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Many-threaded Differential Evolution on the GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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

January 30, 2013 by hgpu

Scheduling (ir)regular applications on heterogeneous platforms

Artur Miguel Matos Mariano

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Tags: Computer science, CUDA, FFT, Heterogeneous systems, N-body simulation, nVidia, nVidia GeForce GTX 580, Task scheduling, Thesis

January 30, 2013 by hgpu

GPUDet: A Deterministic GPU Architecture

Hadi Jooybar, Wilson W. L. Fung, Mike O'Connor, Joseph Devietti, Tor M. Aamodt

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Tags: Computer science, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce GTX 480

January 29, 2013 by hgpu

A dataflow-like programming model for future hybrid clusters

Jens Breitbart

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Tags: Cluster computing, Computer science, CUDA, Distributed data structures, Hybrid computing, nVidia, nVidia GeForce GTX 480, Tesla C2050

January 28, 2013 by hgpu

Exploring Different Automata Representations for Efficient Regular Expression Matching on GPUs

Xiaodong Yu, Michela Becchi

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Tags: Cellular automata, Computer science, CUDA, nVidia, Performance, Security

January 28, 2013 by hgpu

Warped Register File: A Power Efficient Register File for GPGPUs

Mohammad Abdel-Majeed, Murali Annavaram

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, Performance

January 28, 2013 by hgpu

GPUfs: Integrating a File System with GPUs

Mark Silberstein, Bryan Ford, Idit Keidar, Emmett Witchel

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Tags: Computer science, CUDA, nVidia, Operating systems, Tesla C2075

January 26, 2013 by hgpu

Advanced Trends of Heterogeneous Computing with CPU-GPU Integration: Comparative Study

Ishan Rajani, G Nanda Gopal

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Tags: AMD FireStream 9270, ATI, Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Warp level parallelism

January 26, 2013 by hgpu

Selection algorithm of graphic accelerators in heterogeneous cluster for optimization computing

A. M. Lavreniuk, M. S. Lavreniuk

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, OpenCL, Tesla M2050

January 26, 2013 by hgpu

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Malik Muhammad Zaki Murtaza Khan

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Tags: Code generation, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2050, Thesis

January 26, 2013 by hgpu

Automatic Parallelization for GPUs

Thomas B. Jablin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming techniques, Thesis

January 26, 2013 by hgpu

Locality-Aware Work Stealing on Multi-CPU and Multi-GPU Architectures

Thierry Gautier, Joao V. F. Lima, Nicolas Maillard, Bruno Raffin

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Package, Tesla C2050

January 25, 2013 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

Many-threaded Differential Evolution on the GPU

Scheduling (ir)regular applications on heterogeneous platforms

GPUDet: A Deterministic GPU Architecture

A dataflow-like programming model for future hybrid clusters

Exploring Different Automata Representations for Efficient Regular Expression Matching on GPUs

Warped Register File: A Power Efficient Register File for GPGPUs

GPUfs: Integrating a File System with GPUs

Advanced Trends of Heterogeneous Computing with CPU-GPU Integration: Comparative Study

Selection algorithm of graphic accelerators in heterogeneous cluster for optimization computing

Autotuning, Code Generation and Optimizing Compiler Technology for GPUs

Automatic Parallelization for GPUs

Locality-Aware Work Stealing on Multi-CPU and Multi-GPU Architectures

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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