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The trade-off between fast branch prediction and good branch prediction is sometimes dealt with by having two branch predictors. The first branch predictor is fast and simple. The second branch predictor, which is slower, more complicated, and with bigger tables, will override a possibly wrong prediction made by the first predictor.
The machine code for the above example using predication might look something like this: [1] ( condition ) do_something ( not condition ) do_something_else Besides eliminating branches, less code is needed in total, provided the architecture provides predicated instructions.
Control dependencies are dependencies introduced by the code or the programming algorithm itself. They control the order in which instructions occur within the execution of code. [4] One common example is an "if" statement. "if" statements create branches in a program.
Fetch the prediction for the addresses of the targets of branches in that run of instructions Select the address corresponding to the branch predicted taken As the predictor RAM can be 5–10% of the size of the instruction cache, the fetch happens much faster than the instruction cache fetch, and so this recurrence is much faster.
This approach is employed in a variety of areas, including branch prediction in pipelined processors, value prediction for exploiting value locality, prefetching memory and files, and optimistic concurrency control in database systems. [1] [2] [3] Speculative multithreading is a special case of speculative execution.
Historically, branch prediction took statistics, and used the result to optimize code. A programmer would compile a test version of a program, and run it with test data. The test code counted how the branches were actually taken. The statistics from the test code were then used by the compiler to optimize the branches of released code.
The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.
Extensively using function pointers to call functions may produce a slow-down for the code on modern processors, because a branch predictor may not be able to figure out where to branch to (it depends on the value of the function pointer at run time) although this effect can be overstated as it is often amply compensated for by significantly ...