Davide Spataro

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Andrej Dujella

University of Zagreb

Hemin Koyi

Uppsala University

Jana Javornik

University of East London

Graham Martin

University of Leicester

Gwen Robbins Schug

University of North Carolina at Greensboro

Gabriel Gutierrez-Alonso

University of Salamanca

John Sutton

Macquarie University

Eros Carvalho

Universidade Federal do Rio Grande do Sul

Kevin Arbuckle

Swansea University

Jesper Hoffmeyer

University of Copenhagen

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Papers by Davide Spataro

Seamless acceleratin numerical regular grid methods on manycore systems

Dottorato di Ricerca in Matematica ed Informatica. Ciclo XXXOver the last two decades, a lot has ... more Dottorato di Ricerca in Matematica ed Informatica. Ciclo XXXOver the last two decades, a lot has changed regarding the way modern scientific applications are designed, written and executed, especially in the field of data-analytics, scientific computing and visualization. Dedicated computing machines are nowadays large, powerful agglomerates of hundreds or thousands of multi-core computing nodes interconnected via network each coupled with multiple accelerators. Those kinds of parallel machines are very complex and their efficient programming is hard, bug-prone and time-consuming. In the field of scientific computing, and of modeling and simulation especially, parallel machines are used to obtain approximate numerical solutions to differential equations for which the classical approach often fails to solve them analytically making a numerical computer-based approach absolutely necessary. An approximate numerical solution of a partial differential equation can be obtained by applying a number of methods, as the finite element or finite difference method which yields approximate values of the unknowns at a discrete number of points over the domain. When large domains are considered, big parallel machines are required in order to process the resulting huge amount of mesh nodes. Parallel programming is notoriously complex, often requiring great programming efforts in order to obtain efficient solvers targeting large computing cluster. This is especially true since heterogeneous hardware and GPGPU has become mainstream. The main thrust of this work is the creation of a programming abstraction and a runtime library for seamless implementation of numerical methods on regular grids targeting different computer architecture: from commodity single-core laptops to large clusters of heterogeneous accelerators. A framework, OpenCAL had been developed, which exposes a domain specific language for the definition of a large class of numerical models and their subsequent deployment on the targeted machines. Architecture programming details are abstracted from the programmer that with little or no intervention at all can obtain a serial, multi-core, single-GPU, multi- GPUs and cluster of GPUs OpenCAL application. Results show that the framework is effective in reducing programmer effort in producing efficient parallel numerical solvers.Università della Calabri

Parallel Execution of Cellular Automata through Space Partitioning: The Landslide Simulation Sciddicas3-Hex Case Study

2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2017

The performance and scalability of cellular automata, when executed on parallel/distributed machi... more The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute its code only after all the other nodes have executed the previous step. However, if the code is parallelized by partitioning the space of the automata, these synchronization requirements can be relaxed: indeed, a node that manages a given portion of the cellular automata can execute a new step after synchronizing only with the nodes that manage the adjacent portions, while the remaining nodes can execute different time steps. This can be a notable advantage in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or of the data and/or of the different functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as a bottleneck can vary during the execution. The goal of the paper is to analyze the benefits that can be achieved with the described approach when different space partitioning strategies are taken into account: i.e., the mono-and the two-dimensional partitioning. Experiments referred to a wellknown cellular automata, namely the SciddicaS3-hex model for landslide simulation, exhibit good scalability and prove that the partitioning scheme adopted can result crucial for improving the overall computational performances.

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A General Computational Formalism for Networks of Structured Grids

Lecture Notes in Computer Science, 2020

Extended Cellular Automata (XCA) represent one of the most known parallel computational paradigm ... more Extended Cellular Automata (XCA) represent one of the most known parallel computational paradigm for the modeling and simulation of complex systems on stenciled structured grids. However, the formalism does not perfectly lend itself to the modeling of multiple automata were two or more models co-evolve by interchanging information and by synchronizing during the dynamic evolution of the system. Here we propose the Extended Cellular Automata Network (XCAN) formalism, an extension of the original XCA paradigm in which different automata are described by means of a graph, with vertices representing automata and interrelations modeled by a set of edges. The formalism is applied to the modeling of a theoretical 2D/3D coupled system, where space/time variance and synchronization aspects are pointed out.

