7.3.4 Data Ownership
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7.3.4 Data Ownership

Data ownership partitions a given data structure over the threads or CPUs, so that each thread/CPU accesses its subset of the data structure without any synchronization overhead whatsoever. However, if one thread wishes to access some other thread's data, the first thread is unable to do so directly. Instead, the first thread must communicate with the second thread, so that the second thread performs the operation on behalf of the first, or, alternatively, migrates the data to the first thread.

Data ownership might seem arcane, but it is used very frequently:

1. Any variables accessible by only one CPU or thread (such as `auto` variables in C and C++) are owned by that CPU or process.
2. An instance of a user interface owns the corresponding user's context. It is very common for applications interacting with parallel database engines to be written as if they were entirely sequential programs. Such applications own the user interface and his current action. Explicit parallelism is thus confined to the database engine itself.
3. Parametric simulations are often trivially parallelized by granting each thread ownership of a particular region of the parameter space.

If there is significant sharing, communication between the threads or CPUs can result in significant complexity and overhead. Furthermore, if the most-heavily used data happens to be that owned by a single CPU, that CPU will be a ``hot spot'', sometimes with results resembling that shown in Figure . However, in situations where no sharing is required, data ownership achieves ideal performance, and with code that can be as simple as the sequential-program case shown in Figure . Such situations are often referred to as ``embarrassingly parallel'', and, in the best case, resemble the situation previously shown in Figure .

Another important instance of data ownership occurs when the data is read-only, in which case, all threads can ``own'' it via replication.