The Experts below are selected from a list of 144 Experts worldwide ranked by ideXlab platform

Michael Wolfe - One of the best experts on this subject based on the ideXlab platform.

  • elimination of redundant Array Subscript range checks
    Programming Language Design and Implementation, 1995
    Co-Authors: Priyadarshan Kolte, Michael Wolfe
    Abstract:

    This paper presents a compiler optimization algorithm to reduce the run time overhead of Array Subscript range checks in programs without compromising safety. The algorithm is based on partial redundancy elimination and it incorporates previously developed algorithms for range check optimization. We implemented the algorithm in our research compiler, Nascent, and conducted experiments on a suite of 10 benchmark programs to obtain four results: (1) the execution overhead of naive range checking is high enough to merit optimization, (2) there are substantial differences between various optimizations, (3) loop-based optimizations that hoist checks out of loops are effective in eliminating about 98% of the range checks, and (4) more sophisticated analysis and optimization algorithms produce very marginal benefits.

  • PLDI - Elimination of redundant Array Subscript range checks
    Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation - PLDI '95, 1995
    Co-Authors: Priyadarshan Kolte, Michael Wolfe
    Abstract:

    This paper presents a compiler optimization algorithm to reduce the run time overhead of Array Subscript range checks in programs without compromising safety. The algorithm is based on partial redundancy elimination and it incorporates previously developed algorithms for range check optimization. We implemented the algorithm in our research compiler, Nascent, and conducted experiments on a suite of 10 benchmark programs to obtain four results: (1) the execution overhead of naive range checking is high enough to merit optimization, (2) there are substantial differences between various optimizations, (3) loop-based optimizations that hoist checks out of loops are effective in eliminating about 98% of the range checks, and (4) more sophisticated analysis and optimization algorithms produce very marginal benefits.

Cheng-ming Yang - One of the best experts on this subject based on the ideXlab platform.

  • Data dependence analysis for Array references
    Journal of Systems and Software, 2000
    Co-Authors: Tsung-chuan Huang, Cheng-ming Yang
    Abstract:

    Abstract Data dependence analysis is essential in order to determine whether a loop can be vectorized or parallelized. It is used to investigate whether two memory references in a loop are in the same location. In this paper we present a new scheme of exact data dependence analysis for Array Subscript analysis in parallel programs, called interval reduction (IR) test. This method reduces the solution interval of each constraint variable in the dependence equation by repeated projection. Once the effective solution interval of any variable shrinks to empty, this linear diophantine equation has no integer solution and the memory accesses subject to this constraint are then independent. Otherwise, all the integer solutions can be found, and thus the dependence distance can be computed as well. Experimental results are also presented to show its effectiveness compared to the Power test and the Omega test.

Priyadarshan Kolte - One of the best experts on this subject based on the ideXlab platform.

  • elimination of redundant Array Subscript range checks
    Programming Language Design and Implementation, 1995
    Co-Authors: Priyadarshan Kolte, Michael Wolfe
    Abstract:

    This paper presents a compiler optimization algorithm to reduce the run time overhead of Array Subscript range checks in programs without compromising safety. The algorithm is based on partial redundancy elimination and it incorporates previously developed algorithms for range check optimization. We implemented the algorithm in our research compiler, Nascent, and conducted experiments on a suite of 10 benchmark programs to obtain four results: (1) the execution overhead of naive range checking is high enough to merit optimization, (2) there are substantial differences between various optimizations, (3) loop-based optimizations that hoist checks out of loops are effective in eliminating about 98% of the range checks, and (4) more sophisticated analysis and optimization algorithms produce very marginal benefits.

  • PLDI - Elimination of redundant Array Subscript range checks
    Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation - PLDI '95, 1995
    Co-Authors: Priyadarshan Kolte, Michael Wolfe
    Abstract:

    This paper presents a compiler optimization algorithm to reduce the run time overhead of Array Subscript range checks in programs without compromising safety. The algorithm is based on partial redundancy elimination and it incorporates previously developed algorithms for range check optimization. We implemented the algorithm in our research compiler, Nascent, and conducted experiments on a suite of 10 benchmark programs to obtain four results: (1) the execution overhead of naive range checking is high enough to merit optimization, (2) there are substantial differences between various optimizations, (3) loop-based optimizations that hoist checks out of loops are effective in eliminating about 98% of the range checks, and (4) more sophisticated analysis and optimization algorithms produce very marginal benefits.

K. Kennedy - One of the best experts on this subject based on the ideXlab platform.

  • Integer programming for Array Subscript analysis
    IEEE Transactions on Parallel and Distributed Systems, 1995
    Co-Authors: Jaspal Subhlok, K. Kennedy
    Abstract:

    We present a new method to determine whether a convex region contains any integer points. The method is designed for Array Subscript analysis in parallel programs. The general problem is whether a system of linear equalities and inequalities has an integer solution. A set of known techniques is used to transform the problem to that of finding whether a convex region contains any integer points. The main result of the paper is a set of new search procedures that identify an integer solution in a convex region, or prove that no integer solutions exist. They are based on the geometrical properties of convex regions that are not empty, but also do not contain any integer points. The results contribute to exact and efficient dependence and synchronization analysis of parallel programs. >

Tsung-chuan Huang - One of the best experts on this subject based on the ideXlab platform.

  • The local memory access sequence of multiple induction variables on distributed memory machines
    Computers & Electrical Engineering, 2004
    Co-Authors: Tsung-chuan Huang, Liang-cheng Shiu, Hwa-jyh Jean
    Abstract:

    Abstract Generating the local memory access sequence is an important issue while compiling a data-parallel language into an SPMD code. There are many researches dealing with this issue for cyclic(k) distribution in simple Subscripts. But the problem becomes highly complicated when the Array references are with complex Subscripts. One of the complex Array reference functions is Array Subscript containing multiple induction variables (MIV Subscripts). MIV is an affine combination of two or more nested loop indices in a single dimension. In this paper, we develop a general method in O(k) time to evaluate the start element for a given global start element. We compute the course distance first, and then traverse the FSM until the start element is found. In our method, the FSM table constructed in the one-level algorithm [J. Parallel Distr. Comput. 26(1) (1995) 72] can be used directly, but in the method of Ramanujam et al. [Languages and Compilers for Parallel Computing, vol. 1366. Springer-Verlag, 1998, p. 49] the l , r vectors of the processor must be evaluated for each global start element and the time-expensive operations like division and mod are required to check the space boundary of processors. Experimental results have revealed our method is more efficient than theirs.

  • Data dependence analysis for Array references
    Journal of Systems and Software, 2000
    Co-Authors: Tsung-chuan Huang, Cheng-ming Yang
    Abstract:

    Abstract Data dependence analysis is essential in order to determine whether a loop can be vectorized or parallelized. It is used to investigate whether two memory references in a loop are in the same location. In this paper we present a new scheme of exact data dependence analysis for Array Subscript analysis in parallel programs, called interval reduction (IR) test. This method reduces the solution interval of each constraint variable in the dependence equation by repeated projection. Once the effective solution interval of any variable shrinks to empty, this linear diophantine equation has no integer solution and the memory accesses subject to this constraint are then independent. Otherwise, all the integer solutions can be found, and thus the dependence distance can be computed as well. Experimental results are also presented to show its effectiveness compared to the Power test and the Omega test.