In optimizing compilers, data structure choices directly influence the power and efficiency of practical program optimization. A poor choice of data structure can inhibit optimization or slow compilation to the point that advanced optimization features become undesirable. Recently, static single assignment form and the control dependence graph have been proposed to represent data flow and control flow propertiee of programs. Each of these previously unrelated techniques lends efficiency and power to a useful class of program optimization. Although both of these structures are attractive, the difficulty of their construction and their potential size have discouraged their use. We present new algorithms that efficiently compute these data structures for arbitrary control flow graphs. The algorithms use dominance frontiers, a new concept that may have other applications. We also give analytical and experimental evidence that all of these data structures are usually linear in the size of the original program. This paper thus presents strong evidence that these structures can be of practical use in optimization.

... This paper concerns the problem of interprocedural slicing---generating a slice of an entire program, where the slice crosses the boundaries of procedure calls. To solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends previous dependence representations to incorporate collections of procedures (with procedure calls) rather than just monolithic programs. Our main result is an algorithm for interprocedural slicing that uses the new representation. (It should be noted that our work concerns a somewhat restricted kind of slice: Rather than permitting a program to be sliced with respect to program point p and an arbitrary variable, a slice must be taken with respect to a variable that is defined or used at p.) The chief

Aliasing occurs at some program point during execution when two or more names exist for the same location. In a language which allows pointers, the problem of determining the set of pairs of names at a program point which may refer to the same location during program execution is NP-hard. We present an algorithm which safely approximates Interprocedural May Alias in the presence of pointers. This algorithm has been implemented in a prototype analysis tool for C programs. 3 The research reported here was supported, in part, by Siemens Research Corporation and NSF grant CCR8920078. y Department of Computer Science, Rutgers University, New Brunswick, NJ 08903 Contents 1 Introduction 3 2 Problem Representation 6 2.1 Interprocedural Control Flow Graph : : : : : : : : : : : : : : : : : : : : : : : : : : : 6 2.2 Types : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 6 2.3 Object Names : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : ...

Algorithms exist for compiling Fortran D for MIMD distributed-memory machines, but are significantly restricted in the presence of procedure calls. This paper presents 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, 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.

This paper concerns the static analysis of programs that perform destructive updating on heap-allocated storage. We give an algorithm that conservatively solves this problem by using a finite shape-graph to approximate the possible “shapes” that heap-allocated structures in a program can take on. In contrast with previous work, our method M even accurate for certain programs that update cyclic data structures. For example, our method can determine that when the input to a program that searches a list and splices in a new element is a possibly circular list, the output is a possibly circular list.

We present practical approximation methods for computing interprocedural aliases and side effects for a program written in a language that includes pointers, reference parameters and recursion. We present the following results: 1) An algorithm for flow-sensitive interprocedural alias analysis which is more precise and efficient than the best interprocedural method known. 2) An extension of traditional flow-insensitive alias analysis which accommodates pointers and provides a framework for a family of algorithms which trade off precision for efficiency. 3) An algorithm which correctly computes side effects in the presence of pointers. Pointers cannot be correctly handled by conventional methods for side effect analysis. 4) An alias naming technique which handles dynamically allocated objects and guarantees the correctness of data-flow analysis. 5) A compact representation based on transitive reduction which does not result in a loss of precision and improves precision in some cases. 6)...

Static Analysis of programs is indispensable to any software tool, environment, or system that requires compile time information about the semantics of programs. With the emergence of languages like C and LISP, Static Analysis of programs with dynamic storage and recursive data structures has become a field of active research. Such analysis is difficult, and the Static Analysis community has recognized the need for simplifying assumptions and approximate solutions. However, even under the common simplifying assumptions, such analyses are harder than previously recognized. Two fundamental Static Analysis problems are May Alias and Must Alias. The former is not recursive (i.e., is undecidable) and the latter is not recursively enumerable (i.e., is uncomputable), even when all paths are executable in the program being analyzed for languages with if-statements, loops, dynamic storage, and recursive data structures. Categories and Subject Descriptors: D.3.1 [Programming Languages...

The ParaScope parallel programming environment developed to support scientific programming of shared-memory multiprocessors, includes a collection of tools that use global program analysis to help users develop and debug parallel programs. This paper focuses on ParaScope’s compilation system, its parallel program editor, and its parallel debugging system. The compilation system extends the traditional single-procedure compiler by providing a mechanism for managing the compilation of complete programs. Thus, ParaScope can support both traditional single-procedure optimization and optimization across procedure boundaries. The ParaScope editor brings both compiler analysis and user expertise to bear on program parallelization. It assists the knowledgeable user by displaying and managing analysis and by proiiding a variety of interactive program tran.formation.s that are effective in exposing parallelism. The debugging svstem detects and reports timing-dependent errors, called data races, in execution of parallel programs. The system combines static analysis. program instrumentation. and run-time reporting to provide a mechanical system for isolating errors in parallel program executions. Finally, we describe a new project to extend ParaScope to support programming in Fortran D, a machine-independent parallel pro-gramming language intended for use with both distributed-memory and shared-memory parallel computers..

We have developed compiler algorithms that analyze coarse-grained, explicitly parallel programs and restructure their shared data to minimize the number of false sharing misses. The algorithms analyze the per-process data accesses to shared data, use this information to pinpoint the data structures that are prone to false sharing and choose an appropriate transformation to reduce it. The algorithms eliminated an average (across the entire workload) of 64% of false sharing misses, and in two programs more than 90%. However, how well the reduction in false sharing misses translated into improved execution time depended heavily on the memory subsystem architecture and previous programmer efforts to optimize for locality. On a multiprocessor with a large cache configuration and high cache miss penalty, the transformations improved the execution time of programmer-unoptimized applications by as much as 60%. However, on programs where previous programmer efforts to improve data locality had ...

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