
Pasqua D'AmbraNational Research Council of Italy, Rome · Institute for Applied Computing "Mauro Picone", Naples branch
Pasqua D'Ambra
Ph.D.
About
90
Publications
8,193
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Introduction
Pasqua D'Ambra is a research director with the Institute for Applied Computing “Mauro Picone", Naples branch, National Research Council of Italy.
Additional affiliations
January 1990 - December 1994
December 1994 - June 2015
Publications
Publications (90)
Linear solvers are key components in any software platform for scientific and engineering computing. The solution of large and sparse linear systems lies at the core of physics-driven numerical simulations relying on partial differential equations (PDEs) and often represents a significant bottleneck in datadriven procedures, such as scientific mach...
In this paper, we propose some Chebyshev polynomials of the 1st-kind which produce optimal bound for a polynomial dependent constant involved in the AMG $V$-cycle error bound and do not require information about the spectrum of matrices. We formulate a variant of a minimax problem already proposed in [J. Lottes, Optimal polynomial smoothers for mul...
In this chapter, we describe the Parallel Sparse Computation Toolkit (PSCToolkit), a suite of libraries for solving large-scale linear algebra problems in an HPC environment. In particular, we focus on the tools provided for the solution of symmetric and positive-definite linear systems using up to 8192 GPUs on the EuroHPC-JU Leonardo supercomputer...
In this paper, we describe an upgrade of the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency and scalability in the computation of the pressure field at each time step of the numerical procedure for solving a Large Eddy Simulation formulation of the incompressible Navier–Stokes equations. We developed...
In this paper, we discuss the convergence of an Algebraic MultiGrid (AMG) method for general symmetric positive-definite matrices. The method relies on an aggregation algorithm, named coarsening based on compatible weighted matching, which exploits the interplay between the principle of compatible relaxation and the maximum product matching in undi...
We present and release in open source format a sparse linear solver which efficiently exploits heterogeneous parallel computers. The solver can be easily integrated into scientific applications that need to solve large and sparse linear systems on modern parallel computers made of hybrid nodes hosting Nvidia Graphics Processing Unit (GPU) accelerat...
We consider here a cell‐centered finite difference approximation of the Richards equation in three dimensions, averaging for interface values the hydraulic conductivity , a highly nonlinear function, by arithmetic, upstream and harmonic means. The nonlinearities in the equation can lead to changes in soil conductivity over several orders of magnitu...
In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. We incorporate structural and attribute similarities between the ver-tices in an augmented graph by creating additional vertices and edges as proposed in [1, 2]. The augmented graph is then embedded in a Euclidean space associated to its Lapla-...
In this paper we propose a new approach to detect clusters in undirected graphs with attributed vertices. We incorporate structural and attribute similarities between the vertices in an augmented graph by creating additional vertices and edges as proposed in [1, 2]. The augmented graph is then embedded in a Euclidean space associated to its Laplaci...
This paper presents a new software framework for solving large and sparse linear systems on current hybrid architectures, from small servers to high-end supercomputers, embedding multi-core CPUs and Nvidia GPUs at the node level. The framework has a modular structure and is composed of three main components, which separate basic functionalities for...
In this paper, we describe some work aimed at upgrading the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency, and scalability in the computation of the pressure field at each time step of the numerical procedure for solving an LES formulation of the incompressible Navier-Stokes equations. We developed a...
In the near future, Exascale systems will need to bridge three technology gaps to achieve high performance while remaining under tight power constraints: energy efficiency and thermal control; extreme computation efficiency via HW acceleration and new arithmetic; methods and tools for seamless integration of reconfigurable accelerators in heterogen...
We consider here a cell-centered finite difference approximation of the Richards
equation in three dimensions, averaging for interface values the hydraulic conductivity, a highly nonlinear function, by arithmetic, upstream and harmonic
means. The nonlinearities in the equation can lead to changes in soil conductivity
over several orders of magnitud...
In this paper, we discuss a quality measure for an aggregation-based coarsening algorithm, named "coarsening based on compatible weighted matching", which relies on the interplay between the principle of compatible relaxation and the maximum product matching in weighted graphs. The measure we propose is based on a recent general convergence analysi...
