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Readers/writers protocols are discussed in [And00] and most operating systems texts Reducing the size of the critical section Another approach to improving performance begins with analyzing the implementations of the operations in more detail It may be the case that only part of the operation involves actions that interfere with other operations If so, the size of the critical section can be reduced to that smaller part Notice that this sort of optimization is very easy to get wrong, so it should be attempted only if it will give significant performance improvements over simpler approaches, and the programmer completely understands the interferences in question Nested locks This technique is a sort of hybrid between two of the previous approaches, noninterfering operations and reducing the size of the critical section Suppose we have an ADT with two operations Operation A does a lot of work both reading and updating variable x and then reads and updates variable y in a single statement Operation B reads and writes y Some analysis shows that UEs executing A need to exclude each other, UEs executing B need to exclude each other, and because both operations read and update y, technically, A and B need to mutually exclude each other as well However, closer inspection shows that the two operations are almost noninterfering If it weren't for that single statement where A reads and updates y, the two operations could be implemented in separate critical sections that would allow one A and one B to execute concurrently A solution is to use two locks, as shown in Fig 533 A acquires and holds lockA for the entire operation B acquires and holds lockB for the entire operation A acquires lockB and holds it only for the statement updating y Whenever nested locking is used, the programmer should be aware of the potential for deadlocks and.

This eliminates all the irrelevant detail and makes it easy to see what the problem is (on the bottom line) and where it occurred (the lines above it) So no matter how big the traceback is, the last line always speci es the unhandled exception, and we just have to work back until we nd our program s le

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Notice that we have named the tables using the guideline we discussed earlier In addition, you can see the implementation of our surrogate primary key, a column named objid in all tables Tables such as tbl_ product_instance have a composite primary key that is made up of the primary keys from the two joined tables As it happens, this is also how we name the foreign key columns the shortened table name (no tbl_ prefix) followed by _objid We look at foreign keys in the next section

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double check the code (The classic example of deadlock, stated in terms of the previous example, is as follows: A acquires lockA and B acquires lockB A then tries to acquire lockB and B tries to acquire lockA Neither operation can now proceed) Deadlocks can be avoided by assigning a partial order to the locks and ensuring that locks are always acquired in an order that respects the partial order In the previous example, we would define the order to be lockA < lockB and ensure that lockA is never acquired by a UE already holding lockB Application specific semantic relaxation Yet another approach is to consider partially replicating shared data (the software caching described in [YWC 96 + ]) and perhaps even allowing the copies to be inconsistent if this can be done without affecting the results of the computation For example, a distributed memory solution to the phylogeny problem described earlier might give each UE its own copy of the set of sets already rejected and allow these copies to be out of synch; tasks may do extra work (in rejecting a set that has already been rejected by a task assigned to a different UE), but this extra work will not affect the result of the computation, and it may be more efficient overall than the communication cost of keeping all copies in synch

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