Vviewpoints
DOI: 10.1145/1562164.1562179
Viewpoint
Face the inevitable,
Embrace parallelism
Hardware, software, and applications must all evolve
in anticipation of the proliferation of parallelism.

ItooK My first parallel program- ming class in graduate school, approximately 20 years ago. Having attended a fairly well- funded and well-equipped graduate program, my fellow students and I had at our disposal a shared-memory multiprocessor system we could use for experiments. Moreover, we had access to a Cray supercomputer at a nearby su-

percomputing center. The tools available at the time for parallel programming amounted to auto-vectorizing compilers, some vendor-specific performance libraries, and non-standard threading application programming interfaces. Much of the hardware we used was relatively unstable and the tools buggy. It was a daunting task, though we were merely asked to develop paral-

lel versions of simple algorithms, like sorts. The zeitgeist was one of experimentation with immature programming models on cold-war-fueled supercomputer innovation.

How things have changed. While some of the functional components we experimented with were quite large, they really did not approach the vast complexities faced by today’s developers. With the exception of the rarified air of research labs (academic or otherwise), sequential microprocessors comprised the vast majority of computers that were used. However, in the two decades since, mainstream microprocessors have abruptly evolved to become increasingly (overtly) parallel devices.

how Software has changed

Calling modern applications complex does not quite do justice to the state of affairs. It may surprise some readers to learn that hardware vendors often have insight into the architectures of a broad range of applications. For Intel, this spans a fairly large variety of market segments. The reason, of course, is that hardware platform companies have a vested interest in ensuring software runs well (running best is the goal) on their products.

Applications that span hundreds of thousands or millions of lines of code are the norm. The use of externally sourced libraries is fairly commonplace. Many application frameworks are implemented at such a level of abstrac-