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New Ways To Optimize Machine Learning

By nileshthiagarajan

Excerpt from article: “New Ways To Optimize Machine Learning

Some projects are experimenting with larger strides. A stride of 2 means that the window moves to the right by two pixels at a time. After the right edge of the image is reached, the window then moves down by 2 pixels. This skips half the data, reducing the volume by a factor of 4 (2 horizontally, 2 vertically). But, of course, it comes at the expense of the loss of some precision, even though the “skipped” pixels aren’t omitted outright from calculations, since they will appear within the window of the remaining calculations. A designer would need to decide whether or not any loss of precision would be acceptable for their application.

“One of the benefits of using a stride of 2 is that you get an extra cycle to do the computations, since you ignore the intermediate data being fed from memory,” said Michael Fingeroff, high-level synthesis technologist at Siemens EDA. It should be noted that many hardware platforms currently support strides greater than 1, but it would appear that it’s not a common technique at present.

Read the entire article on SemiEngineering originally published on April 2nd, 2020.

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This article first appeared on the Siemens Digital Industries Software blog at https://blogs.sw.siemens.com/hlsdesign-verification/2020/04/02/new-ways-to-optimize-machine-learning/