Facing the Multicore - Challenge II: Aspects of New by James Reinders (auth.), Rainer Keller, David Kramer,

By James Reinders (auth.), Rainer Keller, David Kramer, Jan-Philipp Weiss (eds.)

This state of the art survey positive aspects subject matters relating to the impression of multicore, manycore, and coprocessor applied sciences in technological know-how and for large-scale functions in an interdisciplinary surroundings. The papers hide problems with present study in mathematical modeling, layout of parallel algorithms, points of microprocessor structure, parallel programming languages, hardware-aware computing, heterogeneous structures, manycore applied sciences, functionality tuning, and necessities for large-scale purposes. The contributions offered during this quantity provide a survey at the cutting-edge, the techniques and views for destiny advancements. they're an end result of an inspiring convention conceived and arranged via the editors on the Karlsruhe Institute expertise (KIT) in September 2011. The twelve revised complete papers awarded including contributed papers specialize in mix of latest points of microprocessor applied sciences, parallel purposes, numerical simulation, and software program improvement; therefore they truly express the opportunity of rising applied sciences within the quarter of multicore and manycore processors which are paving the best way in the direction of own supercomputing and extremely most probably in the direction of exascale computing.

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The FFT kernel is somewhere between these two extremes and can potentially run well on accelerators but requires some optimization effort. Several PRACE-PP “Future Technology” prototypes were used for benchmarking. Final results of these prototypes can be found in [25]. An overview of the different hardware is given in Table 2; the mapping between languages and hardware can be found in Table 1. We chose double-precision arithmetic and compared the whole time of the main mathematical routine, which included the time for data movements to and from accelerator devices.

ArBB language extensions are underlined. 0; f o r ( u s i ze j = 0 , j < L e v e l . l e n g t h ( ) , j ++) { y p o i n t += a l p h a [ j ] ∗ mul reduce ( max( 1 − abs ( L e v e l [ j ] ∗ D a t a P o i n t − I n d e x [ j ] ) , 0 ) ) ; } en d f o r ; } }; map( l o c a l : : e v a l G r i d P o i n t ) ( s t o r a g e s i z e , D a t a se t , L e v e l , Index , a l p h a , y ) ; } astrophysical DR5 dataset is highly clustered. 3 · 10−4 . As shown in [8], computation with single precision is sufficient.

The difference in performance has been further intensified by the fact that Chapel and X10 were amongst the few languages which could not make use of library calls. The compiler releases used for Chapel and X10 were mostly proof-of-concepts. Looking at the reported development time and lines of code, Chapel clearly outperformed all other languages. Within PRACE1IP, we are monitoring progress made with new Chapel compiler releases. UPC and CAF have been selected for studies on more complex benchmark codes.

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