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Watch out multicore: GPUs are right behind


By Alexandra Weber Morales


 Alexandra Weber Morales
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November 1, 2010 —  (Page 1 of 6)
“A manycore processor is a device for turning a compute-bound problem into a memory-bound problem,” said Mark Murphy, a Ph.D. candidate in electrical engineering and computer science at the University of California, Berkeley, working and lecturing in the Intel-financed Parallel Computing Lab (Par Lab).

“This is a quote that I use in almost every talk I give. Kathy Yelick [director of the National Energy Research Scientific Computing Center at Lawrence Berkeley Laboratory] was the first to say it...Essentially, the amount of on-chip computation is growing much faster than the amount of memory bandwidth that you have, so we are at the point where you need at least 10 times as many floating point operations as you have memory loads," he continued.

"If you load a single cache line, you want to be sure to use all of it, and you want to be sure, if you can, to load single cache lines at a time. This is the same problem as we have with CPUs, but it’s exacerbated in GPUs because of the large amount of on-chip parallelism.”

Just a few years ago, Intel’s multicore CPU efforts were stealing headlines. C++ guru Herb Sutter first sounded the alarm to developers that Moore’s Law could no longer be counted on with a Slashdot article entitled “The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software.” (Disclosure: I was on retainer as a contract editor to help Intel evangelize concurrent programming to software developers from 2007 to 2009.)

A funny thing happened on the way to the multicore future, however: While CPU makers and developers alike were slamming into Amdahl’s “Wall,” struggling to realize performance increases for eight or 16 cores thanks to the sequential overhead of their legacy code, GPU makers were quietly cooking up a revolution.

It’s been a few decades in the making, granted. The concept of general-purpose graphics processing units (GPGPUs) dates to the late 1970s. But a number of factors have coalesced recently:



Related Search Term(s): parallel processing

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