M. A. Ertl and A. Krall. Optimal instruction scheduling using constraint logic programming. In Programming Language Implementation and Logic Programming (PLILP), 1991. Home/Search Document Not in Database Summary Related Articles Check |
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Fast Optimal Instruction Scheduling for Single-issue.. - van Beek, Wilken (2001) (5 citations) (Correct)
....open problem whether there exists a polynomial time algorithm for any fixed d 2. Previous work has also developed optimal algorithms for the general problem when d 2. The approaches taken include dynamic programming [10] integer linear programming [1, 5, 14, 21] and constraint programming [7]. However, with the exception of [21] to which we do a detailed comparison later in the paper) these previous approaches have only been evaluated on a few problems with the sizes of the problems ranging between 10 and 40 instructions. Further, their experimental results suggest that none of them ....
....later in the paper) these previous approaches have only been evaluated on a few problems with the sizes of the problems ranging between 10 and 40 instructions. Further, their experimental results suggest that none of them would scale up beyond problems of this size. For example, Ertl and Krall [7] present a constraint programming approach which solves the problem optimally. Their CSP model has latency constraints and an all different constraint. As our experiments confirm (see Table 3 and the discussion at the end of Section 5) such a model does not scale beyond 50 instructions. However, ....
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M. A. Ertl and A. Krall. Optimal instruction scheduling using constraint logic programming. In Programming Language Implementation and Logic Programming (PLILP), 1991.
Finite Domain Constraints in Industrial Development 1.1 Background - Gr Ou Nd (Correct)
....these two functions produce suboptimal code. This is because the lack of coordination between register allocation and instruction scheduling results in poor use of the register set. The problem can be stated easily and declaratively as an optimization problem over finite domain constraints [9]. Processor specific limits, e.g. PC relative offsets that constrain the mobility of instructions, should be easy to integrate into the same framework. Other objective functions, such as minimal code size as opposed to optimal execution time, should be equally easy to integrate. 1.3 Approach ....
M. A. Ertl. Optimal Instruction Scheduling using Constraint Logic Programming. In Programming Languages Implementation and Logic Programming (PLILP), pp. 75-86, 1991. Springer LNCS 528.
Over-Constrained Systems in CLP and CSP - Jampel (1996) (2 citations) (Correct)
....successful practical applications solving difficult and commercially important real world problems. Examples include scheduling for factories and for computer instruction sets; financial applications such as options and portfolio analysis; and modelling water usage, DNA, and electrical circuits [3, 10, 23, 24, 38, 39, 64, 72, 78, 79, 86]. Many problems which previously appeared local to a particular application domain, and which were therefore solved in an ad hoc manner, can now be seen as instances of constraint problems. For example, AI applications as disparate as machine vision and belief revision can now be considered in ....
M. Anton Ertl and Andreas Krall. Optimal Instruction Scheduling Using Constraint Logic Programming. In J. Maluszy'nski and M. Wirsing, editors, PLILP'91: Proceedings 3rd International Symposium on Programming Language Implementation and Logic Programming, LNCS 528, Passau, Germany, August 1991. Springer.
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