high performance computing on graphics processing units: hgpu.org

hgpu.org » Data Structures and Algorithms

Deterministic Sample Sort For GPUs

Frank Dehne, Hamidreza Zaboli

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Tags: Algorithms, Computational Complexity, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 285, Sorting

November 12, 2010 by hgpu

Faster Radix Sort via Virtual Memory and Write-Combining

Jan Wassenberg, Peter Sanders

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Tags: Algorithms, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, Sorting

November 10, 2010 by hgpu

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

Kimikazu Kato, Tikara Hosino

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Tags: Computer science, CUDA, Data Structures and Algorithms, Information Retrieval, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

GPU-Quicksort: A practical Quicksort algorithm for graphics processors

Daniel Cederman, Philippas Tsigas

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Package, Sorting

October 27, 2010 by hgpu

Fast parallel GPU-sorting using a hybrid algorithm

E. Sintorn, U. Assarsson

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Tags: Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce 8800 GTX, Sorting

October 27, 2010 by hgpu

GPU sample sort

Nikolaj Leischner, Vitaly Osipov, Peter Sanders

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, Sorting, Tesla C1060

October 27, 2010 by hgpu

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

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high performance computing on graphics processing units: hgpu.org

Deterministic Sample Sort For GPUs

Faster Radix Sort via Virtual Memory and Write-Combining

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

GPU-Quicksort: A practical Quicksort algorithm for graphics processors

Fast parallel GPU-sorting using a hybrid algorithm

GPU sample sort

Recent source codes

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

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

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