Abbrevation
PMAM
City
San Francisco
Country
United States
Deadline Paper
Start Date
End Date
Abstract

Rapid advancements in multicore and chip&#8211;level multi&#8211;threading<br>technologies open new challenges and make multicore systems a part of the<br>computing landscape&#046; From high&#8211;end servers to mobile phones, multicores<br>and manycores are steadily entering every single aspect of the information<br>technology&#046;<br>However most programmers are trained in sequential programming, yet most<br>existing parallel programming models are prone to errors such as data race<br>and deadlock&#046; Therefore to fully utilise multicore and manycore hardware,<br>parallel programming models that allow easy transition of sequential<br>programs to parallel programs with good performance and enable development<br>of error&#8211;free codes are urgently needed&#046;<br>This workshop is dedicated primarily to gather researchers and<br>practitioners addressing the main challenges and share experiences in the<br>emerging multicore and manycore software engineering and distributed<br>programming paradigm&#046; This workshop aims to provide a discussion forum for<br>people interested in programming environments, models, tools and<br>applications specifically designed for parallel multicore and manycore<br>hardware environments&#046;<br>The program committee cordially invites any novel research ideas in (but<br>not limited to) the following topics:<br>programming models and systems for multicore, manycore, and clusters of multicore/manycore<br>multicore and manycore software engineering<br>parallel and distributed algorithms on GPU and multicore clusters<br>parallel libraries and frameworks<br>performance analysis, efficiency and effectiveness<br>massively parallel processing on multicore/manycore systems and clusters<br>automated parallelization and compilation techniques<br>debugging and performance autotuning tools and techniques for multicore/manycore applications<br>parallel algorithms, applications and benchmarks on multicore/manycore systems<br>runtime power/energy management on multicore/manycore systems and clusters<br>fault tolerance and resilience<br>