Elevating commodity storage with the SALSA host translation layer

To satisfy increasing storage demands in both capacity and performance, industry has turned to multiple storage technologies, including Flash SSDs and SMR disks. These devices employ a translation layer that conceals the idiosyncrasies of their mediums and enables random access. Device translation layers are, however, inherently constrained: resources on the drive are scarce, they cannot be adapted to application requirements, and lack visibility across multiple devices. As a result, performance and durability of many storage devices is severely degraded. In this paper, we present SALSA: a translation layer that executes on the host and allows unmodified applications to better utilize commodity storage. SALSA supports a wide range of single- and multi-device optimizations and, because is implemented in software, can adapt to specific workloads. We describe SALSA's design, and demonstrate its significant benefits using microbenchmarks and case studies based on three applications: MySQL, the Swift object store, and a video server.Comment: Presented at 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS

Fast counting with tensor networks

We introduce tensor network contraction algorithms for counting satisfying assignments of constraint satisfaction problems (#CSPs). We represent each arbitrary #CSP formula as a tensor network, whose full contraction yields the number of satisfying assignments of that formula, and use graph theoretical methods to determine favorable orders of contraction. We employ our heuristics for the solution of #P-hard counting boolean satisfiability (#SAT) problems, namely monotone #1-in-3SAT and #Cubic-Vertex-Cover, and find that they outperform state-of-the-art solvers by a significant margin.Comment: v2: added results for monotone #1-in-3SAT; published versio

Bilingualism on the Internet: The Teaching/Learning of Greek as a Second Language in Higher Education.

In the last few years we have observed a rapid increase in Computer Assisted Language Learning (CALL). These applications include software that aims at the teaching of first, second and foreign languages, applications on the Internet or both. The historical retrospection of CALL shows its development, beginning from its first applications in the 1960s up to this date (Warschauer and Healy, 1998). Today more possibilities exist in respect to new technologies but also theories of language learning and pedagogies that go beyond traditional orientations. This paper proposes ways in which Information and Communication Technologies (ICT) can be used to enhance the teaching/learning of the Greek language in departments of Greek studies in higher education outside Greece. It describes an Internet based application for the teaching/learning of Greek as a second language, “Λόγου χάρη” ('Logou hari') (Kourtis-Kazoullis, 2005), which is based on the creative analysis and production of literary texts, as well as collaboration between university classes

A Stability Approach to Mean-Variance Optimization

I jointly treat two critical issues in the application of mean-variance portfolios, that is, estimation risk and portfolio instability. I find that theory-based portfolio strategies, which are known to outperform naive diversification (inline image) in the absence of transaction costs, heavily underperform it under transaction costs. This is because they are highly unstable over time. I propose a generic method to stabilize any given portfolio strategy while maintaining or improving its efficiency. My empirical analysis confirms that the new method leads to stable and efficient portfolios that offer equal or lower turnover than inline image and larger Sharpe ratio, even under high transaction costs