Doi: 10.1145/1400214.1400227
What does the proliferation of concurrency mean for the software you develop?
soFtWArE PrActitionErs todAY could be forgiven if recent microprocessor developments have given them some trepidation about the future of software. While Moore’s Law continues to hold (that is, transistor density continues to double roughly every 18 months), due to both intractable physical limitations and practical engineering considerations, that increasing density is no longer being spent on boosting clock rate, but rather on putting multiple CPU cores on a single CPU die. from the software perspective, this not a revolutionary shift, but rather an evolutionary one: multicore CPUs are not the birthing of a new paradigm, but rather the progression of an old one (multiprocessing) into more widespread deployment. from many recent articles and papers on the subject, however, one might think that this blossoming of concurrency is the coming of the apocalypse that “the free lunch is over.” 10
As practitioners who have long been at the coal face of concurrent systems, we hope to inject some calm reality (if not some hard-won wisdom) into a discussion that has too often descended into hysterics. Specifically, we hope to answer the essential question: what does the proliferation of concurrency mean for
the software that you develop? Perhaps regrettably, the answer to that question is neither simple nor universal— your software’s relationship to concurrency depends on where it physically executes, where it is in the stack of abstraction, and the business model that surrounds it. And given that many software projects now have components in different layers of the abstraction stack spanning different tiers of the architecture, you may well find that even for the software that you write, you do not have one answer but several: some of your code may be able to be left forever executing in sequential bliss, and some of your code may need to be highly parallel and explicitly multithreaded. Further complicating the answer, we will argue that much of your code will not fall neatly into either category: it will be essentially sequential in nature but will need to be aware of concurrency at some level. While we will assert that less—much less—code needs to be parallel than some might fear, it is nonetheless true that writing parallel code remains something of a black art. We will also therefore give specific implementation techniques for developing a highly parallel system. As such, this article will be somewhat dichotomous: we will try to both argue that most code can (and should) achieve concurrency without explicit parallelism, and at the same time elucidate techniques for those who must write explicitly parallel code. Indeed, this article is half stern lecture on the merits of abstinence and half Kama Sutra.
some historical context Before discussing concurrency with respect to today’s applications, it is helpful to explore the history of concurrent execution: even by the 1960s—when the world was still wet with the morning dew of the computer age—it was becoming clear that a single central processing unit executing a single instruction stream would result in unnecessarily limited system performance. While computer designers experimented with different ideas to circumvent this limi-
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