Параллел кайта ишлаш технологиялари ва замонавий инструментал воситалари
Аннотация
В данной работе рассматриваются реализации параллельных алгоритмов для высокопроизводительных вычислительных систем. Даются понятия программного потока, поточной вычислительной модели, рассмотрены технологии многозадачности и гиперпоточности. Исследованы возможности многоядерных процессоров и инструментальные средства поддержки параллельного программирования.
Ушбу мацолада тезкор хисоблашнинг самарали технологиялари, окимли кайта ишлаш усуллари, параллел тизимларнинг таснифи, бир ядроли процессорларда оцимли цайта ишлаш технологиялари тахлили куриб чикилди. Шунингдек, купядроли процессорларда параллел (окимли) кайта ишлаш жараёнларини янги технология сифатида унумдорликни оширишдаги ахамияти, купядроли процессорларда окимли кайта ишлаш ва замонавий параллелаштиришнинг инструментал воситалари тахлил килинди.
In this article researches the implementation of parallel algorithms, modern high-performance computing systems, program flow, Flynn classification, SISD, SIMD, MISD, API calls, flow computational model, multitasking, hyperthreading technology. Also, the problems of stream processing in tasks on multi-core processors are considered as an effective technology to speed up computations. After the emergence of the concept of parallelism at the command level, the constant progress in the development of microprocessors led to the release of processors with multiple cores. To effectively use the capabilities of multicore processors, it is necessary to understand the features of the flow programming model, as well as the capabilities of the platform hardware. To enable parallel processing of programs, the hardware platform must support the ability to simultaneously execute several program threads. With proper implementation, threading can improve performance through more efficient use of hardware resources. There is a direct correspondence between processes and program threads. There may be multiple threads in the process. All program threads of the same process share the same address space and can thus interact with each other. A program has one or more processes, each process contains one or more threads, and each thread is assigned to be executed by the processor by the operating system scheduler.
Ушбу мацолада тезкор хисоблашнинг самарали технологиялари, окимли кайта ишлаш усуллари, параллел тизимларнинг таснифи, бир ядроли процессорларда оцимли цайта ишлаш технологиялари тахлили куриб чикилди. Шунингдек, купядроли процессорларда параллел (окимли) кайта ишлаш жараёнларини янги технология сифатида унумдорликни оширишдаги ахамияти, купядроли процессорларда окимли кайта ишлаш ва замонавий параллелаштиришнинг инструментал воситалари тахлил килинди.
In this article researches the implementation of parallel algorithms, modern high-performance computing systems, program flow, Flynn classification, SISD, SIMD, MISD, API calls, flow computational model, multitasking, hyperthreading technology. Also, the problems of stream processing in tasks on multi-core processors are considered as an effective technology to speed up computations. After the emergence of the concept of parallelism at the command level, the constant progress in the development of microprocessors led to the release of processors with multiple cores. To effectively use the capabilities of multicore processors, it is necessary to understand the features of the flow programming model, as well as the capabilities of the platform hardware. To enable parallel processing of programs, the hardware platform must support the ability to simultaneously execute several program threads. With proper implementation, threading can improve performance through more efficient use of hardware resources. There is a direct correspondence between processes and program threads. There may be multiple threads in the process. All program threads of the same process share the same address space and can thus interact with each other. A program has one or more processes, each process contains one or more threads, and each thread is assigned to be executed by the processor by the operating system scheduler.