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C, AC, Split-C, Parallel C Preprocessor Unified Parallel C ( UPC ) is an extension of the C programming language designed for high-performance computing on large-scale parallel machines , including those with a common global address space ( SMP and NUMA ) and those with distributed memory (e. g. clusters ).
Single instruction, multiple threads (SIMT) is an execution model used in parallel computing where single instruction, multiple data (SIMD) is combined with multithreading. It is different from SPMD in that all instructions in all "threads" are executed in lock-step.
Task parallelism (also known as function parallelism and control parallelism) is a form of parallelization of computer code across multiple processors in parallel computing environments. Task parallelism focuses on distributing tasks —concurrently performed by processes or threads —across different processors.
Each and every programming language has an execution model, which determines the manner in which the units of work (that are indicated by program syntax) are scheduled for execution. Detailed examples of the specification of execution models of a few popular languages include those of Python, [1] the execution model of the Unified Parallel C ...
There are many pleasingly parallel problems that have such relatively independent code blocks, in particular systems using pipes and filters. For example, when producing live broadcast television, the following tasks must be performed many times a second: Read a frame of raw pixel data from the image sensor,
pthreads defines a set of C programming language types, functions and constants. It is implemented with a pthread.h header and a thread library. There are around 100 threads procedures, all prefixed pthread_ and they can be categorized into five groups: Thread management – creating, joining threads etc. Mutexes; Condition variables
Loop-level parallelism is a form of parallelism in software programming that is concerned with extracting parallel tasks from loops.The opportunity for loop-level parallelism often arises in computing programs where data is stored in random access data structures.
YUCCA is a Sequential to Parallel automatic code conversion tool developed by KPIT Technologies Ltd. Pune. It takes input as C source code which may have multiple source and header files. It gives output as transformed multi-threaded parallel code using pthreads functions and OpenMP constructs. The YUCCA tool does task and loop level ...