Toward an Energy Efficient Language and Compiler for (Partially) Reversible Algorithms

We introduce a new programming language for expressing reversibility, Energy-Efficient Language (Eel), geared toward algorithm design and implementation. Eel is the first language to take advantage of a partially reversible computation model, where programs can be composed of both reversible and irreversible operations. In this model, irreversible operations cost energy for every bit of information created or destroyed. To handle programs of varying degrees of reversibility, Eel supports a log stack to automatically trade energy costs for space costs, and introduces many powerful control logic operators including protected conditional, general conditional, protected loops, and general loops. In this paper, we present the design and compiler for the three language levels of Eel along with an interpreter to simulate and annotate incurred energy costs of a program.Comment: 17 pages, 0 additional figures, pre-print to be published in The 8th Conference on Reversible Computing (RC2016

Tabled CLP for Reasoning Over Stream Data

The interest in reasoning over stream data is growing as quickly as the amount of data generated. Our intention is to change the way stream data is analyzed. This is an important problem because we constantly have new sensors collecting information, new events from electronic devices and/or from customers and we want to reason about this information. For example, information about traffic jams and costumer order could be used to define a deliverer route. When there is a new order or a new traffic jam, we usually restart from scratch in order to recompute the route. However, if we have several deliveries and we analyze the information from thousands of sensors, we would like to reduce the computation requirements, e.g. reusing results from the previous computation. Nowadays, most of the applications that analyze stream data are specialized for specific problems (using complex algorithms and heuristics) and combine a computation language with a query language. As a result, when the problems become more complex (in e.g. reasoning requirements), in order to modify the application complex and error prone coding is required. We propose a framework based on a high-level language rooted in logic and constraints that will be able to provide customized services to different problems. The framework will discard wrong solutions in early stages and will reuse previous results that are still consistent with the current data set. The use of a constraint logic programming language will make it easier to translate the problem requirements into the code and will minimize the amount of re-engineering needed to comply with the requirements when they change