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Cilk Plus differs from Cilk and Cilk++ by adding array extensions, being incorporated in a commercial compiler (from Intel), and compatibility with existing debuggers. [ 8 ] Cilk Plus was first implemented in the Intel C++ Compiler with the release of the Intel compiler in Intel Composer XE 2010.
In computer programming, array slicing is an operation that extracts a subset of elements from an array and packages them as another array, possibly in a different dimension from the original. Common examples of array slicing are extracting a substring from a string of characters, the " ell " in "h ell o", extracting a row or column from a two ...
Intel Parallel Building Blocks (PBB) was a collection of three programming solutions designed for multithreaded parallel computing. PBB consisted of Cilk Plus, Threading Building Blocks (TBB) and Intel Array Building Blocks (ArBB). [1] [2] [3]
Array programming is very well suited to implicit parallelization; a topic of much research nowadays.Further, Intel and compatible CPUs developed and produced after 1997 contained various instruction set extensions, starting from MMX and continuing through SSSE3 and 3DNow!, which include rudimentary SIMD array capabilities.
In computer programming, program slicing is the computation of the set of program statements, the program slice, that may affect the values at some point of interest, referred to as a slicing criterion. Program slicing can be used in debugging to locate source of errors more easily. Other applications of slicing include software maintenance ...
Intel C++ Compiler, GNU Compiler Collection since GCC 6, and Clang since clang 7 allow for a simplified approach, with the compiler taking care of function duplication and selection. GCC and clang requires explicit target_clones labels in the code to "clone" functions, [ 20 ] while ICC does so automatically (under the command-line option /Qax ).
Intel oneAPI DPC++/C++ Compiler is available for Windows and Linux and supports compiling C, C++, SYCL, and Data Parallel C++ (DPC++) source, targeting Intel IA-32, Intel 64 (aka x86-64), Core, Xeon, and Xeon Scalable processors, as well as GPUs including Intel Processor Graphics Gen9 and above, Intel X e architecture, and Intel Programmable Acceleration Card with Intel Arria 10 GX FPGA. [5]
The programming control structures on which autoparallelization places the most focus are loops, because, in general, most of the execution time of a program takes place inside some form of loop. There are two main approaches to parallelization of loops: pipelined multi-threading and cyclic multi-threading. [ 3 ]