By Nagarajan Kanna, Jaspal Subhlok (auth.), Guang R. Gao, Lori L. Pollock, John Cavazos, Xiaoming Li (eds.)
Itisourpleasuretopresentthepapersacceptedforthe22ndInternationalWo- store on Languages and Compilers for Parallel Computing held in the course of October 8–10 2009 in Newark Delaware, united states. considering the fact that 1986, LCPC has turned a necessary venueforresearchersto reportonworkinthegeneralareaofparallelcomputing, high-performance machine structure and compilers. LCPC 2009 endured this custom and particularly prolonged the realm of curiosity to new parallel computing accelerators similar to the IBM telephone Processor and picture Processing Unit (GPU). This 12 months we acquired fifty two submissions from 15 international locations. every one submission receivedatleastthreereviewsandmosthadfour.ThePCalsosoughtadditional externalreviewsforcontentiouspapers.ThePCheldanall-dayphoneconference on August 24 to debate the papers. notebook participants who had a con?ict of curiosity have been requested to go away the decision quickly while the corresponding papers have been mentioned. From the fifty two submissions, the computer chosen 25 complete papers and five brief paperstobeincludedintheworkshopproceeding,representinga58%acceptance fee. We have been lucky to have 3 keynote speeches, a panel dialogue and an educational during this year’s workshop. First, Thomas Sterling, Professor of computing device technological know-how at Louisiana country college, gave a keynote speak titled “HPC in part swap: in the direction of a brand new Parallel Execution Model.” Sterling argued new multi-dimensional examine thrust was once required to achieve the layout ambitions in regards to strength, complexity, clock expense and reliability within the new parallel c- puter systems.ParalleX,anexploratoryexecutionmodeldevelopedbySterling’s team was once brought to lead the co-design of recent architectures, programming tools and approach software.
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Extra info for Languages and Compilers for Parallel Computing: 22nd International Workshop, LCPC 2009, Newark, DE, USA, October 8-10, 2009, Revised Selected Papers
Sample text
P. P. G. Dietz Table 3. Replacing OpenMP constructs with AFN Library routines OpenMP Constructs/Routines AFN Lib Routines for OpenMP #pragma omp barrier =⇒ afn barrier omp(); #pragma omp critical afn lock omp(); { /* structured-block */ } =⇒ { /* structured-block */ } afn unlock omp(); omp init lock(lock) =⇒ afn alloc omp() omp destroy lock(lock) =⇒ afn free omp() omp set lock(lock) =⇒ afn lock omp() omp unset lock(lock) =⇒ afn unlock omp() source-to-source translator. 2 which features GOMP [11], an OpenMP implementation for GCC.
The pContainer component is the basic storage unit for data. For the stapl pList, we use the stl list as the component. Similarly, for other pContainers, the components are extensions of stl containers or other The STAPL pList 21 Table 1. Representative methods of the pList container pList Interface Description Collective Operations (must be called by all locations) p list(size t N, const T& value = T()) Creates a pList with N elements, each of which is a copy of value. p list(size t N, partition type& ps) Creates a pList with N elements based on the given partition strategy.
These non-blocking methods allow for better communication/computation overlap and enable the stapl RTS to aggregate messages to reduce the communication overhead [19]. Since there is no data replication, operations like push back and push front, if invoked concurrently, may produce serialization in the locations managing the head and the tail of the list. For this reason we added two new methods to the pList interface, push anywhere and push anywhere async, that allow the pList to insert the element in an unspecified location in order to minimize communication and improve concurrency.