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A Parallel GPU Version of the Traveling Salesman Problem

Molly A. O'Neil, Dan Tamir, Martin Burtscher

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Package, Tesla C2050

December 16, 2011 by hgpu

Reducing Thread Divergence in GPU-based B and B Applied to the Flow-shop problem

Imen Chakroun, Ahcene Bendjoudi, Nouredine Melab

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050

December 16, 2011 by hgpu

Algorithms acceleration of pattern-matching in multi-core architectures

David Rodenas Pico

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GT 430, nVidia GeForce GTX 320 M, Thesis

December 16, 2011 by hgpu

Reducing Thread Divergence in GPU-based B&B Applied to the Flow-shop problem

Imen Chakroun, Ahcene Bendjoudi, Nouredine Melab

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050

December 16, 2011 by hgpu

Efficient XML Path Filtering Using GPUs

Roger Moussalli, Robert Halstead, Mariam Salloum, Walid Najjar, Vassilis J. Tsotras

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Tags: Computer science, CUDA, Data Structures and Algorithms, FPGA, nVidia, Optimization, Tesla C1060

December 16, 2011 by hgpu

A Predictive Model for Solving Small Linear Algebra Problems in GPU Registers

Michael J. Anderson, David Sheffield, Kurt Keutzer

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Tags: Benchmarking, Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia Quadro FX 6000, Package, Signal processing

December 16, 2011 by hgpu

Improving GPU Robustness by Making Use of Faulty Parts

Artem Durytskyy, Mohamed Zahran, Ramesh Karri

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Tags: Computer science, Fault simulation, Hardware Architecture, nVidia, Performance

December 16, 2011 by hgpu

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

Uzi Vishkin, Rajeev Barua

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Tags: Algorithms, Benchmarking, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Prefetch, Rendering, Thesis

December 16, 2011 by hgpu

Affine Vector Cache for memory bandwidth savings

Sylvain Collange, Alexandre Kouyoumdjian

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Tags: Benchmarking, Computer science, CUDA, Memory model, nVidia, Tesla

December 16, 2011 by hgpu

Simultaneous Branch and Warp Interweaving for Sustained GPU Performance

Nicolas Brunie, Sylvain Collange, Gregory Diamos

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Tags: Computer science, CUDA, nVidia, Performance

December 15, 2011 by hgpu

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory level parallelism, nVidia, nVidia Quadro FX 5600, Warp level parallelism

December 15, 2011 by hgpu

A GPU-based Approximate SVD Algorithm

Blake Foster, Sridhar Mahadevan, Rui Wang

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Tags: Algorithms, Computer science, CUDA, Matrix decomposition, nVidia, nVidia GeForce GTX 480, Package

December 15, 2011 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

A Parallel GPU Version of the Traveling Salesman Problem

Reducing Thread Divergence in GPU-based B and B Applied to the Flow-shop problem

Algorithms acceleration of pattern-matching in multi-core architectures

Reducing Thread Divergence in GPU-based B&B Applied to the Flow-shop problem

Efficient XML Path Filtering Using GPUs

A Predictive Model for Solving Small Linear Algebra Problems in GPU Registers

Improving GPU Robustness by Making Use of Faulty Parts

Optimizing for a Many-Core Architecture without Compromising Ease-of-Programming

Affine Vector Cache for memory bandwidth savings

Simultaneous Branch and Warp Interweaving for Sustained GPU Performance

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

A GPU-based Approximate SVD Algorithm

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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