high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Improving GPU Simulations of Spiking Neural P Systems

Francis George C. Cabarle, Henry N. Adorna, Miguel A. Martinez-Del-Amor, Mario J. Perez-Jimenez

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Tags: Computer science, CUDA, Linear Algebra, Membrane computing, Neural networks, nVidia, P systems, Tesla C1060

June 25, 2012 by hgpu

GPU Implementation of the Branch and Bound method for knapsack problems

Mohamed Esseghir Lalami, Didier El-Baz

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Tags: Computer science, CUDA, Hybrid computing, nVidia, Optimization, Tesla C2050

June 25, 2012 by hgpu

Approximate Principal Direction Trees

Mark McCartin-Lim, Andrew McGregor, Rui Wang

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Tags: Computer science, Data Structures and Algorithms, Machine learning, nVidia, nVidia GeForce GTX 470

June 25, 2012 by hgpu

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

Imen Chakroun, Nouredine Melab

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Tags: Computer science, CUDA, GPU cluster, nVidia, Optimization, Tesla S1070

June 25, 2012 by hgpu

Fast motion detection from airborne videos using graphics processing unit

Kui Liu, Ben Ma, Qian Du, Genshe Chen

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, Optical flow

June 23, 2012 by hgpu

Hierarchical overlapped tiling

Xing Zhou, Jean-Pierre Giacalone, Maria Jesus Garzaran, Robert H Kuhn, Yang Ni, David Padua

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Tags: Compilers, Computer science, OpenCL, Performance

June 23, 2012 by hgpu

GPU-accelerated Model Checking of Periodic Self-Suspending Real-Time Tasks

Per-Erik Mahl, Tim Liberg

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 320 M, nVidia GeForce GTX 275, Task scheduling, Thesis

June 23, 2012 by hgpu

Bacon: A GPU Programming System With Just in Time Specialization

Nat Tuck

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Tags: ATI, ATI Radeon HD 5830, Benchmarking, Computer science, Matrix multiplication, OpenCL

June 23, 2012 by hgpu

Parallel Neural Network Training with OpenCL

Nenad Krpan, Domagoj Jakobovic

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Tags: Algorithms, Computer science, Heterogeneous systems, Neural networks, nVidia, nVidia GeForce GTS 250, OpenCL, Optimization

June 23, 2012 by hgpu

High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

Andrei Frunza

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Tags: Computer science, CUDA, Diffusion tensor, nVidia, nVidia GeForce GTX 580, Physics, Thesis

June 21, 2012 by hgpu

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

Marc de la Asuncion, Jose M. Mantas, Manuel J. Castro

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Tags: Computer science, CUDA, Finite volume method, nVidia, nVidia GeForce GTX 580, Performance

June 21, 2012 by hgpu

FMM-based vortex method for simulation of isotropic turbulence on GPUs, compared with a spectral method

Rio Yokota, L. A. Barba

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Tags: Computational Physics, Computer science, CUDA, Fast multipole method, FFT, Fluid dynamics, N-body simulation, Numerical Analysis, Numerical simulation, nVidia, Package, Spectral methods, Tesla C2070, Tesla M2050

June 21, 2012 by hgpu

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

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Improving GPU Simulations of Spiking Neural P Systems

GPU Implementation of the Branch and Bound method for knapsack problems

Approximate Principal Direction Trees

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

Fast motion detection from airborne videos using graphics processing unit

Hierarchical overlapped tiling

GPU-accelerated Model Checking of Periodic Self-Suspending Real-Time Tasks

Bacon: A GPU Programming System With Just in Time Specialization

Parallel Neural Network Training with OpenCL

High performance implementation of hydrodynamic interactions and applications with the sub-cellular element method

Evaluating the impact of reordering unstructured meshes on the performance of finite volume GPU solvers

FMM-based vortex method for simulation of isotropic turbulence on GPUs, compared with a spectral method

Recent source codes

True 4-Bit Quantized CNN Training on CPU

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

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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