R. Gupta, D. A. Berson, and J. Z. Fang. Path pro le guided partial redundancy elimination using speculation. In Proceedings of the 1998. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Speculative Alias Analysis for Executable Code - Fernández, Espasa (2002) (Correct)
....at a time. Therefore, the compiler does not have the opportunity to optimize the full program as a whole, even when performing sophisticated inter procedural transformations. A second reason for the interest in binary optimization has been the emergence of pro le directed compilation techniques [26, 9, 12, 20]. The compiler can use to great advantage the pro ling information. However, the same problem of separate compilation plagues the use of pro le feedback: large projects will be forced to re build every le to take advantage of the pro ling information. Furthermore, the pro le guided ....
....by providing more reliable information in the common case. However, the speculative nature of our schemes causes the analysis results to be not always correct. This means that any optimization performed using this speculative analysis will be speculative as well. Speculative optimizations [21, 17, 22, 20, 27] have been widely used in the compiler world for reducing the overall execution time of programs. The key idea behind speculation is breaking the original program sequence by executing a (possibly unsafe) better reordering of instructions, corresponding to the most likely execution paths. Since ....
[Article contains additional citation context not shown here]
R. Gupta, D. A. Berson, and J. Z. Fang. Path pro le guided partial redundancy elimination using speculation. In Proceedings of the 1998.
Profile Guided Compiler Optimizations - Gupta, Mehofer, Zhang (2002) (1 citation) Self-citation (Gupta) (Correct)
....Second it is assumed that the entire control ow trace is available so that the execution frequencies of each of these interesting paths can be determined. While it is possible to compute path based data ow information and maintain complete control ow traces using the techniques described in [20] and [27; 43] respectively, for practical reasons it may be desirable to explore less expensive alternatives. In this section we present a detailed cost bene t algorithm which uses probabilistic data ow analysis (PDFA) guided by two edge pro les. Therefore this algorithm neither requires the ....
R. Gupta, D. Berson, and J.Z. Fang, \Path Prole Guided Partial Redundancy Elimination Using Speculation," IEEE International Conference on Computer Languages (ICCL), pages 230-239, Chicago, Illinois, May 1998.
Timestamped Whole Program Path Representation and its.. - Zhang, Gupta (2001) (6 citations) Self-citation (Gupta) (Correct)
....traces in a form that is suitable for analysis which is performed from the perspective of basic blocks. In particular, we consider a class of applications that perform data ow analysis on the program and utilize the WPP information to gather data ow facts, including frequencies of data ow facts [20, 7, 13, 14, 15], which can be observed to hold during the program execution represented by the WPP. Applications that fall in this category include identi cation of hot data ow facts for pro leguided code optimizers (static and dynamic) as well as debugging aids (dynamic slicing and currency determination ....
....which is aimed at answering data ow queries with respect to a given WPP. Examples of such queries are: does a data ow fact hold or how often does a data ow fact hold at a program point with respect to a given WPP. Such analysis is useful for pro le guided compile time optimization of programs [2, 7, 3, 11, 23, 13, 14, 15], dynamic optimization of programs [3, 6] here the pro le represents a partial execution history of the program which is used to optimize the remainder of the program s execution) and debugging of programs [10, 17, 1] The analysis we present focuses on gathering hot data ow facts that hold ....
[Article contains additional citation context not shown here]
R. Gupta, D. Berson, and J.Z. Fang, \Path Prole Guided Partial Redundancy Elimination Using Speculation," IEEE International Conference on Computer Languages, pages 230-239, Chicago, Illinois, May 1998.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC