Faster Chips Are Leaving Programmers in Their Dust

mlimber writes "The New York Times is running a story about multicore computing and the efforts of Microsoft et al. to try to switch to the new paradigm: "The challenges [of parallel programming] have not dented the enthusiasm for the potential of the new parallel chips at Microsoft, where executives are betting that the arrival of manycore chips — processors with more than eight cores, possible as soon as 2010 — will transform the world of personal computing.... Engineers and computer scientists acknowledge that despite advances in recent decades, the computer industry is still lagging in its ability to write parallel programs." It mirrors what C++ guru and now Microsoft architect Herb Sutter has been saying in articles such as his "The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software." Sutter is part of the C++ standards committee that is working hard to make multithreading standard in C++."

Comments

Personal computing?

[Dan East]

"processors with more than eight cores, possible as soon as 2010 -- will transform the world of personal computing"

Exactly what areas of "personal computing" are requiring this horsepower? The only two that come to mind are games and encoding video. The video encoding part is already covered - that scales nicely to multiple threads, and even free encoders will use the extra cores to their full potential. That leaves gaming, which is basically proprietary. The game engine must be designed so that AI, physics, and other CPU-bound algorithms can be executed in parallel. This has already been addressed.

So this begs the question, exactly how will average consumer benefit from an OS and software that can make optimum use of multiple cores, when the performance issues users complain about are not even CPU-bound in the first place?

Dan East

Re:Threads Are Not the Answer

[caerwyn]

This is very, very wrong. Data-set partitioning is certainly one way of achieving parallelism in programming, but it is hardly the only way- nor is it applicable to all domains, as many problems have solutions with too many inter-cell data dependencies. In addition, threads provide a wealth of benefits to application developers by allowing multiple unrelated tasks to be performed simultaneously.

There is, and will always be, overhead associated with parallelization. It may sound great to say "oh, we can farm out parts of this data set to other cores!", but that requires a lot of start-up and tear-down synchronization. It's not at all uncommon for overall performance to be improved by doing something *unrelated* at the same time, requiring less synchronization overhead.

Are threads perfect for everything? No. But calling them the second worse thing to happen to computing is, as best, disingenuous.