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Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Jan G. Cornelis, Jan Lemeire

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Computer science, nVidia, nVidia GeForce GTX 280, OpenCL

October 10, 2011 by hgpu

Streaming-Oriented Parallelization of Domain-Independent Irregular Kernels

Jacobo Lobeiras, Margarita Amor, Manuel Arenaz, Basilio B. Fraguela

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Tags: Algorithms, ATI, ATI Radeon HD 4850, Brook, Computer science, OpenMP, Performance, Presentation

October 10, 2011 by hgpu

Evaluation of GPU Architectures Using Spiking Neural Networks

Vivek K. Pallipuram, Mohammad A. Bhuiyan, Melissa C. Smith

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Tags: ATI, ATI Radeon HD 5870, Computer science, Neural networks, nVidia, OpenCL, Optimization, Performance, Presentation, Tesla C2050

October 10, 2011 by hgpu

Towards an Effective Unified Programming Model for Many-Cores

Ana Lucia Varbanescu, Pieter Hijma, Rob V. van Nieuwpoort, Henri E. Bal

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Tags: ATI, Cell processor, Computer science, nVidia, OpenCL, Optimization, Programming techniques

October 10, 2011 by hgpu

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Peter Zinterhof

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Tags: Algorithms, Computational Complexity, Computer science, Nearest neighbour, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, OpenCL, OpenMPI, Search, Tesla C2050

October 10, 2011 by hgpu

Computer Vision Models in Surveillance Robotics

A. Moro

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia GeForce 9800 GT, nVidia GeForce GTX 295, Thesis

October 9, 2011 by hgpu

Parallel and efficient Boolean on polygonal solids

H. Zhao, C. C. L. Wang, Y. Chen, X. Jin

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Tags: Computer science, CUDA, Image processing, nVidia GeForce GTX 480

October 9, 2011 by hgpu

Programming framework for clusters with heterogeneous accelerators

Anson H.T. Tse, David B. Thomas, K.H. Tsoi, Wayne Luk

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Tags: Computer science, Finance, FPGA, Heterogeneous systems, Physics, Programming techniques, Tesla

October 8, 2011 by hgpu

Multifrontal computations on GPUs and their multi-core hosts

Robert F. Lucas, Gene Wagenbreth, Dan M. Davis, Roger Grimes

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Tags: Computer science, CUDA, Factorization, nVidia, Performance, Sparse matrix, Tesla C1060

October 7, 2011 by hgpu

Non-recursive beam search on GPU for formal concept analysis

W. B. Langdon, Shin Yoo, Mark Harman

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Tesla C2050

October 7, 2011 by hgpu

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

Ye Tian, Bin Zhou, Yutong Zhang, Ka Wing Chan

Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Sparse matrix

October 7, 2011 by hgpu

Hybrid coherence for scalable multicore architectures

John Henry Kelm

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Tags: Computer science, Memory model, Thesis

October 7, 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

Benchmarks Based on Anti-Parallel Patterns for the Evaluation of GPUs

Streaming-Oriented Parallelization of Domain-Independent Irregular Kernels

Evaluation of GPU Architectures Using Spiking Neural Networks

Towards an Effective Unified Programming Model for Many-Cores

Data-Parallel Construction of delta_N-Nets with Maximum Dispersion

Computer Vision Models in Surveillance Robotics

Parallel and efficient Boolean on polygonal solids

Programming framework for clusters with heterogeneous accelerators

Multifrontal computations on GPUs and their multi-core hosts

Non-recursive beam search on GPU for formal concept analysis

Investigation on the Use of GPGPU for Fast Sparse Matrix Factorization

Hybrid coherence for scalable multicore architectures

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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