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This document provides an overview of the gpuCL.js module, part of the InPylex Power Engine developed by Carnation Games. The module leverages the GPU.js library to perform matrix operations on the GPU, offering a powerful tool for game development and other applications requiring high-performance matrix computations.
gpu.js library installed via npm: npm install gpu.js.gpuCL.js file.gpu.js library by running npm install gpu.js in your project directory.To use the gpuCL module in your project, first, import it:
javascript const { GPUCL } = require('./gpuCL');
Then, create an instance of the GPUCL class:
javascript const gpuCL = new GPUCL();
You can now perform matrix operations using the methods provided by the GPUCL class:
javascript // Example: Matrix multiplication const result = gpuCL.multiply(matrixA, matrixB);
// Example: Matrix addition const sum = gpuCL.add(matrixA, matrixB);
// Example: Matrix subtraction const difference = gpuCL.subtract(matrixA, matrixB);
// Example: Matrix division const quotient = gpuCL.divide(matrixA, matrixB);
For more complex operations or optimizations, you can create custom kernels using the createKernel method of the GPU instance:
javascript const customKernel = gpu.createKernel(function(a, b) { // Custom operation logic here }).setOutput([512, 512]);
Contributions to the InPylex Power Engine are welcome. Please follow the standard GitHub workflow: fork, branch, commit, and pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
For any questions or support, please contact Carnation Games at support@carnationgames.com.
FAQs
Libraries for high-speed computation with GPUs
We found that inpylex demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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