This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
All of the below properties or methods, when requested/called in JavaScript, will trigger the browser to synchronously calculate the style and layout*. This is also called reflow or layout thrashing, and is common performance bottleneck.
elem.offsetLeft, elem.offsetTop, elem.offsetWidth, elem.offsetHeight, elem.offsetParentelem.clientLeft, elem.clientTop, elem.clientWidth, elem.clientHeightelem.getClientRects(), elem.getBoundingClientRect()
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“I perfectly understand our CSS. I never have any issues with cascading rules. I never have to use !important or inline styles. Even though somebody else wrote this bit of CSS, I know exactly how it works and how to extend it. Fixes are easy! I have a hard time breaking our CSS. I know exactly where to put new CSS. We use all of our CSS and it’s pretty small overall. When I delete a template, I know the exact corresponding CSS file and I can delete it all at once. Nothing gets left behind.”
You often hear updog saying stuff like this. Who’s updog? Not much, who is up with you?
| from mincepie import mapreducer, launcher | |
| import gflags | |
| import glob | |
| import leargist | |
| import numpy as np | |
| import os | |
| from PIL import Image | |
| import uuid | |
| # constant value |