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Implementing density functional theory (DFT) methods on many-core GPGPU accelerators

Bishwajit Mohan Gosswami

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Tags: Chemistry, CUDA, Density-functional theory, nVidia, Tesla C2070, Thesis

June 19, 2012 by hgpu

Gdev: First-Class GPU Resource Management in the Operating System

Shinpei Kato, Michael McThrow, Carlos Maltzahn, Scott Brandt

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package

June 18, 2012 by hgpu

An Improved CUDA-Based Implementation of Differential Evolution on GPU

A. K. Qin, Federico Raimondo, Florence Forbes, Yew Soon Ong

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Tags: Computer science, CUDA, Differential evolution, nVidia, nVidia GeForce GTX 560

June 18, 2012 by hgpu

Solving the Vlasov equation for one-dimensional models with long range interactions on a GPU

Tarcisio M. Rocha Filho

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Tags: Computational Physics, CUDA, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 590, Physics, Statistical Mechanics

June 18, 2012 by hgpu

GPUmotif: An Ultra-Fast and Energy-Efficient Motif Analysis Program Using Graphics Processing Units

Pooya Zandevakili, Ming Hu, Zhaohui Qin

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Tags: Algorithms, Biochemistry, Biology, Chemistry, Computational biology, Computer science, CUDA, Genetics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

June 17, 2012 by hgpu

Branch and Data Herding: Reducing Control and Memory Divergence for Error-tolerant GPU Applications

John Sartori, Rakesh Kumar

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480

June 17, 2012 by hgpu

ScatterAlloc: Massively Parallel Dynamic Memory Allocation for the GPU

Steinberger Markus, Kenzel Michael, Kainz Bernhard, Schmalstieg Dieter

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Tags: Computer science, CUDA, Hashing, Memory, nVidia, nVidia Quadro FX 6000, Package

June 16, 2012 by hgpu

E-MOGA: A General Purpose Platform for Multi Objective Genetic Algorithm running on CUDA

Sami M. Salamin, Mohammed Aldasht, Hashem Tamimi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9500 GTX, Optimization

June 16, 2012 by hgpu

Accelerating Lambert’s Problem on the GPU in MATLAB

Nathan L. Parrish

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Tags: Algorithms, Computer science, CUDA, Fortran, nVidia, nVidia GeForce GT 430, nVidia GeForce GT 540 M, nVidia GeForce GTX 560 Ti, Package

June 16, 2012 by hgpu

Parallel Primitives based Spatial Join of Geospatial Data on GPGPUs

Jianting Zhang

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia Quadro FX 6000, Package

June 16, 2012 by hgpu

GiST Scan Acceleration using Coprocessors

Felix Beier, Torsten Kilias, Kai-Uwe Sattler

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Tags: Collision detection, Computer science, CUDA, nVidia, Raytracing, Tesla C2050

June 16, 2012 by hgpu

Energy Efficiency Analysis of GPUs

Juan M. Cebrian, Gines D. Guerrero, Jose M. Garcia

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 465, nVidia GeForce GTX 480

June 15, 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

Implementing density functional theory (DFT) methods on many-core GPGPU accelerators

Gdev: First-Class GPU Resource Management in the Operating System

An Improved CUDA-Based Implementation of Differential Evolution on GPU

Solving the Vlasov equation for one-dimensional models with long range interactions on a GPU

GPUmotif: An Ultra-Fast and Energy-Efficient Motif Analysis Program Using Graphics Processing Units

Branch and Data Herding: Reducing Control and Memory Divergence for Error-tolerant GPU Applications

ScatterAlloc: Massively Parallel Dynamic Memory Allocation for the GPU

E-MOGA: A General Purpose Platform for Multi Objective Genetic Algorithm running on CUDA

Accelerating Lambert’s Problem on the GPU in MATLAB

Parallel Primitives based Spatial Join of Geospatial Data on GPGPUs

GiST Scan Acceleration using Coprocessors

Energy Efficiency Analysis of GPUs

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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