95,389 research outputs found

    Coarse-grained reconfigurable array architectures

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    Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

    A compiler approach to scalable concurrent program design

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    The programmer's most powerful tool for controlling complexity in program design is abstraction. We seek to use abstraction in the design of concurrent programs, so as to separate design decisions concerned with decomposition, communication, synchronization, mapping, granularity, and load balancing. This paper describes programming and compiler techniques intended to facilitate this design strategy. The programming techniques are based on a core programming notation with two important properties: the ability to separate concurrent programming concerns, and extensibility with reusable programmer-defined abstractions. The compiler techniques are based on a simple transformation system together with a set of compilation transformations and portable run-time support. The transformation system allows programmer-defined abstractions to be defined as source-to-source transformations that convert abstractions into the core notation. The same transformation system is used to apply compilation transformations that incrementally transform the core notation toward an abstract concurrent machine. This machine can be implemented on a variety of concurrent architectures using simple run-time support. The transformation, compilation, and run-time system techniques have been implemented and are incorporated in a public-domain program development toolkit. This toolkit operates on a wide variety of networked workstations, multicomputers, and shared-memory multiprocessors. It includes a program transformer, concurrent compiler, syntax checker, debugger, performance analyzer, and execution animator. A variety of substantial applications have been developed using the toolkit, in areas such as climate modeling and fluid dynamics

    Distributed memory compiler design for sparse problems

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    A compiler and runtime support mechanism is described and demonstrated. The methods presented are capable of solving a wide range of sparse and unstructured problems in scientific computing. The compiler takes as input a FORTRAN 77 program enhanced with specifications for distributing data, and the compiler outputs a message passing program that runs on a distributed memory computer. The runtime support for this compiler is a library of primitives designed to efficiently support irregular patterns of distributed array accesses and irregular distributed array partitions. A variety of Intel iPSC/860 performance results obtained through the use of this compiler are presented

    Parallel machine architecture and compiler design facilities

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    The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role

    Minimum entropy restoration using FPGAs and high-level techniques

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    One of the greatest perceived barriers to the widespread use of FPGAs in image processing is the difficulty for application specialists of developing algorithms on reconfigurable hardware. Minimum entropy deconvolution (MED) techniques have been shown to be effective in the restoration of star-field images. This paper reports on an attempt to implement a MED algorithm using simulated annealing, first on a microprocessor, then on an FPGA. The FPGA implementation uses DIME-C, a C-to-gates compiler, coupled with a low-level core library to simplify the design task. Analysis of the C code and output from the DIME-C compiler guided the code optimisation. The paper reports on the design effort that this entailed and the resultant performance improvements

    A Compiler and Runtime Infrastructure for Automatic Program Distribution

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    This paper presents the design and the implementation of a compiler and runtime infrastructure for automatic program distribution. We are building a research infrastructure that enables experimentation with various program partitioning and mapping strategies and the study of automatic distribution's effect on resource consumption (e.g., CPU, memory, communication). Since many optimization techniques are faced with conflicting optimization targets (e.g., memory and communication), we believe that it is important to be able to study their interaction. We present a set of techniques that enable flexible resource modeling and program distribution. These are: dependence analysis, weighted graph partitioning, code and communication generation, and profiling. We have developed these ideas in the context of the Java language. We present in detail the design and implementation of each of the techniques as part of our compiler and runtime infrastructure. Then, we evaluate our design and present preliminary experimental data for each component, as well as for the entire system
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