DataSpread: Unifying Databases and Spreadsheets.

Spreadsheet software is often the tool of choice for ad-hoc tabular data management, processing, and visualization, especially on tiny data sets. On the other hand, relational database systems offer significant power, expressivity, and efficiency over spreadsheet software for data management, while lacking in the ease of use and ad-hoc analysis capabilities. We demonstrate DataSpread, a data exploration tool that holistically unifies databases and spreadsheets. It continues to offer a Microsoft Excel-based spreadsheet front-end, while in parallel managing all the data in a back-end database, specifically, PostgreSQL. DataSpread retains all the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the advantages of traditional relational databases, such as scalability and the ability to use arbitrary SQL to import, filter, or join external or internal tables and have the results appear in the spreadsheet. DataSpread needs to reason about and reconcile differences in the notions of schema, addressing of cells and tuples, and the current pane (which exists in spreadsheets but not in traditional databases), and support data modifications at both the front-end and the back-end. Our demonstration will center on our first and early prototype of the DataSpread, and will give the attendees a sense for the enormous data exploration capabilities offered by unifying spreadsheets and databases

The Simulation Model Partitioning Problem: an Adaptive Solution Based on Self-Clustering (Extended Version)

This paper is about partitioning in parallel and distributed simulation. That means decomposing the simulation model into a numberof components and to properly allocate them on the execution units. An adaptive solution based on self-clustering, that considers both communication reduction and computational load-balancing, is proposed. The implementation of the proposed mechanism is tested using a simulation model that is challenging both in terms of structure and dynamicity. Various configurations of the simulation model and the execution environment have been considered. The obtained performance results are analyzed using a reference cost model. The results demonstrate that the proposed approach is promising and that it can reduce the simulation execution time in both parallel and distributed architectures

Implementing a protected zone in a reconfigurable processor for isolated execution of cryptographic algorithms

We design and realize a protected zone inside a reconfigurable and extensible embedded RISC processor for isolated execution of cryptographic algorithms. The protected zone is a collection of processor subsystems such as functional units optimized for high-speed execution of integer operations, a small amount of local memory, and general and special-purpose registers. We outline the principles for secure software implementation of cryptographic algorithms in a processor equipped with the protected zone. We also demonstrate the efficiency and effectiveness of the protected zone by implementing major cryptographic algorithms, namely RSA, elliptic curve cryptography, and AES in the protected zone. In terms of time efficiency, software implementations of these three cryptographic algorithms outperform equivalent software implementations on similar processors reported in the literature. The protected zone is designed in such a modular fashion that it can easily be integrated into any RISC processor; its area overhead is considerably moderate in the sense that it can be used in vast majority of embedded processors. The protected zone can also provide the necessary support to implement TPM functionality within the boundary of a processor