To achieve high performance and high energy efficiency
on near-future exascale computing systems, three key
technology gaps needs to be bridged. These gaps include: energy
efficiency and thermal control; extreme computation efficiency
via HW acceleration and new arithmetics; methods and
tools for seamless integration of reconfigurable accelerators...
Linear solvers for large and sparse systems are a key element of scientific applications, and their efficient implementation is necessary to harness the computational power of current computers. Algebraic MultiGrid (AMG) preconditioners are a popular ingredient of such linear solvers; this is the motivation for the present work, where we examine so...
My invited seminar at the colloquium series within the EuroCC project at the National HPC Competence Center for Cyprus
Sparse solvers are one of the building blocks of any technology for reliable and high-performance scientific and engineering computing. In this paper we present a software package which implements an efficient multigrid sparse solver running on Graphics Processing Units. The package is a branch of a wider initiative of software development for spar...
Linear solvers for large and sparse systems are a key element of scientific applications, and their efficient implementation is necessary to harness the computational power of current computers. Algebraic Multigrid (AMG) Preconditioners are a popular ingredient of such linear solvers; this is the motivation for the present work where we examine som...
Current applications in Computational and Data Science often require the solution of large and sparse linear systems. The notion of "large" is qualitative and there is a clear tendency to increase it; currently, it is not unusual the need to solve systems with millions or even billions of unknowns. The methods of choice to efficiently solve the abo...
We
describe
main
issues
and
design
principles
of
an
efficient
implementation,
tailored
to
recent
genera
tions
of
Nvidia
Graphics
Processing
Units
(GPUs),
of
an
Algebraic
MultiGrid
(AMG)
preconditioner
previ
ously
proposed
by
one
of
the
authors
and
already
available
in
the
open-source
package
BootCMatch:
Boo...
Complex scientific and engineering models are very useful and very significant tools in the search for answers to many difficult questions which are important for the modern society. These models are often described mathematically bynon-linearsystemsofpartialdifferentialequations.Thediscretizationofthespatial derivativesinthesesystemsleads to large...
This paper proposes improving the solve time of a bootstrap algebraic multigrid (AMG) designed previously by the authors. This is achieved by incorporating the information, a set of algebraically smooth vectors, generated by the bootstrap algorithm, in a single hierarchy by using sufficiently large aggregates, and these aggregates are compositions...
Graph Laplacian is a popular tool for analyzing graphs, in particular in graph partitioning and clustering. Given a notion of similarity (via an adjacency matrix), graph clustering refers to identifying different groups such that vertices in the same group are more similar compared to vertices across different groups. Data clustering can be reformu...
Many scientific applications require the solution of large and sparse linear systems of equations using Krylov subspace methods; in this case, the choice of an effective preconditioner may be crucial for the convergence of the Krylov solver. Algebraic MultiGrid (AMG) methods are widely used as preconditioners, because of their optimal computational...
We describe main issues and design principles of an efficient implementation, tailored to recent generations of Nvidia Graphics Processing Units (GPUs), of an Algebraic MultiGrid (AMG) preconditioner previously proposed by one of the authors and already available in the open-source package BootCMatch: Bootstrap algebraic multigrid based on Compatib...
This article has two main objectives: one is to describe some extensions of an adaptive Algebraic Multigrid (AMG) method of the form previously proposed by the first and third authors, and a second one is to present a new software framework, named BootCMatch, which implements all the components needed to build and apply the described adaptive AMG b...
This paper investigates application of previously developed Adaptive Algebraic Multilevel Method (α-AMG) to graph Laplacian matrices arising from general graphs. A main challenge in developing AMG methods for graph Laplacian matrices on general graphs is the design of effective coarsening procedure; namely, it appears difficult to maintain reasonable...
We discuss the design and development of a parallel code for Large Eddy Simulation (LES) by exploiting libraries for sparse matrix computations. We formulate a numerical procedure for the LES of turbulent channel flows, based on an approximate projection method, in terms of linear algebra operators involving sparse matrices and vectors. Then we imp...
Fast and scalable software modules for image segmentation are needed for modern high–throughput screening platforms in Computational Biology. In- deed, accurate segmentation is one of the main steps to be applied in a basic software pipeline aimed to extract accurate measurements from a large amount of images. Image segmentation is often formulated...
Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding...
