By J. A. Bergstra, J. W. Klop (auth.), Wolfgang Bibel, Klaus P. Jantke (eds.)
Read or Download Mathematical Methods of Specification and Synthesis of Software Systems '85: Proceedings of the International Spring School Wendisch-Rietz, GDR, April 22–26, 1985 PDF
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Extra resources for Mathematical Methods of Specification and Synthesis of Software Systems '85: Proceedings of the International Spring School Wendisch-Rietz, GDR, April 22–26, 1985
1 Benchmark 1 In the ﬁrst benchmark, we aimed at observing the behavior of MHS2 for small scenarios (N = 40, M = 40, L = 2) where all minimal candidates can be cal1 , culated. In Figure 3, we observe both the speedup (deﬁned as Sup(np) = TTnp where Tnp is the time needed to solve the problem for np processes) and the ) for both the stride and random load eﬃciency (deﬁned as Ef (np) = Sup(np) np distribution functions. The analysis of Figure 3 shows diﬀerent speedup/eﬃciency patterns for r values.
F i r s t _ c o l u m n u n t i l j > p r o d u c t . l a s t _ c o l u m n loop from k := l e f t . f i r s t _ c o l u m n u n t i l k > l e f t . l a s t _ c o l u m n loop p r o d u c t [ i , j ] := p r o d u c t [ i , j ] + l e f t [ i , k ] ∗ right [ k , j ] k := k + 1 end j := j + 1 end i := i + 1 end left . free ; right . free end Listing 6. Matrix multiplication worker using slices and views For the performance measurement, the matrix multiplication test multiplies a 2000 to 800 matrix with an 800 to 2000 matrix.
More specifically, every object in SCOOP belongs to exactly one processor and only this processor has access to the state of the object. A processor can however be instructed to execute a call on behalf of another processor, by adding the call to the processor’s request queue. Also this regime oﬀers protection from data races. Unfortunately, the strict avoidance of shared memory has severe performance disadvantages when trying to parallelize various commonplace computational problems. As an example, Listing 1 shows an in-place Quicksort algorithm written in SCOOP.