By Ralf Karrenberg
Ralf Karrenberg provides Whole-Function Vectorization (WFV), an technique that enables a compiler to instantly create code that exploits data-parallelism utilizing SIMD directions. Data-parallel purposes resembling particle simulations, inventory alternative cost estimation or video interpreting require an identical computations to be played on large quantities of information. with out WFV, one processor center executes a unmarried example of a data-parallel functionality. WFV transforms the functionality to execute a number of cases instantly utilizing SIMD directions. the writer describes a complicated WFV set of rules that features a number of analyses and code iteration options. He exhibits that this strategy improves the functionality of the generated code in a number of use cases.
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Additional info for Automatic SIMD Vectorization of SSA-based Control Flow Graphs
For the sake of brevity, we only show the eﬀects on the updated elements of state d per rule. We assume a non-standard execution model: predicated execution. Regardless of the ﬂow of control, every operation in the program is executed in topological order. However, the state is only updated if the value @(x) of the program point x is true, otherwise the operation has no eﬀect: @(x) is the predicate of x. The value of @ is true for the entry program point, and initially false for all other program points.
The following problem occurs if such an operation has an operand that is a nested data structure: If this data structure is not uniform, we have to generate code that extracts the sequential values from that data structure and creates values of the corresponding scalar data structure for each of the sequential operations. If the operation is allowed to modify the value, we have to introduce additional write-back operations afterwards. 3 shows an example for this. 3 Structures of data passed to unknown functions yield signiﬁcant overhead due to creation of temporary scalar structures.
Vectorization of arbitrary control ﬂow requires to generate mask code that tracks which instances are active at any point of the function. Furthermore, we do not want to discard results of inactive instances after each operation, since that would introduce far too much overhead. Placing only as many blend operations as required, however, is a non-trivial task in the presence of complex loop structures. To our knowledge, WFV is the only vectorization approach that can vectorize arbitrary control ﬂow.
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