Embryonic Stem Cells (ESCs) are of great interest for providing a resource to generate useful cell types for transplantation or novel therapeutic studies. However, molecular events controlling the unique ability of ESCs to self-renew as pluripotent cells or to differentiate producing somatic progeny have not been fully elucidated yet. In this conte...
Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG)are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near null kernel of the underlined Matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aime...
We introduce a new composite adaptive Algebraic Multigrid (composite alpha-AMG) method to solve systems of linear equations
without a-priori knowledge or assumption on characteristics of near-null components of the AMG preconditioned problem referred to as algebraic smoothness.
Our version of alpha-AMG is a composite solver built through a bootstra...
We present a comparative study of parallel Schwarz preconditioners in the solution of linear systems arising in a Large Eddy Simulation (LES) procedure for turbulent plane channel flows. This procedure applies a time-splitting technique to suitably filtered Navier–Stokes equations, in order to decouple the continuity and momentum equations, and use...
This book constitutes thoroughly refereed post-conference proceedings of the workshops of the 17th International Conference on Parallel Computing, Euro-Par 2011, held in Bordeaux, France, in August 2011. The papers of these 12 workshops CCPI, CGWS, HeteroPar, HiBB, HPCVirt, HPPC, HPSS HPCF, PROPER, CCPI, and VHPC focus on promotion and advancement...
The workshop Algorithms and Programming Tools for Next-Generation High- Performance Scientific Software (HPSS) focuses on recent advances in algorithms and programming tools development for next-generation high-performance scientific software as enabling technologies for new insights into Computational Science.
The chemical task in internal combustion engine simulations concerns with the solution of a non-linear stiff system of Ordinary Differential Equations (ODEs) per each cell of a discretization grid representing engine geometry. The computa- tional cost of the above task, when a detailed kinetic scheme is used, is dominating in engine simulations. Du...
Domain decomposition ideas have long been an essential tool for the solution of PDEs on parallel computers. In recent years many research efforts have been focused on recursively employing do-main decomposition methods to obtain multilevel preconditioners to be used with Krylov solvers. In this context, we developed MLD2P4 (MultiLevelDomain Decompo...
The graphics processing unit (GPU) is used to solve large linear systems derived from partial differential equations. The differential equations studied are strongly convection-dominated, of various sizes, and common to many fields, including computational ...
The solution of large and sparse linear systems is one of the main computational kernels in CFD applications and is often a very time-consuming task, thus requiring the use of effective algorithms on high-performance computers. Preconditioned Krylov solvers are the methods of choice for these systems, but the availability of “good” preconditioners...
This work is concerned with the application of algebraic multilevel preconditioners in the solution of pressure linear systems arising in the large eddy simulation of turbulent incompressible flows in wall-bounded domains. These systems, coming from the discretization of elliptic equations with periodic and Neumann boundary conditions, are large an...
Reliable and efficient solution of chemical kinetics is one of the main computational kernels in engine simulations. The chemical schemes are characterized by high degrees of stiffness, due to the very different reaction rates, and include intermediate species with low density, whose accurate solution is needed to well understand the combustion pro...
Multi-dimensional models for predictive simulations of modern engines are an example of multi-physics and multi-scale mathematical models, since lots of thermofluiddynamic processes in complex geometrical configurations have to be considered. Typical models involve different submodels, including turbulence, spray and combustion models, with differe...
Numerical algorithms have played a key role in parallel computing since
its beginning. In fact, numerical routines have caused the highest
demand for computing power anywhere, making their efficient
parallelization one of the core methodical tasks in high-performance
computing. Many of today’s fastest computers are mostly used for
the solution of h...
The PDP 2007, the Fifteenth Euromicro Conference on Parallel, Distributed and Network-based Processing, organized by the Institute for High-Performance Computing and Networking (ICAR) of the Italian National Research Council (CNR), was held in Naples, Italy. A paper was presented on a business process monitor for the recharging system of a mobile p...
Design and implementation issues that concern the development of a package of parallel algebraic two-level Schwarz preconditioners are discussed. The computations are based on the Parallel Sparse BLAS (PSBLAS) library. The package implements various versions of Additive Schwarz preconditioners and applies a smoothed aggregation technique to generat...
