Yes, TensorFlow.js does support GPU acceleration. TensorFlow.js leverages WebGL, a graphics library that enables GPU-accelerated computations on the web, to run machine learning models in the browser. This allows TensorFlow.js to take advantage of the powerful parallel processing capabilities of GPUs, resulting in faster and more efficient model execution.

  By utilizing WebGL shaders, TensorFlow.js is able to perform matrix and tensor computations on the GPU, which significantly speeds up the execution of deep learning models. The GPU acceleration provided by TensorFlow.js is especially beneficial for models with large input sizes or complex architectures, as it can potentially reduce inference time by orders of magnitude compared to CPU-only execution.

  It's worth mentioning that in order to leverage GPU acceleration with TensorFlow.js, the user's device must have a compatible GPU and browser. Modern desktop and laptop computers, as well as some mobile devices, are typically equipped with GPUs that can be utilized for GPU-accelerated machine learning with TensorFlow.js.

  In summary, TensorFlow.js supports GPU acceleration through WebGL, enabling faster and more efficient execution of machine learning models in the browser.