Inferring Energy Bounds via Static Program Analysis and Evolutionary Modeling of Basic Blocks

The ever increasing number and complexity of energy-bound devices (such as the ones used in Internet of Things applications, smart phones, and mission critical systems) pose an important challenge on techniques to optimize their energy consumption and to verify that they will perform their function within the available energy budget. In this work we address this challenge from the software point of view and propose a novel parametric approach to estimating tight bounds on the energy consumed by program executions that are practical for their application to energy verification and optimization. Our approach divides a program into basic (branchless) blocks and estimates the maximal and minimal energy consumption for each block using an evolutionary algorithm. Then it combines the obtained values according to the program control flow, using static analysis, to infer functions that give both upper and lower bounds on the energy consumption of the whole program and its procedures as functions on input data sizes. We have tested our approach on (C-like) embedded programs running on the XMOS hardware platform. However, our method is general enough to be applied to other microprocessor architectures and programming languages. The bounds obtained by our prototype implementation can be tight while remaining on the safe side of budgets in practice, as shown by our experimental evaluation.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854). Improved version of the one presented at the HIP3ES 2016 workshop (v1): more experimental results (added benchmark to Table 1, added figure for new benchmark, added Table 3), improved Fig. 1, added Fig.

CFA2: a Context-Free Approach to Control-Flow Analysis

In a functional language, the dominant control-flow mechanism is function call and return. Most higher-order flow analyses, including k-CFA, do not handle call and return well: they remember only a bounded number of pending calls because they approximate programs with control-flow graphs. Call/return mismatch introduces precision-degrading spurious control-flow paths and increases the analysis time. We describe CFA2, the first flow analysis with precise call/return matching in the presence of higher-order functions and tail calls. We formulate CFA2 as an abstract interpretation of programs in continuation-passing style and describe a sound and complete summarization algorithm for our abstract semantics. A preliminary evaluation shows that CFA2 gives more accurate data-flow information than 0CFA and 1CFA.Comment: LMCS 7 (2:3) 201

QD-Janus: A Sequential Implementation of Janus in Prolog

Janus is a language designed for distributed constraint programming. This paper describes QDJanus, a sequential implementation of Janus in Prolog. The compiler uses a number of novel analyses and optimizations to improve the performance of the system. The choice of Prolog as the target language for a compiler, while unusual, is motivated by the following: (i) the semantic gap between Janus and Prolog is much smaller than that between Janus and, say, C or machine language---this simplifies the compilation process significantly, and makes it possible to develop a system with reasonable performance fairly quickly; (ii) recent progress in Prolog implementation techniques, and the development of Prolog systems whose speeds are comparable to those of imperative languages, indicates that the translation to Prolog need not entail a significant performance loss compared to native code compilers; and (iii) compilation to Prolog can benefit immediately from a significant body of work on, and impl..