high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Spatial Data Structures, Sorting and GPU Parallelism for Situated-agent Simulation and Visualisation

A.V. Husselmann, K.A. Hawick

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Tags: Computer science, CUDA, Data parallelism, N-body simulation, nVidia, nVidia GeForce GTX 590, Sorting

May 20, 2012 by hgpu

CUDA Based Enhanced Differential Evolution: a Computational Analysis

Donald Davendra, Jan Gaura, Magdalena Bialic-Davendra, Roman Senkerik

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Tags: Algorithms, Computer science, CUDA, Differential evolution, nVidia, Tesla C2050

May 20, 2012 by hgpu

Combustion Simulations Using Graphic Processing Units

Mingjie Wang

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Tags: Algorithms, CUDA, nVidia, Physics, Tesla S1070

May 19, 2012 by hgpu

A GPU Algorithm for 3D Convex Hull

Mingcen Gao, Thanh-Tung Cao, Ashwin Nanjappa, Tiow-Seng Tan, Zhiyong Huang

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

May 19, 2012 by hgpu

Real-Time Systems with Radiation-Hardened Processors: A GPU-based Framework to Explore Tradeoffs

Mohammad Alhowaidi

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Tags: Computer science, nVidia, OpenCL, Sensing, Tesla M2050, Thesis

May 19, 2012 by hgpu

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

Steve Dower

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Tags: Algorithms, Computer science, Evolutionary Computations, Heterogeneous systems, nVidia, nVidia GeForce GT 540 M

May 19, 2012 by hgpu

SPOC: GPGPU Programming Through Stream Processing With OCaml

Mathias Bourgoin, Emmanuel Chailloux, Jean-Luc Lamotte

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Tags: ATI, ATI Radeon HD 6950, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2070

May 19, 2012 by hgpu

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

VCV.Rao, Nisha Agrawa, Samrit Maity

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Tags: AMD FirePro V5900, AMD FirePro V7900, AMD FireStream 9350, ATI, Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, MPI, nVidia, OpenCL, Partial differential equations, PDEs, Tesla C2060

May 19, 2012 by hgpu

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

He Huang, Liqiang Wang, En-Jui Lee, Po Chen

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Tags: Computer science, CUBLAS, CUDA, Earth and Space Sciences, Geoscience, MPI, nVidia, Optimization, Tesla C2050, Tesla M2070

May 19, 2012 by hgpu

Accelerated GPU Simulation of Compressible Flow by the Discontinuous Evolution Galerkin Method

Block B. J., Lukacova-Medvid'ova M., Virnau P., Yelash L.

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Tags: CUDA, Fluid dynamics, Numerical simulation, nVidia, nVidia GeForce GTX 580

May 19, 2012 by hgpu

High Performance Monte Carlo and Time-Stepping Dynamics for the Classical Spin Heisenberg Model on GPUs

K.A. Hawick, D.P. Playne

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Tags: Algorithms, CUDA, Heisenberg model, Monte Carlo simulation, nVidia, Physics, Rendering, Stochastic simulation

May 19, 2012 by hgpu

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

Tobias Beisel, Tobias Wiersema, Christian Plessl, Andre Brinkmann

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

May 19, 2012 by hgpu

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

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high performance computing on graphics processing units: hgpu.org

Programming

Spatial Data Structures, Sorting and GPU Parallelism for Situated-agent Simulation and Visualisation

CUDA Based Enhanced Differential Evolution: a Computational Analysis

Combustion Simulations Using Graphic Processing Units

A GPU Algorithm for 3D Convex Hull

Real-Time Systems with Radiation-Hardened Processors: A GPU-based Framework to Explore Tradeoffs

Automatic Implementation of Evolutionary Algorithms on GPUs using ESDL

SPOC: GPGPU Programming Through Stream Processing With OCaml

C-DAC’s Efforts – Application Kernels on HPC Cluster with GPU Accelerators

An MPI-CUDA Implementation and Optimization for Parallel Sparse Equations and Least Squares (LSQR)

Accelerated GPU Simulation of Compressible Flow by the Discontinuous Evolution Galerkin Method

High Performance Monte Carlo and Time-Stepping Dynamics for the Classical Spin Heisenberg Model on GPUs

Programming and Scheduling Model for Supporting Heterogeneous Accelerators in Linux

Recent source codes

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

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

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

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