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Compoundly weighted Voronoi: a sequential and parallel implementation

Vincent Boerjan

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Tags: Algorithms, Computer science, nVidia, nVidia Quadro NVS 5200 M, OpenCL, OpenGL, Tessellation, Thesis, Voronoi diagram

October 31, 2014 by hgpu

Hierarchical Mapping Techniques for Signal Processing Systems on Parallel Platforms

Lai-Huei Wang

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Tags: Computer vision, CUDA, Design space exploration, DSP, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 680, Signal processing, Thesis

October 31, 2014 by hgpu

Finite Element Numerical Integration on Xeon Phi coprocessor

Filip Kruzel, Krzysztof Banas

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Tags: Algorithms, Computer science, Intel Xeon Phi, nVidia, OpenCL, Tesla K20

October 31, 2014 by hgpu

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

Kazuya Matsumoto, Naohito Nakasato, Stanislav Sedukhin

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Tags: ATI, ATI Radeon HD 7970, BLAS, Computer science, Intel Xeon Phi, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX Titan, OpenCL

October 29, 2014 by hgpu

Sparse Recovery on GPUs: Accelerating the Iterative Soft-Thresholding Algorithm

Achal Shah, Angshul Majumdar

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Tags: Algorithms, CUDA, Machine learning, nVidia, nVidia GeForce GTX 680, Signal processing

October 29, 2014 by hgpu

Efficient Particle-Mesh Spreading on GPUs

Xiangyu Guo, Xing Liu, Peng Xu, Zhihui Du, Edmond Chow

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla K40

October 29, 2014 by hgpu

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Lokendra Singh Panwar

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computational Complexity, Computer science, CUDA, Finite difference, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Seismology, Tesla C1060, Tesla C2050, Thesis

October 29, 2014 by hgpu

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K10, Tesla K20

October 29, 2014 by hgpu

Testing and Exposing Weak Graphics Processing Unit Memory Models

Tyler Rey Sorensen

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, PTX, Tesla C2075, Thesis

October 27, 2014 by hgpu

Parallel Finite Volume Algorithm on Graphic Processing Units (GPU)

Amirsaman Farrokhpanah, Hanif Montazeri, Javad Mostaghimi

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Tesla K20

October 27, 2014 by hgpu

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

Michelle Perry

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Tags: Bayesian, CUDA, High Energy Physics - Phenomenology, Neural networks, nVidia, nVidia GeForce GT 320 M, Physics, Tesla M2050

October 27, 2014 by hgpu

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

David Markvica

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Tags: Algorithms, Biology, Computational biology, Computer science, Heterogeneous systems, Metaheuristics, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Optimization, Pattern recognition, Thesis

October 27, 2014 by hgpu

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

ThunderKittens: Tile primitives for speedy kernels

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

NVIDIA Nemotron Parse 1.1

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

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

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high performance computing on graphics processing units: hgpu.org

Compoundly weighted Voronoi: a sequential and parallel implementation

Hierarchical Mapping Techniques for Signal Processing Systems on Parallel Platforms

Finite Element Numerical Integration on Xeon Phi coprocessor

Implementing Level-3 BLAS Routines in OpenCL on Different Processing Units

Sparse Recovery on GPUs: Accelerating the Iterative Soft-Thresholding Algorithm

Efficient Particle-Mesh Spreading on GPUs

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Testing and Exposing Weak Graphics Processing Unit Memory Models

Parallel Finite Volume Algorithm on Graphic Processing Units (GPU)

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

Recent source codes

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

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

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

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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