By Luc Bougé, Martti Forsell, Jesper Larsson Träff, Achim Streit, Wolfgang Ziegler, Michael Alexander, Stephen Childs
Parallelanddistributedprocessing,althoughwithinthefocusofcomputerscience researchforalongtime,isgainingmoreandmoreimportanceinawidespectrum of purposes. those court cases goal to illustrate using parallel and dispensed processing recommendations in di?erent program ?elds, and try and spark curiosity in novel learn instructions to develop the embracing version of high-performance computing study commonly. the target of those workshops is to speci?cally tackle researchers c- ing from college, and governmental examine companies and application-oriented businesses, so one can shut the space among basically s- enti?c examine and the applicability of the examine principles to real-life difficulties. Euro-Par is an annual sequence of foreign meetings devoted to the promotionandadvancementofallaspectsofparallelanddistributedcomputing. The 2007 occasion used to be the thirteenth factor of the convention. Euro-Par has for a very long time been wanting to allure colocated occasions sharing an identical objective of selling the improvement of parallel and dispensed computing, either as an business procedure and an educational self-discipline, extending the frontier of either the state-of-the-art and the country of the perform. in view that 2006, Euro-Par o?ers researchersthe likelihood to colocate complicated technical workshops back-to-back with the most convention. this is often for a mutual bene?t: the workshops can make the most of all technical and social amenities that are organize for the convention, in order that the organizational initiatives are stored to a minimum point; the convention can depend upon workshopstoexperimentwithspeci?careasofresearchwhicharenotyetmature adequate, or too speci?c, to guide to an o?cial, full-?edged subject on the conference.
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Extra resources for Euro-Par 2007 Workshops: Parallel Processing: HPPC 2007, UNICORE Summit 2007, and VHPC 2007, Rennes, France, August 28-31, 2007, Revised Selected Papers
Sample text
257–266. ACM Press, New York (2004) 9. : Fair Cache Sharing and Partitioning in a Chip Multiprocessor Architecture. In: Proc. of the 13th Intl. Conf. on Paral. Arch. and Comp. , pp. 111–122. IEEE Computer Society, Los Alamitos (2004) 10. : Organizing the Last Line of Defense before Hitting the Memory Wall for CMPs. In: Proc. of the 10th Intl. Symp. High Perf. Comp. , p. 176. IEEE Computer Society, Los Alamitos (2004) 11. : Power Model Validation Through Thermal Measurements. In: Proc. of the 34th Int.
Consider the following sieve block which writes characters to an array: char *p = 0xfeed; sieve { p[0] = ’b’; p[1] = ’e’; p[2] = ’e’; p[3] = ’f’; } Auto-parallelisation of Sieve C++ Programs 27 Without delayed-write combining, the side-effect queue grows significantly with each delayed write: sieve { p[0] = ’b’; // queue: p[1] = ’e’; // queue: p[2] = ’e’; // queue: // p[3] = ’f’; // queue: // } [(0xfeed,1,’b’)] [(0xfeed,1,’b’), [(0xfeed,1,’b’), (0xfeef,1,’e’)] [(0xfeed,1,’b’), (0xfeef,1,’e’), (0xfeee,1,’e’)] (0xfeee,1,’e’), (0xfeee,1,’e’), (0xfef0,1,’f’)] Applying delayed-write combining results in a smaller queue: sieve { p[0] = p[1] = p[2] = p[3] = } ’b’; ’e’; ’e’; ’f’; // // // // queue: queue: queue: queue: [(0xfeed,1,’b’)] [(0xfeed,2,"be")] [(0xfeed,3,"bee")] [(0xfeed,4,"beef")] This optimisation is particularly beneficial for the Mandelbrot benchmark which writes pixels into a contiguous unsigned char array.
COMA adds complexity to locating a data in the memory but at the same time, increases the chances of data being in the local cache. In a Microgrid of microthreaded processors we propose a cache memory based on the COMA approach and allow data to migrate dynamically within the on-chip memory. A significant difference between the on-chip COMA and traditional COMA system is that the traditional COMA system will hold all data in the system without a backing store. However, onchip COMA is unlikely to provide enough space to store so much data.