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Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Petr Pospichal, Eoin Murphy, Michael O'Neill, Josef Schwarz, Jiri Jaros

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Genetic programming, Java, nVidia, nVidia GeForce GTX 480, Optimization

December 19, 2011 by hgpu

Parallel programming with inductive synthesis

Shaon Barman, Rastislav Bodik, Sagar Jain, Yewen Pu, Saurabh Srivastava, Nicholas Tung

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Programming techniques

December 19, 2011 by hgpu

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Erzhou Zhu, Haibing Guan, Guoxing Dong, Yindong Yang, Hongbo Yang

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Tags: Benchmarking, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, PTX

December 18, 2011 by hgpu

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Tesla C2050

December 18, 2011 by hgpu

Collision for 75-step SHA-1: Intensive Parallelization with GPU

E.A. Grechnikov, A.V. Adinetz

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Tags: Computer science, nVidia, OpenCL, Package, Security, Tesla M2050, Tesla X2070

December 18, 2011 by hgpu

Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie

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Tags: AMD FireStream 9250, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Programming techniques, Tesla C1060

December 18, 2011 by hgpu

Efficient Computational Methods for Uncertainty Quantification of Large Systems

Gaurav Gaurav

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Tags: Computer science, CUDA, Nonlinear analysis, nVidia, Tesla C1060, Thesis

December 18, 2011 by hgpu

The MOSIX Cluster Operating System for High-Performance Computing on Linux Clusters, Multi-Clusters, GPU Clusters and Clouds

A. Barak, A. Shiloh

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Tags: Cloud, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

December 18, 2011 by hgpu

Parallel paradigms in optimal structural design

Van Huyssteen, Salomon Stephanus

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Thesis

December 18, 2011 by hgpu

Massively Parallel Logic Simulation with GPUs

Yuhao Zhu, Bo Wang, Yangdong Deng

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce GTX 280, Optimization, Performance

December 17, 2011 by hgpu

Extendable pattern-oriented optimization directives

Huimin Cui, Jingling Xue, Lei Wang, Yang Yang, Xiaobing Feng, Dongrui Fan

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization

December 17, 2011 by hgpu

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Kyle L. Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Sorting, Tesla M2070

December 17, 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

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Parallel programming with inductive synthesis

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Collision for 75-step SHA-1: Intensive Parallelization with GPU

Leveraging Parallelism with CUDA and OpenCL

Efficient Computational Methods for Uncertainty Quantification of Large Systems

Parallel paradigms in optimal structural design

Massively Parallel Logic Simulation with GPUs

Extendable pattern-oriented optimization directives

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

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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