gpu-kernel-performance

Here are 4 public repositories matching this topic...

eyalroz / gpu-kernel-runner

Runs a single CUDA/OpenCL kernel, taking its source from a file and arguments from the command-line

gpu opencl cuda runner gpgpu multi-language performance-analysis profiling performance-testing debugging-tool gpu-kernels gpu-kernel-performance

Updated Jun 10, 2026
C++

sparcityeu / SparseViz

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Sparse Matrix and Tensor Visualization Tool for Reorderings

performance-engineering sparse-data performance-visualization performance-monitoring matrix-visualizer tensor-visualization gpu-kernel-performance matrix-ordering

Updated Nov 9, 2025
C++

Rheinwalt / gaussian_kde_gpu

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GPU Gaussian kernel density estimation

python gpu cuda numba kernel-density-estimation gpu-kernel-performance

Updated Jul 21, 2023
Jupyter Notebook

Sarthak-Mohapatra / Classification-of-GPU-Run-as-high-or-low-time-consuming-using-various-classification-Algorithms.

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As part of this project, various classification algorithms like SVM, Decision Trees and XGBoost was used to classify a GPU Run as high or low time consuming process. The main purpose of this project is to test and compare the predictive capabilities of different classification algorithms

python numpy svm matrix scikit-learn machine-learning-algorithms cross-validation pandas seaborn matrix-multiplication matplotlib performance-analysis decision-trees svm-kernel classification-algorithms k-fold-cross-validation gpu-kernel-performance xgboost-algorithms

Updated May 13, 2020
Jupyter Notebook

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