Specifying explicit assigns OpenMP threads to a list of OS proc IDs that have been explicitly specified by using the proclist= modifier, which is required for this affinity type. This includes the low-level API interfaces such as kmp_set_affinity and kmp_get_affinity, which have no effect and will return a nonzero error code. This forces the OpenMP run-time library to behave as if the affinity interface was not supported by the operating system.
Specifying disabled completely disables the thread affinity interfaces. For example, in a topology map, the nearer a node is to the root, the more significance the node has when sorting the threads.
#Intel c compiler flags verbose free#
Specifying compact assigns the OpenMP thread +1 to a free thread context as close as possible to the thread context where the OpenMP thread was placed. Specify KMP_AFFINITY=verbose,none to list a machine topology map. type = none (default)ĭoes not bind OpenMP threads to particular thread contexts however, if the operating system supports affinity, the compiler still uses the OpenMP thread affinity interface to determine machine topology. Not valid with type values of explicit, none, or disabled. The logical and physical types are deprecated but supported for backward compatibility. Physical (deprecated instead use scatter, possibly with an offset value) Logical (deprecated instead use compact, but omit any permute value) Takes the following specifiers: fine, thread, and core String consisting of keyword and specifier. The following table describes the supported specific arguments. The KMP_AFFINITY environment variable uses the following general syntax: Syntaxįor example, to list a machine topology map, specify KMP_AFFINITY=verbose,none to use a modifier of verbose and a type of none.
#Intel c compiler flags verbose software#
Shell, Environment, and Other Software Settings Open MP Tuning Flags the discrete cosine/sine transforms or DCT/DST). Description from FFTW:įFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e.
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