Survey on Combinatorial Register Allocation and Instruction Scheduling

Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization

Requirements and Tools for Variability Management

Explicit and software-supported Business Process Management has become the core infrastructure of any medium and large organization that has a need to be efficient and effective. The number of processes of a single organization can be very high, furthermore, they might be very similar, be in need of momentary change, or evolve frequently. If the ad-hoc adaptation and customization of processes is currently the dominant way, it clearly is not the best. In fact, providing tools for supporting the explicit management of variation in processes (due to customization or evolution needs) has a profound impact on the overall life-cycle of processes in organizations. Additionally, with the increasing adoption of Service-Oriented Architectures, the infrastructure to support automatic reconfiguration and adaptation of business process is solid. In this paper, after defining variability in business process management, we consider the requirements for explicit variation handling for (service based) business process systems. eGovernment serves as an illustrative example of reuse. In this case study, all local municipalities need to implement the same general legal process while adapting it to the local business practices and IT infrastructure needs. Finally, an evaluation of existing tools for explicit variability management is provided with respect to the requirements identified.

The CIAO multiparadigm compiler and system: A progress report

Abstract is not available

Anytime Computation of Cautious Consequences in Answer Set Programming

Query answering in Answer Set Programming (ASP) is usually solved by computing (a subset of) the cautious consequences of a logic program. This task is computationally very hard, and there are programs for which computing cautious consequences is not viable in reasonable time. However, current ASP solvers produce the (whole) set of cautious consequences only at the end of their computation. This paper reports on strategies for computing cautious consequences, also introducing anytime algorithms able to produce sound answers during the computation.Comment: To appear in Theory and Practice of Logic Programmin

An improved connectionist activation function for energy minimization

Symmetric networks that are based on energy minimization, such as Boltzmann machines or Hopfield nets, are used extensively for optimization, constraint satisfaction, and approximation of NP-hard problems. Nevertheless, finding a global minimum for the energy function is not guaranteed, and even a local minimum may take an exponential number of steps. We propose an improvement to the standard activation function used for such networks. The improved algorithm guarantees that a global minimum is found in linear time for tree-like subnetworks. The algorithm is uniform and does not assume that the network is a tree. It performs no worse than the standard algorithms for any network topology. In the case where there are trees growing from a cyclic subnetwork, the new algorithm performs better than the standard algorithms by avoiding local minima along the trees and by optimizing the free energy of these trees in linear time. The algorithm is self-stabilizing for trees (cycle-free undirected graphs) and remains correct under various scheduling demons. However, no uniform protocol exists to optimize trees under a pure distributed demon and no such protocol exists for cyclic networks under central demon