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An oft-mentioned rule of thumb is that a reaction should never be scaled up more than 4 because it may not work as well at the larger scale, and further modi cations of the procedure may be needed This rule is likely honored as often in the breach as the observance, since it is obviously dif cult to accumulate a signi cant quantity of a target compound if scaling up starts at the 1 mg level and is limited to fourfold increases Why should the outcome of a reaction be dependent on the scale at which it is conducted There are several reasons Mixing and heat transfer may be less ef cient when reaction volumes are larger Heterogeneous reactions that depend on reagent transfer between two phases are notorious for problems in scale-up.

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While a chemical step might have been limiting at the smaller scale, the ef ciency of mixing might become limiting at the larger scale The apparatus used for a reaction can never be identical at different scales think of scaling up a 10 mL syringe by 100 For the same reason reagent concentrations may be increased upon scale-up to obtain greater productivity from a reaction, which may affect the yield..

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#include <stdio.h> #include <upc.h> #de ne TBL_SZ 12 main () { static shared int fahrenheit[TBL_SZ]; static shared int step=10; int celsius, i; for(i=MYTHREAD; i < TBL_SZ; i+=THREADS) { celsius= step*i; fahrenheit[i]= celsius*(9.0/5.0) + 32; } if(MYTHREAD==0) for (i=0 ; i < TBL_SZ; i++) { celsius= step*i; printf ("%d \t %d \n", fahrenheit[i], celsius) ; } } The line static shared int fahrenheit [ TBL_SZ]; declares an array fahrenheit of size TBL_SZ of integers, which will be shared by all threads. Thus, any of the threads can directly access any of the elements of fahrenheit. However, UPC establishes a logical partitioning of the shared space so that each variable in shared space is de ned to have af nity to exactly one thread. On some platforms it is signi cantly faster for a thread to access shared variables to which it has af nity than to access shared variables that have af nity to another thread. A shared array such as fahrenheit will be spread across the thread partitions in round-robin fashion such that fahrenheit [ has af nity to thread 0] 0, fahrenheit [ has af nitiy to thread 1, and so on. After each thread gets 1] an element, we wrap around, giving fahrenheit [ THREADS] to thread 0, fahrenheit [ THREADS+1] to thread 1, and so on. This round-robin distribution of shared array elements is the default in UPC, but programmers may also distribute shared arrays by blocks of elements. In later chapters we show how to declare blocked distributions, which has a performance advantage for some applications. In this temperature-conversion example, however, the default distribution of the elements matches the work distribution, as each thread will compute exactly the table elements that have af nity to it.

This chapter provided some excellent tools for Windows NT management. You learned how to add and delete users, change group memberships, and do it all with fast API calls. This opens the door for timesaving batch-automation. You also learned about another COM object, which provides the methods to remotely or locally shut down or restart your system. You also discovered ADSI, the new interface for all kinds of namespaces. You explored the object hierarchy and created tools to enumerate domains, groups, users, services, and even property sets. ADSI allows almost anything. It s your complete toolbox for professional administration. This chapter concludes the long Windows scripting tour we started 24 chapters ago. Scripting has matured, and you now have both the inside knowledge and the tools to efficiently master any challenge true scripting power at your fingertips.

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