair McDougall, Michael D. Albrow

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Tesla C2075

November 12, 2015 by hgpu

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

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high performance computing on graphics processing units: hgpu.org

Programming

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning

Embedded Ensemble Propagation for Improving Performance, Portability and Scalability of Uncertainty Quantification on Emerging Computational Architectures

Supervised Hashing with Deep Neural Networks

Large Scale Artificial Neural Network Training Using Multi-GPUs

GPU-accelerated adjoint algorithmic differentiation

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Accelerating Recommender Systems using GPUs

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

FIESTA 4: optimized Feynman integral calculations with GPU support

Microlensing Observations Rapid Search for Exoplanets: MORSE code for GPUs

Recent source codes

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

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