I rapporti tecnici dell'ICAR-CNR sono pubblicati dall'Istituto di Calcolo e Reti ad Alte Prestazioni del Consiglio Nazionale delle Ricerche. Tali rapporti, approntati sotto l'esclusiva responsabilità scientifica degli autori, descrivono attività di ricerca del personale e dei collaboratori dell'ICAR, in alcuni casi in un formato preliminare prima d...
Multidimensional engine simulation is a very challenging field, since many thermofluid processes in complex geometrical configurations have to be considered. Typical mathematical models involve the complete system of unsteady Navier-Stokes equations for turbulent multi-component mixtures of ideal gases, coupled to equations for modeling vaporizing...
We present a package of parallel preconditioners which implements one-level and two-level Domain Decomposition algorithms
on the top of the PSBLAS library for sparse matrix computations. The package, named 2LEV-D2P4 (Two-LEVel Domain Decomposition
Parallel Preconditioners Package based on PSBLAS), currently includes various versions of additive Sc...
In this work we focus on parallel combustion simulation in modern Common Rail Diesel engines when the interaction between
complex chemical kinetics and turbulence is taken into account. We introduce a turbulence term in a detailed chemical reaction
model and analyze the impact on the reliability of pollutant emission predictions and on the efficie...
In this paper we analyze the behaviour of two stiff ODE solvers in the solution of chemical kinetics systems arising from
detailed models of Diesel combustion. We consider general-purpose solvers, based on Backward Differentiation Formulas or Runge-Kutta
methods and compare their impact, in terms of reliability and efficiency, on the solution of tw...
In the last years the in-cylinder 3d combustion models have been focused on the emission predictions, using detailed combustion chemistry. In this paper, we discuss the integration of a detailed combustion chemical kinetic model into the unsteady compressible Navier-Stokes one used by KIVA3V-II code, in order to simulate a Common Rail FIAT 1.9 JTD...
We describe some extensions to Parallel Sparse BLAS (PSBLAS), a library of routines providing basic Linear Algebra operations needed to build iterative sparse linear system solvers on distributed-memory parallel computers. We focus on the implementation of parallel Additive Schwarz preconditioners, widely used in the solution of linear systems aris...
Fast and reliable parallel algorithms for the basic problems of numerical mathematics and their effective implementation in
easy-to-use portable software components are crucial for computational solution of scientific and engineering problems. This
Topic track is a forum for the presentation and discussion of new developments in the field of parall...
In this paper we present first experiences concerning the integration of MPI-based numerical software into an advanced programming environment for building parallel and distributed high-performance applications, which is under development in the context of Italian national research projects. Such a programming environment, named ASSIST, is based on...
In this paper we provide a view of the design and development activity concerning advanced environments for parallel and distributed computing. We start from assessing the main issues driving this research track, in the areas of hardware and software technology and of applications. Then, we identify some key concepts, that can be considered as comm...
An abstract is not available.
In this paper we present our experiences in wrapping a parallel multidimensional quadrature routine, based on thè BLACS message-passing library, in order to obtain a software component computing multiple multi-dimensional integrala. The reference framework, where thè component lives, is a programming environment called ASSIST, under development in...
This paper resumes a description of computational Problem Solving Methodology (PSM), as the methodic process which, given a problem, leads to a software system for its solution. In this context is collocated scientific computing and is discussed the influence of computing environments on the development of effective algorithms and software. Paralle...
During most of the year, the concentrations of both primary and secondary air pollutants over the Campania region (southern Italy) do not comply with the Italian air quality standards. To gain insight into the chemical and meteorological processes that lead to high air pollutant concentrations over this area, the parallel package PNAM (Parallel Nap...
In this paper we analyze the efficiency of some stiff ode solvers, applied to the coupled solution of vertical turbulent diffusion
and chemical kinetics in Air Quality Models. We consider four general-purpose solvers, based on bdf or Rosenbrock methods,
and two special-purpose solvers, developed for odes from atmospheric chemistry, and compare thei...
The parallel Naples airshed model (PNAM) is a parallel software package for the numerical simulation of photosmog episodes in urban scale domains. It solves the atmospheric diffusion equations, which model the air pollution dynamics in a Eulerian approach, using a symmetric time-splitting, where the advection is separated from the (coupled) diffusi...