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2. Context and Motivation
e. g., arithmetic units enables higher degrees of instruction-level parallelism.
In combination with duplicated register files, techniques such as simultaneous
multithreading can hide memory latency and utilize the available functional
units more efficiently. Duplicating whole cores enables more heterogeneous
parallel workloads. However, workloads such as data-intensive graphic
operations are better served by large data-parallel units. These can come in
the form of vector processing units embedded into a traditional processor, or
modern GPU computing processors that consist of vast numbers of very simple
but highly parallel processing elements. Depending on target applications,
processor vendors mix and match these design options to offer more computational
power to their customers [Hennessy and Patterson, 2007]. However,
exploiting available hardware parallelism remains a task for software developers.
To conclude, multicore processors will play a major role for the foreseeable
future and software developers will need to use the offered parallelism to
fulfill the performance requirements for their software.
2.3. Concurrent vs. Parallel Programming: Definitions
The goal of this section is to clarify the notions of concurrency and parallelism
in order to accurately categorize the programming concepts of this field later
in this dissertation. To this end, this dissertation introduces the additional
notions of concurrent programming and parallel programming, which provide
stronger distinguishing properties and facilitate the discussions in Chapter 3.
2.3.1. Concurrency and Parallelism
Distinction often avoided Defining the two terms concurrency and parallelism
is often avoided in literature. Subramaniam [2011, p. xiv] even claims
“there’s no clear distinction between these two terms in industry[...]”. Others such
as Axford [1990, p. 4,6] and Lea [1999, p. 19] mention the terms, but do not
make a clear distinction between them. However, they indicate the difference
between systems with physical parallelism and systems with merely time
shared execution.
Distinction by execution model from historical perspective Lin and Snyder
[2008, p. 21] explain the situation within its historic context. The term concurrency
was used in the operating system and database communities, which
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