Abstract: The use of pointers and indirect memory accesses in the program, as well as the complex control flow are some of the main weaknesses of the static analysis of programs. The program properties investigated by this analysis are too conservative to accurately describe program behavior and hence they prevent parallel execution of the program. The application of dynamic analysis allows us to expand the capabilities of semi-automatic parallelization. In the SAPFOR system (System FOR Automated Parallelization), a dynamic analysis tool has been implemented, based on on the instrumentation of the LLVM representation of an analyzed program, which allows the system to explore programs in both C and Fortran programming languages. The capabilities of the static analysis implemented in SAPFOR are used to reduce the overhead program execution, while maintaining the completeness of the analysis. The use of static analysis allows to reduce the number of analyzed memory accesses and to ignore scalar variables, which can be explored in a static way. The developed tool was tested on performance tests from the NAS Parallel Benchmarks package for C and Fortran languages. The implementation of dynamic analysis, in addition to traditional types of data dependencies (flow, anit, output), allows us to determine privitizable variables and a possibility of pipeline execution of loops. Together with the capabilities of DVM and OpenMP these greatly facilitates program parallelization and simplify insertion of the appropriate compiler directives.

Abstract: The system for automated parallelization SAPFOR (System FOR Automated Parallelization) includes tools for program analysis and transformation. The main goal of the system is to reduce the complexity of program parallelization. SAPFOR system is focused on the investigation of multilingual applications in Fortran and C programming languages. The low-level LLVM IR representation is used in SAPFOR for program analysis. This representation allows us to perform various IR-level optimizations to improve the quality of program analysis. At the same time, it loses some features of the program, which are available in its higher level representation. One of these features is the multi-dimensional structure of the arrays. Data dependence analysis is one of the main problems which should be solved to automate program parallelization. Moreover, such an analysis belongs to the class of NP-hard problems. Knowledge of the multidimensional structure of arrays allows in many cases to take into account the structure of index expressions in calls to arrays and reduce the complexity of the analysis. In addition, the use of multi-dimensional arrays allows us to use multi-dimensional processor matrix and to parallelize a whole loop nests, rather than a single loop in the nest. So, parallelism of a program is going to be increased. These opportunities are natively supported in the DVM system. This paper discusses the approach used in the SAPFOR system to recover the form of multi-dimensional arrays by their linearized representation in LLVM IR. The proposed approach has been successfully evaluated on various applications including performance tests from the NAS Parallel Benchmarks suite.

Abstract: DVM-system is designed for the development of parallel programs of scientific and technical calculations in the C-DVMH and Fortran-DVMH languages. These languages use a single DVMH-model of parallel programming model and are an extension of the standard C and Fortran languages with parallelism specifications in the form of compiler directives. The DVMH model makes it possible to create efficient parallel programs for heterogeneous computing clusters, in the nodes of which accelerators, graphic processors or Intel Xeon Phi coprocessors can be used as computing devices along with universal multi-core processors. The article presents new features of DVM-system that have been developed recently.

Abstract: DVM-system is designed for the development of parallel programs of scientific and technical calculations in the C-DVMH and Fortran-DVMH languages. These languages use a single DVMH-model of parallel programming model and are an extension of the standard C and Fortran languages with parallelism specifications in the form of compiler directives. The DVMH model makes it possible to create efficient parallel programs for heterogeneous computing clusters, in the nodes of which accelerators, graphic processors or Intel Xeon Phi coprocessors can be used as computing devices along with universal multi-core processors. The article describes the method of debugging parallel programs in DVM-system, as well as new features of DVM-debugger.

Abstract: DVM-system is designed for the development of parallel programs of scientific and technical calculations in the C-DVMH and Fortran-DVMH languages. These languages use a single DVMH-model of parallel programming model and are an extension of the standard C and Fortran languages with parallelism specifications in the form of compiler directives. The DVMH model makes it possible to create efficient parallel programs for heterogeneous computing clusters, in the nodes of which accelerators, graphic processors or Intel Xeon Phi coprocessors can be used as computing devices along with universal multi-core processors. The article describes the experience of the successful using of DVM-system to develop a parallel software code for calculating the problem of radiation magnetic gas dynamics and for research of plasma dynamics in the QSPA channel.