Practical Aspects of Declarative Languages: 18th by Marco Gavanelli, John Reppy

By Marco Gavanelli, John Reppy

This publication constitutes the refereed lawsuits of the 18th foreign Symposium on useful points of Declarative Languages, PADL 2016, held in St. Petersburg, FL, united states, in January 2016.

The eleven revised papers provided have been rigorously reviewed and chosen from 17 preliminary submissions for inclusion within the e-book. PADL is a discussion board for researchers and practitioners to offer unique paintings emphasizing novel functions and implementation concepts for all different types of declarative recommendations, together with, useful, good judgment, constraints, etc.

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Extra resources for Practical Aspects of Declarative Languages: 18th International Symposium, PADL 2016, St. Petersburg, FL, USA, January 18-19, 2016. Proceedings

Example text

During this process, there are no memory transfers between the CPU and the GPU, with the exception of: (1) flow control flags, such as the “exit” flag, used to communicate whether the computation is terminated, and (2) the transfer of the computed answer set from the GPU to the CPU. The overall structure of the CUD@ASP-computation procedure (depicted in Fig. 3) is the conventional structure of an ASP solver. The differences lay in the selection heuristic (ASP computation) and in the parallelization of all the support functions involved.

For each analyzed conflict, a new nogood is learned and added to Δ. This procedure takes also care of backtracking/backjumping, through the use of a specific grid of kernels (Backjumping). , the values of A and LEVEL) are updated accordingly. Notice that the prototype can learn from all the conflicts detected by the same run of NoGoodCheckAndPropagate. The number of conflicts to process can be specified through a command-line option. In case of multiple learned nogoods involving different “target” decision levels, the lowest level is selected.

This process allows classical backjumping in the search tree generated by the execution of CUD@ASP-computation [31]. This part of the solver is the one that is less suitable to SIMT parallelism, due to the fact that a (sequential) sequence of resolution steps must be encoded. This procedure ends with the identification of a unique implication point (UIP [25]) that determines the lower decision level/literal among those causing the detected conflicts. As default behavior, the solver selects one of the (possibly multiple) conflicts generated by NoGoodCheckAndPropagate.

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