This paper addresses the issue of compiling concurrent loop nests in the presence of complicated array references and irregularly distributed arrays. Arrays accessed within loops may contain accesses that make it impossible to precisely determine the reference pattern at compile time. This paper proposes a run time support mechanism that is used effectively by a compiler to generate efficient code in these situations. The compiler accepts as input a Fortran 77 program enhanced with specifications for distributing data, and outputs a message passing program that runs on the nodes of a distributed memory machine. The runtime support for the compiler consists of a library of primitives designed to support irregular patterns of distributed array accesses and irregularly distributed array partitions. A variety of performance results on the Intel iPSC/860 are presented.>

Compilers for data-parallel languages such as Fortran D and High-Performance Fortran use data alignment and distribution specifications as the basis for translating programs for execution on MIMD distributed-memory machines. This paper describes techniques for generating efficient code for programs that use block-cyclic distributions. These techniques can be applied to programs with symbolic loop bounds, symbolic array dimensions, and loops with non-unit strides. We present algorithms for computing the data elements that need to be communicated among processors both for loops with unit and non-unit strides, a linear-time algorithm for computing the memory access sequence for loops with non-unit strides, and experimental results for a hand-compiled test case using block-cyclic distributions

Fortran D and High Performance Fortran are languages designed to support efficient data-parallel programming on a variety of parallel architectures. The goal of the D Editor is to provide a tool that allows scientists to use these languages efficiently. The D Editor combines analyses for shared memory machines and compiler optimizations for distributed memory machines. By cooperating with the underlying compiler, it can provide novel information on partitioning, parallelism, and communication based on compile time analysis at the level of the original Fortran program. The D Editor uses color coding and a collection of graphical displays to help the user to zoom in on portions of the program containing sequentialized code or expensive communication. The prototype implementation is useful for interactively displaying the results of compile time analysis; however, it has a number of shortcomings that must be addressed. Future enhancements will provide additional advice and transformation capabilities. We believe the D Editor is representative of a new generation of tools that will be needed to assist scientists to fully exploit languages such as High Performance Fortran.>

Distributed shared memory (DSM) systems provide an illusion of shared memory on distributed memory systems such as workstation networks and some parallel computers such as the Cray T3D and Convex SPP-1. On these systems, users can write programs using a shared memory style of programming instead of message passing which is tedious and error prone. Our experience with one such system TreadMarks, has shown that a large class of applications does not perform well on these systems. TreadMarks is a software distributed shared memory system designed by Rice University researchers to run on networks of workstations and massively parallel computers. Due to the distributed nature of the memory system, shared memory synchronization primitives such as locks and barriers often cause significant amounts of communication. We have provided a set of powerful primitives that will alleviate the problems with locks and barriers on such systems. We have designed two sets of primitives the first set maintains coherence and is easy to use by a programmer, the second set does not maintain coherence and is best used by a compiler. These primitives require that the underlying DSM be enhanced. We have implemented some of our primitives on the TreadMarks DSM system and obtained reasonable performance improvements on application kernels from molecular dynamics and numerical analysis. Furthermore, we have identified key compiler optimizations that use the noncoherent primitives to reduce synchronization overhead and improve the performance of DSM systems.>

No abstract available.

The Fortran D compiler uses data decomposition specifications to automatically translate Fortran programs for execution on MIMD distributed-memory machines. This paper introduces and classifies a number of advanced optimizations needed to achieve acceptable performance; they are analyzed and empirically evaluated for stencil computations. Profitability formulas are derived for each optimization. Results show that exploiting parallelism for pipelined computations, reductions, and scans is vital. Message vectorization, collective communication, and efficient coarsegrain pipelining also significantly affect performance. 1 Introduction Parallel computing represents the only plausible way to continue to increase the computational power available to computational scientists and engineers. However, parallel computers are not likely to be widely successful until they are also easy to program. MIMD distributed-memory machines such as the Intel iPSC/860 present the most difficult programming m...

Algorithms exist for compiling Fortran D for MIMD (multiple-instruction multiple-data) distributed-memory machines, but they are significantly restricted in the presence of procedure calls. The authors present interprocedural analysis, optimization, and code generation algorithms for Fortran D that limit compilation to only one pass over each procedure. This is accomplished by collecting summary information after edits, and then compiling procedures in reverse topological order to propagate necessary information. Delaying instantiation of the computation partition, communication, and dynamic data decomposition is key to enabling interprocedural optimization. Recompilation analysis preserves the benefits of separate compilation. Empirical results show that interprocedural optimization is crucial in achieving acceptable performance for a common application.>

Massivelyparallel MIMD distributed-memory machines can provide enormous computation power.