Algorithms and Architectures for Parallel Processing: 11th by David Abramson (auth.), Yang Xiang, Alfredo Cuzzocrea,

By David Abramson (auth.), Yang Xiang, Alfredo Cuzzocrea, Michael Hobbs, Wanlei Zhou (eds.)

This quantity set LNCS 7016 and LNCS 7017 constitutes the refereed court cases of the eleventh overseas convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2011, held in Melbourne, Australia, in October 2011.
The first quantity offers 24 revised ordinary papers and 17 revised brief papers including the summary of the keynote lecture - all rigorously reviewed and chosen from eighty five preliminary submissions. The papers conceal the various dimensions of parallel algorithms and architectures, encompassing basic theoretical techniques, sensible experimental effects, and advertisement parts and platforms and concentrate on wide components of parallel and disbursed computing, i.e., architectures, algorithms and networks, and structures and applications.

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Additional info for Algorithms and Architectures for Parallel Processing: 11th International Conference, ICA3PP, Melbourne, Australia, October 24-26, 2011, Proceedings, Part I

Sample text

Different parts of a computational unit u Generally spoken, a computational unit u consists of three parts (see Figure 4): – excl1 (u): u accesses only exclusive variables – shared(u): u accesses shared and exclusive variables alike – excl2 (u): u accesses only exclusive variables Each of these parts can also be empty. Based on this observation we define: Lu := shared(u) = ∅ heldu , all locks, otherwise where heldu := {Lock m | m held throughout shared(u)} This means: Lu consists of the locks held throughout shared(u), if shared(u) is not empty (denoted by heldu above); otherwise Lu equals the set of all locks.

1 Introduction As multi-core processors have become more and more ubiquitous in recent years, programmers are faced with the challenge of writing parallel programs to leverage this computing power. Yet, writing parallel programs is inherently harder than sequential ones: Among other difficulties, concurrency related bugs, such as deadlocks, atomicity and order violations [1], tend to appear randomly and are troublesome to reproduce and fix – especially if several variables are involved. How can we support programmers in this tedious work and improve existing tools?

In [11] control dependencies were completely ignored. One final aspect that has yet to be clarified is how exactly one can detect control dependencies during dynamic analysis. To do so, we use the (a) if-else construct idea of reconvergence points introduced in [12]. When encountering a conditional jump, the jump target is jmp (cond) probed to determine the type of control flow construct: For example, if the target is preceded by an uncondiif part if tional forward jump, we have encountered an if-else construct; the reconvergence point is the target of the unconditional jump.

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