high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

M. Bader, A. Bode, H.-J. Bungartz

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Tags: Algorithms, Book, Computer science, CUDA, Heterogeneous systems, nVidia

July 22, 2014 by hgpu

High Performance Low Power Embedded Vision Systems

Antonis S. Nikitakis

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Tags: Algorithms, ARM, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, OpenCV, Thesis

July 22, 2014 by hgpu

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX Titan

July 20, 2014 by hgpu

An execution model for adaptive load-balancing on multicore and multi-GPU systems

Christopher Lauderdale, Robert Springer, Rishi Khan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2070

July 20, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

Algorithms for Large-Scale Power Delivery Network Analysis on Massively Parallel Architectures

Konstantis Daloukas

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Tags: Algorithms, Computer science, CUDA, nVidia, Power Systems Simulation, Tesla K20, Thesis

July 20, 2014 by hgpu

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

Dariusz Cieslakiewicz

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660 M, Thesis

July 18, 2014 by hgpu

GPU acceleration of Runge Kutta-Fehlberg and its comparison with Dormand-Prince method

Wo Mei Seen, R. U. Gobithaasan, Kenjiro T. Miura

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 540 M, ODEs, Ordinary differential equations

July 18, 2014 by hgpu

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Ken Chatfield, Karen Simonyan, Andrew Zisserman

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan, Pattern recognition

July 18, 2014 by hgpu

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Csaba Nemes

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 570, Tesla K20, Thesis

July 17, 2014 by hgpu

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Computer science, CUDA, Distributed computing, Energy-efficient computing, Heterogeneous systems, nVidia, Tesla K20

July 17, 2014 by hgpu

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

Tsutomu Inamoto, Yoshinobu Higami, Shin-ya Kobayashi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance

July 17, 2014 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

High Performance Low Power Embedded Vision Systems

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

An execution model for adaptive load-balancing on multicore and multi-GPU systems

Performance-efficient mechanisms for managing irregularity in throughput processors

Algorithms for Large-Scale Power Delivery Network Analysis on Massively Parallel Architectures

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

GPU acceleration of Runge Kutta-Fehlberg and its comparison with Dormand-Prince method

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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