The Power of GPUs in Parallel Computing
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Imagine if the same graphics card you use to play games was secretly one of the most powerful
scientific tools on the planet. You click “run,” and a task that used to take all
night finishes before your coffee even cools down. Weather simulations, medical scans,
financial models, AI training—things that once needed huge, expensive supercomputers—suddenly
become possible on a single machine under someone’s desk. That shift didn’t
happen by accident. It happened because people figured out how to turn a chip designed for drawing
pictures into a general-purpose engine for doing lots of things in parallel.
That’s what GPU parallel computing and the CUDA programming model are all about, and today we’re
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