Certain answers are a widely accepted semantics of query answering over incomplete databases. Since their computation is a coNP-hard problem, recent research has focused on developing evaluation algorithms with correctness guarantees, that is, techniques computing a sound but possibly incomplete set of certain answers. In this paper, we show how novel evaluation algorithms with correctness guar...

Modern processors contain large last level caches (LLCs) that consume substantial energy and area yet are imperative for high performance. Cache designs have improved dramatically by considering reference locality. Data values are also a source of optimization. Compression and deduplication exploit data values to use cache storage more efficiently resulting in smaller caches without sacrificing...

Iwano, et al. [8] have given an approximate binary search algorithm for computing max mean cuts. This paper gives a short proof of the correctness of their algorithm. It also shows how their algorithm can be dualized to an approximate binary search algorithm for computing min mean cycles that is as fast as but simpler than Orlin and Ahuja’s algorithm [12].

With the power constraints of the dark silicon era looming, architectural changes to improve energy efficiency are critical. Disciplined approximate computing, in which unreliable hardware components are safely used in error-tolerant software, is a promising approach. We discuss programming models, architectures, and accelerators for approximate computing.

Stochastic circuits (SCs) offer tremendous area and power-consumption benefits at the expense of computational inaccuracies. Managing accuracy is a central problem in SC design and has no counterpart in conventional circuit synthesis. It raises a basic question: how to build a systematic design flow for stochastic circuits? We present, for the first time, a systematic design approach to control...

We present techniques for obtaining acceptable unsynchronized parallel computations. Even though these techniques may generate interactions (such as data races) that the current rigid value system condemns as incorrect, they are engineered to 1) preserve key data structure consistency constraints while 2) producing a result that is accurate enough, often enough. And because they contain no sync...

It is normal to expect the processor to produce a correct result. But it may be the case that a software application does not need ”strict” correctness, but rather limited correctness. The goal of this project is to search for potential definition of ”non-strict” correctness, as well as investigate the improvements in performance and power consumption that can be achieved in this new model. Thi...

The Internet of Things significantly increases the amount of data generated, straining the processing capability of current computing systems. Approximate computing is a promising solution to accelerate computation by trading off energy and accuracy. In this paper, we propose a resistive content addressable memory (CAM) accelerator, called RCA, which exploits data locality to have an approximat...

Editor’s notes: Approximate computing is almost always associated with results showing a tradeoff between accuracy and computational efficiency. In this article, however, approximate finds application in hardware trustworthiness encouraging results. —Mario Barbareschi, University of Naples Federico II

Approximate computing exposes opportunities to increase the efficiency of computer systems by trading-off accuracy for energy savings. These optimization opportunities can be found in many emerging classes of applications which exhibit a degree of tolerance to imprecision. Taking full advantage of approximation requires a programming model that provides control to the programmer over what porti...