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Simpleperf case study: Fast initialization of TFLite’s Memory Arena
The TensorFlow Blog blog.tensorflow.org
One of our previous articles, Optimizing TensorFlow Lite Runtime Memory, discusses how TFLite’s memory arena minimizes memory usage by sharing buffers between tensors. This means we can run models on even smaller edge devices. In today’s article, I will describe the performance optimization of the memory arena initialization so that our users get the benefit of low memory usage with little additional overhead.
ML is normally deployed on-device as part of a …
article articles case case study devices edge edge devices engineer memory optimization performance reduce software software engineer study tensorflow tensorflow-lite tflite usage