Arithmetic Branching Programs with Memory

We extend the well known characterization of VPws as the class of polynomials computed by polynomial size arithmetic branching programs to other complexity classes. In order to do so we add additional memory to the computation of branching programs to make them more expressive. We show that allowing different types of memory in branching programs increases the computational power even for constant width programs. In particular, this leads to very natural and robust characterizations of VP and VNP by branching programs with memory. 1

BEEBS: Open Benchmarks for Energy Measurements on Embedded Platforms

This paper presents and justifies an open benchmark suite named BEEBS, targeted at evaluating the energy consumption of embedded processors. We explore the possible sources of energy consumption, then select individual benchmarks from contemporary suites to cover these areas. Version one of BEEBS is presented here and contains 10 benchmarks that cover a wide range of typical embedded applications. The benchmark suite is portable across diverse architectures and is freely available. The benchmark suite is extensively evaluated, and the properties of its constituent programs are analysed. Using real hardware platforms we show case examples which illustrate the difference in power dissipation between three processor architectures and their related ISAs. We observe significant differences in the average instruction dissipation between the architectures of 4.4x, specifically 170uW/MHz (ARM Cortex-M0), 65uW/MHz (Adapteva Epiphany) and 88uW/MHz (XMOS XS1-L1)

Optimization guide for programs compiled under IBM FORTRAN H (OPT=2)

Guidelines are given to provide the programmer with various techniques for optimizing programs when the FORTRAN IV H compiler is used with OPT=2. Subroutines and programs are described in the appendices along with a timing summary of all the examples given in the manual

Certifying cost annotations in compilers

We discuss the problem of building a compiler which can lift in a provably correct way pieces of information on the execution cost of the object code to cost annotations on the source code. To this end, we need a clear and flexible picture of: (i) the meaning of cost annotations, (ii) the method to prove them sound and precise, and (iii) the way such proofs can be composed. We propose a so-called labelling approach to these three questions. As a first step, we examine its application to a toy compiler. This formal study suggests that the labelling approach has good compositionality and scalability properties. In order to provide further evidence for this claim, we report our successful experience in implementing and testing the labelling approach on top of a prototype compiler written in OCAML for (a large fragment of) the C language

Techniques for the realization of ultrareliable spaceborne computers Interim scientific report

Error-free ultrareliable spaceborne computer

Hybrid Information Flow Analysis for Programs with Arrays

Information flow analysis checks whether certain pieces of (confidential) data may affect the results of computations in unwanted ways and thus leak information. Dynamic information flow analysis adds instrumentation code to the target software to track flows at run time and raise alarms if a flow policy is violated; hybrid analyses combine this with preliminary static analysis. Using a subset of C as the target language, we extend previous work on hybrid information flow analysis that handled pointers to scalars. Our extended formulation handles arrays, pointers to array elements, and pointer arithmetic. Information flow through arrays of pointers is tracked precisely while arrays of non-pointer types are summarized efficiently. A prototype of our approach is implemented using the Frama-C program analysis and transformation framework. Work on a full machine-checked proof of the correctness of our approach using Isabelle/HOL is well underway; we present the existing parts and sketch the rest of the correctness argument.Comment: In Proceedings VPT 2016, arXiv:1607.0183