Luisa D'Amore

Prof. Dr. Luisa D'Amore

University of Naples Federico II, Naples, Campania, Italy
orcid

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 1999 in ACM Transactions on Mathematical Software
Verified
Journal Article
Open access
Luisa D'AmoreLuisa D'Amore
Luisa D'Amore
GLGuiliano Laccetti
Guiliano Laccetti
AMAlmerico Murli
Almerico Murli
Our method is based on the numerical evaluation of the integral which occurs in the Riemann Inversion formula. The trapezoidal rule approximation to this integral reduces to a Fourier series. We analyze the corresponding discretization error and demonstrate how this expression can be used in the development of an automatic routine , one in which the user needs to specify only the required accuracy.

8 February 2014 in Journal of Scientific Computing
Verified
Journal Article
Closed access
PDF file
Luisa D'AmoreLuisa D'Amore
Luisa D'Amore
RARossella Arcucci
Rossella Arcucci
LCLUISA CARRACCIUOLO
LUISA CARRACCIUOLO
AMAlmerico Murli
Almerico Murli

1 January 2007 in Journal of Computational and Applied Mathematics
Verified
Journal Article
Closed access
Salvatore CuomoSalvatore Cuomo
Salvatore Cuomo
Luisa D'AmoreLuisa D'Amore
Luisa D'Amore
AMA. Murli
A. Murli
MRM. Rizzardi
M. Rizzardi

27 March 2014 in International Journal of Computer Mathematics
Verified
Journal Article
Closed access
Luisa D'AmoreLuisa D'Amore
Luisa D'Amore
Giuliano LaccettiGiuliano Laccetti
Giuliano Laccetti
Diego RomanoDiego Romano
Diego Romano
GSG. Scotti
G. Scotti
AMA. Murli
A. Murli
Modern graphics processing units (GPUs) have been at the leading edge of increasing parallelism over the last 10 years. This fact has encouraged the use of GPUs in a broader range of applications, where developers are required to lever age this technology with new programming models which ease the task of writing programs to run efficiently on GPUs. In this paper, we discuss the main guidelines to assist the developer when porting sequential scientific code on modern GPUs. These guidelines were carried out by porting the L-BFGS, the (Limited memory-) BFGS algorithm for large scale optimization, available as Harwell routine VA15. The specific interest in the L-BFGS algorithm arises from the fact that this is the computational module with the longest running time of a Oceanographic Data Assimilation application software, on which some of the authors are working.


11 October 2016 in International Journal of Parallel Programming
Verified
Journal Article
Closed access
PDF file
RARossella Arcucci
Rossella Arcucci
Luisa D'AmoreLuisa D'Amore
Luisa D'Amore
LCLUISA CARRACCIUOLO
LUISA CARRACCIUOLO
GSGiuseppe Scotti
Giuseppe Scotti
Giuliano LaccettiGiuliano Laccetti
Giuliano Laccetti