While this approach has the potential to avoid wasted machine time due to stalls, it has the drawback that a thread that's ready to execute a long sequence of instructions may have to wait to execute every instruction. In fine-grained multithreading, the processor switches between threads after each instruction, skipping threads that are stalled. For example, in some older systems, threads were simply implemented as processes, and in the time it took to switch between processes, thousands of instructions could be executed. Of course, for this to be useful, the system must support very rapid switching between threads. Instead of looking for parallelism in the currently executing thread, it may make sense to simply run another thread.

Hardware multithreading provides a means for systems to continue doing useful work when the task being currently executed has stalled-for example, if the current task has to wait for data to be loaded from memory. Thread-level parallelism, or TLP, attempts to provide parallelism through the simultaneous execution of different threads, so it provides a coarser-grained parallelism than ILP, that is, the program units that are being simultaneously executed-threads-are larger or coarser than the finer-grained units-individual instructions. There's essentially no opportunity for simultaneous execution of instructions. The language implementation may be able to reuse the space occupied by previous instances of the same scope, but it guarantees that this optimization will never introduce bugs. Each recursive call of the fib-helper function creates a new scope, containing new variables.

Despite the algorithmic similarity, however, there is an important difference between the iterative algorithm in C and the tail-recursive algorithm in Scheme: the latter has no side effects. One might argue that it isn't “really” recursive it simply casts an iterative algorithm in a tail-recursive form, and this argument has some merit. It is probably better, however, to draw inspiration from the tail-recursive version of the summation example above, and write the following O( n) recursive function:įor a programmer accustomed to writing in a functional style, this code is perfectly natural.

One can write this iterative algorithm in Scheme: Scheme includes (nonfunctional) iterative features. Example 6.83 Efficient Tail-Recursive Fibonacci Function

Openmp fibonacci series c program