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Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

Hon Ming Yip, John C. S. Li, Kai Xie, Xin Cui, Agrim Prasad, Qiannan Gao, Chi Chiu Leung, Raymond H. W. Lam

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 640

July 22, 2014 by hgpu

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

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

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

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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high performance computing on graphics processing units: hgpu.org

Applications

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

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

Recent source codes

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

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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