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All o f these histories demonstrate different kinds o f hazards
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Read/write hazard A thread, tI , reads from a location, t2, then writes to that location, and tI subsequently makes a decision based on its (now invalid) read of t1 This also can be referred to as a stale read Write/write hazard A thread, tI , writes to the same location as t2 in a concurrency unsafe way, leading to lost updates, as in the example given above Write/read hazard A thread, tI , writes to a location and then t2 reads from it before it is safe to do so In some cases, tI may decide to undo its partial update to state due to a subsequent failure, lead ing t2 to make decisions on an invalid snapshot of state that should have never been witnessed This also can be referred to as an unrepeatable read Read/read hazard There is no problem with multiple concurrent threads reading the same shared data simultaneously This property can be exploited to build a critical region variant called a reader/ writer lock to provide better performance for read /read conflicts; this idea is explored more in 6, Data and Control Synchronization
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(This last point is a simplification Normally read / read conflicts are safe in the case of simple shared memory, but there are some cases in which they are not: when a read has a side effect, like reading a stack's guard page, or when reading some data associated with a physical device, it may be nec essary to ensure no two threads try to do it concurrently) Very little of this discussion is specific to the ++ operator itself It just turns out to be a convenient example because it intrinsically exhibits all of the problematic conditions that lead to these timing issues 1 Multiple threads make private copies of data from a shared location 2 Threads publish results back to shared memory, overwriting existing values 3 Compound updates may be made with the intent of establishing or preserving invariants between multiple independent shared locations 4 Threads run concurrently such that their timing overlaps and opera tions interleave
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There is no greater skill that differentiates great concurrent programmers from the rest than the ability to innately predict and consider various tim ings to some reasonable depth of complexity With experience comes the ability to see several steps ahead and proactively identify the timings that can lead to race conditions and other hazards This is especially important when writing sophisticated lock free algorithms, which eschew isolation, immutability, and synchronization in favor of strict discipline and reliance on hardware guarantees, which we'll review in 1 0, Memory Mod els and Lock Freedom
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A fundamental problem is that many program operations are not truly atomic because an operation consists of multiple logical steps, a certain logical step is comprised of many physical steps, or both Atomicity, quite simply, is the property that a single operation or set of operations appear as if they happened at once Any state modifications and side effects performed are completely instantaneous, and no other thread in the system can observe intermediary (and invalid) states that occur in the midst of such an atomic operation Similarly, the atomic operation must not be permitted to fail part way through the update, or if it does so, there must be a corresponding roll back of state updates to the previous state By this definition, atomicity would seldom be practical to achieve, at least physically Although processors guarantee single writes to aligned words of memory are truly atomic, higher level logical operations-like the execution of a single method call on an object, consisting of several statements, function calls, and reads and writes-are not so Simple In fact, sometimes the operations we'd like to make atomic can even span physical machines, perhaps interacting with a Web service or database, at which point the difficulty of ensuring atomicity is greater System wide control mechanisms must be used to achieve atomicity except for very simple read and write operations As already noted, critical regions can simulate atomicity for in-memory updates Transactions, of the ilk found in databases, COM+, and the S y s t e m T r a n s a c t i o n s namespace in NET, are also attractive solutions when multiple or persistent durable resources are involved
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