Ilya Ledovskih

A parallel language and its programming system for heterogeneous networks

The paper presents a new parallel language, mpC, designed specially for programming high-performance computations on heterogeneous networks of computers, as well as its supportive programming environment. The main idea underlying mpC is that an mpC application explicitly defines an abstract network and distributes data, computations and communications over the network. The mpC programming environment uses at run time this information as well as information about any real executing network in order to map the application to the real network in such a way that ensures efficient execution of the application on this real network. Experience of using mpC for solving both regular and irregular real-life problems on networks of heterogeneous computers is also presented.

A programming environment for heterogenous distributed memory machines

mpC is a medium level programming language for distributed memory machines (DMM). The language is an ANSI C superset based on the notion of a network comprising virtual processors of different types and performances connected with links of different bandwidths. It allows the user to describe a network topology, create and discard networks, and distribute data and computations over the networks. In other words, the user can specify (dynamically) the topology of his application, and the mpC programming environment will use this (topological) information in run time to ensure the efficient execution of the application on any particular DMM. The paper outlines the principal features of mpC and its programming environment which make them suitable tools to write efficient and portable parallel programs for heterogenous DMM.

Experiments with mpC: Efficient Solving Regular Problems on Heterogeneous Networks of Computers via Irregulation

mpC is a medium-level parallel language for programming heterogeneous networks of computers. It allows to write libraries of parallel routines adaptable to peculiarities of any particular executing multiprocessor system to ensure efficient running. The adaptable routines distribute data and computations in accordance with performances of participating processors. In this case even the problems traditionally considered regular, become irregular. Advantages of mpC for efficient solving of regular problems on heterogeneous networks of computers are demonstrated with an mpC routine implementing Cholesky factorization, with efficiency of the mpC routine being compared with ScaLAPACK one.

Modular parallel programming in mpC for distributed memory machines

The mpC language is an ANSI C superset supporting modular parallel programming for distributed memory machines. It allows the user to specify dynamically an application topology, and the mpC programming environment uses this information in run time to provide the most efficient execution of the program on any particular distributed memory machine. The paper describes the features of mpC and its programming environment which allow to use them for developing libraries of parallel programs.

Refined Description of the C[] Language

In the paper, an accurate and detailed description of the programming language C[] is given. Unlike previous publications on the language, this paper gives a formal definition of a vector, which is used for the description of the semantics of basic constructs. The language updates that appeared after the first publication are discussed. Other vector programming languages are surveyed and compared with C[].

A Language Approach to Computing on Heterogenous Networks

The paper presents a parallel language, mpC, aimed at programming heterogeneous networks. The main idea underlying mpC is that an mpC application explicitly defines an abstract heterogeneous network and distributes data, computations and communications over the network. The mpC programming system uses this information to map the abstract network to any real executing network in such a way that ensures efficient running of the application on this real network. The mapping is performed at run time and based on information about performances of processors and links of the real network, dynamically adapting the program to the executing network. The quality of the mapping depends on accuracy of estimation of processor performances. Special attention in the paper is paid to mpC means ensuring high quality of the estimation.

Managing processes with network objects and their translation

The mpC language and its supportive portable programming environment are aimed at efficiently-portable modular parallel programming heterogeneous networks of computers (HNCs). Unlike traditional tools used for portable programming HNCs, mpC provides more advanced facilities for process management to support efficient portability. The paper presents the abstraction of network object introduced in the mpC language to manage processes constituting a message-passing program in order to ensure efficient execution of mpC applications on any particular HNC. The main attention is paid to the translation of this high-level mechanism into low-level notions of target message-passing programs.