high performance computing on graphics processing units: hgpu.org

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Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations

Da Li, Hancheng Wu, Michela Becchi

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Tags: Computer science, nVidia, OpenCL, Tesla K20

December 4, 2015 by hgpu

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Min-Young Son, Young-Hak Kim, Byoung-Woo Oh

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 670

December 4, 2015 by hgpu

Programming in CUDA for Kepler and Maxwell Architecture

Esteban G. W. Clua, Marcelo Zamith

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Tags: Computer science, CUDA, nVidia, Performance

December 1, 2015 by hgpu

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

Samaneh Azadi, Jiashi Feng, Stefanie Jegelka, Trevor Darrell

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia

December 1, 2015 by hgpu

A General Framework for Constrained Bayesian Optimization using Information-based Search

Jose Miguel Hernandez-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani

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Source codes

Tags: Bayesian, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Package, Python

December 1, 2015 by hgpu

Efficient Static and Dynamic Memory Management Techniques for Multi-GPU Systems

Max Grossman, Mauricio Araya-Polo

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K10

December 1, 2015 by hgpu

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Junghyun Kim, Thanh Tuan Dao, Jaehoon Jung, Jinyoung Joo, Jaejin Lee

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL

December 1, 2015 by hgpu

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

December 1, 2015 by hgpu

Orchestrating Multiple Data-Parallel Kernels on Multiple Devices

Janghaeng Lee, Mehrzad Samadi, Scott Mahlke

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX 760, OpenCL

November 29, 2015 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

Reordering GPU Kernel Launches to Enable Efficient Concurrent Execution

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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

November 29, 2015 by hgpu

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

Emanuele De Falco

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GT 540 M

November 29, 2015 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Nested Parallelism on GPU: Exploring Parallelization Templates for Irregular Loops and Recursive Computations

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Programming in CUDA for Kepler and Maxwell Architecture

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

A General Framework for Constrained Bayesian Optimization using Information-based Search

Efficient Static and Dynamic Memory Management Techniques for Multi-GPU Systems

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Neural GPUs Learn Algorithms

Orchestrating Multiple Data-Parallel Kernels on Multiple Devices

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

Reordering GPU Kernel Launches to Enable Efficient Concurrent Execution

Design, Implementation and Performance Evaluation of a Stochastic Gradient Descent Algorithm on CUDA

Recent source codes

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

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

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