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Implementation and Evaluation of Recurrence Equation Solvers on GPGPU systems using Rearrangement of Array Configurations

Akiyoshi Wakatani

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Tags: Algorithms, Computer science, CUDA, nVidia, PC cluster, Tesla C1060

July 29, 2012 by hgpu

Distributed-Shared CUDA: Virtualization of Large-Scale GPU Systems for Programmability and Reliability

Atsushi Kawai, Kenji Yasuoka, Kazuyuki Yoshikawa, Tetsu Narumi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Tesla M2050, Virtualization

July 29, 2012 by hgpu

Acceleration of Variance of Color Differences-Based Demosaicing Using CUDA

Muhammad Ismail Faruqi, Fumihiko Ino, Kenichi Hagihara

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 480

July 28, 2012 by hgpu

Speeding up LIP-Canny with CUDA programming

Rafael Palomar, Jose M. Palomares, Joaquin Olivares, Jose M. Castillo, Juan Gomez-Luna

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9200 M GS

July 28, 2012 by hgpu

A virtual memory based runtime to support multi-tenancy in clusters with GPUs

Michela Becchi, Kittisak Sajjapongse, Ian Graves, Adam Procter, Vignesh Ravi, Srimat Chakradhar

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Tags: Cloud, Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, PC cluster, Tesla C1060, Tesla C2050, Virtualization

July 27, 2012 by hgpu

Speeding up Large-Scale Point-in-Polygon Test Based Spatial Join on GPUs

Jianting Zhang, Simin You

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Tags: Computer science, CUDA, Databases, Filtering, nVidia, nVidia Quadro FX 6000

July 27, 2012 by hgpu

High-Performance Spatial Join Processing on GPGPUs with Applications to Large-Scale Taxi Trip Data

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Computer science, CUDA, Databases, Filtering, Nearest neighbour, nVidia, nVidia Quadro FX 6000

July 27, 2012 by hgpu

CUDA Kernel Design for GPU-Based Beam Dymanics Simulations

K. Amyx, J. Balasalle, I. Pogorelov, M. Borland, R. Soliday, Y.Wang

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Tags: CUDA, nVidia, Physics, Tesla C2070

July 27, 2012 by hgpu

Efficient Implementation of the CPR Formulation for the Navier-Stokes Equations on GPUs

Malte Hoffmann, Claus-Dieter Munz, Z. J. Wang

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Tags: Algorithms, CUDA, Fluid dynamics, Graph theory, Navier-Stokes equations, NSEs, nVidia, Tesla C2050

July 26, 2012 by hgpu

Bidimensional Median Filter for Parallel Computing Architectures

Ricardo M. Sanchez, Paul A. Rodriguez

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Sorting

July 26, 2012 by hgpu

Parallelization of Data Intensive Code Using Computer Unified Device Architecture (CUDA)

Bhardwaj Aditi, Bhardwaj Rohatash K., Shishir K. Gangwar

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Tags: Algorithms, Biology, CUDA, nVidia, RNA

July 26, 2012 by hgpu

Fast End-to-End Multi-Conjugate AO Simulations Using Graphical Processing Units and the MAOS Simulation Code

Lianqi Wang, Brent Ellerbroek

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Tags: CUDA, nVidia, nVidia GeForce GTX 580, Optics, Package, Physics

July 25, 2012 by hgpu

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

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

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Programming

Implementation and Evaluation of Recurrence Equation Solvers on GPGPU systems using Rearrangement of Array Configurations

Distributed-Shared CUDA: Virtualization of Large-Scale GPU Systems for Programmability and Reliability

Acceleration of Variance of Color Differences-Based Demosaicing Using CUDA

Speeding up LIP-Canny with CUDA programming

Speeding up Large-Scale Point-in-Polygon Test Based Spatial Join on GPUs

High-Performance Spatial Join Processing on GPGPUs with Applications to Large-Scale Taxi Trip Data

CUDA Kernel Design for GPU-Based Beam Dymanics Simulations

Efficient Implementation of the CPR Formulation for the Navier-Stokes Equations on GPUs

Bidimensional Median Filter for Parallel Computing Architectures

Parallelization of Data Intensive Code Using Computer Unified Device Architecture (CUDA)

Fast End-to-End Multi-Conjugate AO Simulations Using Graphical Processing Units and the MAOS Simulation Code

Recent source codes

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

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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