by Jan A. Zverina, San Diego Supercomputer Center
The news late last year that China’s GPU-rich Tianhe-1A supercomputer was ranked the fastest system in the world focused attention – and a lot of discussion – within the HPC community about the advantages of graphics processing units (GPUs) versus central processing units (CPUs) used in many systems.

While GPUs have for several years primarily been used as fast video game engines to process 3D functions, simulate movement and other mathematically intensive operations that might otherwise strain some CPUs, the newest GPUs are capable of more than making whiz-bang images or movies. Peter Varhol, a contributing editor for the online magazine Desktop Engineering (DE), says GPUs are now capable of performing high-end computations such as those used in engineering applications, in some instances as much as 20 times faster.

However, as Varhol wrote in an article for DE late last year, GPUs don’t necessarily trump CPUs every time. In fact, when it comes to engineering-intensive applications, comparing CPUs with GPUs “is like comparing apples with oranges.”

“The GPU remains a specialized processor, and its performance in graphics computation belies a host of difficulties to perform true general-purpose computing,” Varhol wrote. “The processors themselves require rewriting any software; they have rudimentary programming tools, as well as limits in programming languages and features.”

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