Concurrent programming can improve performance. However, it comes with two drawbacks.
First, concurrent programs can be more difficult to design and reason about than their sequential
counterparts. Second, error conditions that do not exist in sequential programs, such as data race
conditions and deadlock, can make concurrent programs more unreliable. To make concurrent
programming simpler and more reliable, while still providing sufficient performance gains, we
present a concurrency framework based on an existing concurrency initiation mechanism called
Early-Reply is based on the idea that some functions can produce final return values long before
they terminate. Concurrent execution begins when return value of a function is returned to the
caller, allowing the rest of the work of the function to be done on an auxiliary thread. The
simpler sequential programming model can be used by the caller, because the concurrency is
initiated and hidden within the function body. Pike and Sridhar recognized Early-Reply as a way
for sequential programs to get the benefits of concurrent execution. They also discussed using
object-oriented programming to serialize access to data that needs synchronization. Our work
expands on their approach and provides an actual C++ implementation of an Early-Reply based
Our framework simplifies concurrent programming for both users and implementers by allowing
developers to use sequential reasoning, and by providing a minimal framework interface.
Concurrent programming is made more reliable by combining the concurrency synchronization
and initiation into one mechanism within the framework, which isolates where race conditions
and deadlock can occur. Furthermore, this isolation facilitates the development of a simple set
of coding guidelines that can be used by developers (through inspection) or static analysis tools
(through verification) to eliminate race conditions and deadlocks. As a motivating example, we parallelize an instructional compiler that processes multiple input
source files. For each input file; the parsing and semantic analysis execute on the calling thread,
while the code optimization and object code generation execute on an auxiliary thread.
Speedups of 1.5 to 1.7 were observed on a dual processor confirming that sufficient performance
gains are possible.
|Date||17 September 2007|
|Creators||Cook, Stephen Wendell|
|Publisher||Texas A&M University|
|Source Sets||Texas A and M University|
|Type||Book, Thesis, Electronic Thesis, text|
|Format||404543 bytes, electronic, application/pdf, born digital|
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