Gianfranco Bilardi

Bio: Gianfranco Bilardi is an academic researcher from University of Padua. The author has contributed to research in topics: Upper and lower bounds & Model of computation. The author has an hindex of 23, co-authored 96 publications receiving 1760 citations. Previous affiliations of Gianfranco Bilardi include University of Illinois at Urbana–Champaign & IBM.

Adaptive Bitonic Sorting: An Optimal Parallel Algorithm for Shared Memory Machines

Abstract: We propose a parallel algorithm, called adaptive bitonic sorting, which runs on a PRAC, a shared-memory multiprocessor where fetch and store conflicts are disallowed. On a $P$ processors PRAC, our algorithm achieves optimal performance $TP = O(N \log N)$, for any computation time $T$ in the range $\Omega (\log^{2} N) \leq T \leq O(N \log N)$. Adaptive bitonic sorting has also a small constant factor, since it performs less than $2N \log N$ comparisons, and only a handful of operations per comparison.

BSP vs LogP

Abstract: A quantitative comparison of the BSP and LogP models for parallel computation is developed. Very efficient cross simulations between the two models are derived, showing their substantial equivalence for algorithmic design guided by asymptotic analysis. It is also shown that the two models can be implemented with similar performance on most point-to-point networks. In conclusion, within the limits of our analysis that is mainly of asymptotic nature, BSP and LogP can be viewed as closely related variants within the bandwidth-latency framework for modeling parallel computation. BSP seems somewhat preferable due to greater simplicity and portability, and slightly greater power.

Spectral Analysis of Functions of Markov Chains with Applications

Abstract: This paper deals with the spectral analysis of digital processes obtained through memoryless functions of stationary Markov chains. Under the assumption that the Markov chain is ergodic, not necessarily acyclic, closed form formulas are derived for both the discrete part (spectral lines) and the continuous part of the spectral density. The results are applied at the output of a finite state sequential machine driven by a stationary Markov chain, which represents a general model of several situations of engineering interest. Finally, the theory is used to evaluate the spectrum of encoded and modulated digital signals.

Phd by thesis

Abstract: Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

An introduction to parallel algorithms

Abstract: Written by an authority in the field, this book provides an introduction to the design and analysis of parallel algorithms. The emphasis is on the application of the PRAM (parallel random access machine) model of parallel computation, with all its variants, to algorithm analysis. Special attention is given to the selection of relevant data structures and to algorithm design principles that have proved to be useful. Features *Uses PRAM (parallel random access machine) as the model for parallel computation. *Covers all essential classes of parallel algorithms. *Rich exercise sets. *Written by a highly respected author within the field. 0201548569B04062001

The Java memory model

Abstract: This paper describes the new Java memory model, which has been revised as part of Java 5.0. The model specifies the legal behaviors for a multithreaded program; it defines the semantics of multithreaded Java programs and partially determines legal implementations of Java virtual machines and compilers.The new Java model provides a simple interface for correctly synchronized programs -- it guarantees sequential consistency to data-race-free programs. Its novel contribution is requiring that the behavior of incorrectly synchronized programs be bounded by a well defined notion of causality. The causality requirement is strong enough to respect the safety and security properties of Java and weak enough to allow standard compiler and hardware optimizations. To our knowledge, other models are either too weak because they do not provide for sufficient safety/security, or are too strong because they rely on a strong notion of data and control dependences that precludes some standard compiler transformations.Although the majority of what is currently done in compilers is legal, the new model introduces significant differences, and clearly defines the boundaries of legal transformations. For example, the commonly accepted definition for control dependence is incorrect for Java, and transformations based on it may be invalid.In addition to providing the official memory model for Java, we believe the model described here could prove to be a useful basis for other programming languages that currently lack well-defined models, such as C++ and C#.

Introduction to Parallel Computing

Abstract: The constantly increasing demand for more computing power can seem impossible to keep up with. However, multicore processors capable of performing computations in parallel allow computers to tackle ever larger problems in a wide variety of applications. This book provides a comprehensive introduction to parallel computing, discussing theoretical issues such as the fundamentals of concurrent processes, models of parallel and distributed computing, and metrics for evaluating and comparing parallel algorithms, as well as practical issues, including methods of designing and implementing shared- and distributed-memory programs, and standards for parallel program implementation, in particular MPI and OpenMP interfaces. Each chapter presents the basics in one place followed by advanced topics, allowing novices and experienced practitioners to quickly find what they need. A glossary and more than 80 exercises with selected solutions aid comprehension. The book is recommended as a text for advanced undergraduate or graduate students and as a reference for practitioners.