Since all the threads in a process have unhindered access to the shared data space, wouldn't this execution model “trivially” solve all of our IPC problems? Can't we just communicate the data through shared memory and dispense with any other execution models and IPC mechanisms?
If only it were that simple!
One issue is that the access of individual threads to common data must be synchronized. Having one thread read inconsistent data because another thread is part way through modifying it is a recipe for disaster. For example, if one thread is updating a linked list, no other threads can be allowed to traverse or modify the list until the first thread has finished. A code passage that must execute “serially” (i.e., by only one thread at a time) in this manner is termed a “critical section.” The program would fail (intermittently, depending on how frequently a “collision” occurred) with irreparably damaged links unless some synchronization mechanism ensured serial access.
Mutexes, semaphores, and condvars are examples of synchronization tools that can be used to address this problem. These tools are described later in this section.
Although synchronization services can be used to allow threads to cooperate, shared memory per se can't address a number of IPC issues. For example, although threads can communicate through the common data space, this works only if all the threads communicating are within a single process. What if our application needs to communicate a query to a database server? We need to pass the details of our query to the database server, but the thread we need to communicate with lies within a database server process and the address space of that server isn't addressable to us.
The OS takes care of the network-distributed IPC issue because the one interface—message passing—operates in both the local and network-remote cases, and can be used to access all OS services. Since messages can be exactly sized, and since most messages tend to be quite tiny (e.g., the error status on a write request, or a tiny read request), the data moved around the network can be far less with message passing than with network-distributed shared memory, which would tend to copy 4K pages around.