high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Parallel Execution of AES-CTR Algorithm Using Extended Block Size

Nhat-Phuong Tran, Myungho Lee, Sigwon Hong

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Security

October 25, 2011 by hgpu

The Model of Computation of CUDA and its Formal Semantics

Axel Habermaier

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 480, PTX, Thesis

October 25, 2011 by hgpu

Distributed GPU Password Cracking Research Project

Aleksandar Kasabov, Jochem van Kerkwijk

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Tags: Computer science, Distributed computing, nVidia, nVidia GeForce GTX 295, OpenCL, Security

October 25, 2011 by hgpu

Extending Scala with General Purpose GPU Programming

Reidar Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, Java, nVidia, OpenCL, Package, Tesla C870

October 25, 2011 by hgpu

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Brijmohan Singh, Nitin Gupta, Rashi Tyagi, Ankush Mitta, Debashish Ghosh

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Pattern recognition

October 24, 2011 by hgpu

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Pablo Lamilla Alvarez

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Tags: Computer science, GPU cluster, nVidia, nVidia GeForce GT 220, OpenCL, Performance, Thesis

October 24, 2011 by hgpu

Breaking DVB-CSA

Erik Tews, Julian Walde, Michael Weiner

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, Security

October 24, 2011 by hgpu

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

Joo Hong Lee, Mark T. Jones, Paul E. Plassmann

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Tags: ATI, ATI Radeon HD 5750, Computer science, Monte Carlo simulation, OpenCL, Pseudo-random number generators

October 24, 2011 by hgpu

APTCC: Auto Parallelizing Translator From C To CUDA

Takehiko Nawataa, Reiji Suda

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, Tesla C2050

October 24, 2011 by hgpu

Using OpenCL for Implementing Simple Parallel Graph Algorithms

Michael J. Dinneen, Masoud Khosravani, Andrew Probert

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, OpenCL, Tesla C2050

October 24, 2011 by hgpu

Democratizing General Purpose GPU Programming through OpenCL and Scala

Raider Beck, Helge Willum Larsen, Tommy Jensen

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Tags: Benchmarking, Code generation, Compilers, Computer science, nVidia, OpenCL, Package, Tesla C870

October 24, 2011 by hgpu

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Tags: APU, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

October 24, 2011 by hgpu

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

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel Execution of AES-CTR Algorithm Using Extended Block Size

The Model of Computation of CUDA and its Formal Semantics

Distributed GPU Password Cracking Research Project

Extending Scala with General Purpose GPU Programming

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Design and implementation of a high-performance stream-based computing platform on multigenerational GPUs

Breaking DVB-CSA

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

APTCC: Auto Parallelizing Translator From C To CUDA

Using OpenCL for Implementing Simple Parallel Graph Algorithms

Democratizing General Purpose GPU Programming through OpenCL and Scala

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Recent source codes

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

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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