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A Tracking Algorithm for Particle-Like Moving Objects

2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2017

Particle tracking plays an important role in numerous fields of science. In this paper, we presen... more Particle tracking plays an important role in numerous fields of science. In this paper, we present TraCCA, an algorithm for detecting and tracking particles based on geometrical difference evaluation and centroid displacement analysis to reconstruct the trajectories. This method works for n-dimensional input data provided that particles are represented by at least a centroid space coordinate and a geometrical entity which describe their shape. Since 2-D images are a common source of such data, we also present a framework for image-manipulation based on Extended Cellular Automata (XCA). We have applied and validated TraCCA in investigating the motility of B. subtilis. injected in a microfluidic device using 4100 images taken at 100 frames per second. Results show that the framework is able to reconstruct the trajectories as computed motion parameters are in accordance with the ones reported in the literature.

Applications of the OpenCAL scientific library in the context of CFD: Applications to debris flows

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), 2017

We here present computational results as performed by the new OpenCAL scientific library for seam... more We here present computational results as performed by the new OpenCAL scientific library for seamless implementation of models referred to Computational Fluid Dynamics (CFD). In particular, OpenCAL allows for the straightforward definition of Cellular Automata- and Finite Differences-based simulation models of complex systems, by also supporting Extended Cellular Automata and all those computing paradigms based on regular computational grids. Two different parallel implementations are presented, which permit to exploit both multi-core CPUs on shared memory computers, and a wide range of heterogeneous devices like GPUs and other many-core coprocessors. Experiments, referred to a well-known cellular automata, namely the SCIDDICA S3−hex model for landslide simulation, exhibit good scalability, and numerical correctness and efficiency have been assessed on both multi-core CPUs and different many-core coprocessors. The good performances that were achieved in all benchmarks confirm the li...

A first multi-GPU/multi-node implementation of the open computing abstraction layer

Journal of Computational Science, 2019

Here we present a first multi-node/multi-GPU implementation of OpenCAL for grid-based high-perfor... more Here we present a first multi-node/multi-GPU implementation of OpenCAL for grid-based high-performance numerical simulation. OpenCL and MPI have been adopted as low-level APIs for maximum portability and performance evaluated with respect to three different benchmarks, namely a Sobel edge detection filter, a Julia fractal generator, and the SciddicaT Cellular Automata model for fluidflows simulation. Different hardware configurations of a dual-node test cluster have been considered, allowing for executions up to four GPUs. Optimal performance has been achieved in consideration of the compute/memory bound nature of both benchmarks and hardware configurations.

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Multi-agent System with Multiple Group Modelling for Bird Flocking on GPU

2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), 2016

Birds flocking is an interesting natural phenomenon to study as proven by numerous papers in this... more Birds flocking is an interesting natural phenomenon to study as proven by numerous papers in this field. In this paper, we present a GPGPU model for birds flocking simulation using NVIDIA's CUDA framework. This technology has been widely adopted in computational science and have dramatically increased computation performances. Using the autonomous agent approach with multi-agents and multiple groups for birds flocking modeling, we present the ACIADDRI model both aggregate motion of a large number of birds in virtual environment and other species or predators avoidance in the plane as well. From these experiments we gained significant performance improvements in the terms of speedup. In conclusion, the work shows that the use of the CUDA technology can be effective to cut computational costs also in multi-agent modeling.

Efficient Lava Flows Simulations with OpenCL: A Preliminary Application for Civil Defence Purposes

2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2015

GPGPU (General Purpose computing on Graphics Processing Units) has marked a revolution in the fie... more GPGPU (General Purpose computing on Graphics Processing Units) has marked a revolution in the field of Parallel Computing allowing to achieve computational performance unimaginable until a few years ago. This hardware has proven to be extremely reliable and suitable to simulate Cellular Automata (CA) models for modeling complex systems whose evolution can be described in terms of local interactions. Starting from previous GPGPU implementations of CA models with CUDA, this paper presents an effective implementation of a well-known numerical model for simulating lava flows on Graphical Processing Units (GPU) based on the OpenCL (Open Computing Language) standard. In addition, a preliminary Civil Defence application related Hazard maps of an area located at Mt. Etna volcano (South Italy), confirms the validity of OpenCL and both low-cost and high-end graphics hardware as an alternative to expensive solutions for the simulation of CA models.

The new SCIARA-fv3 numerical model and acceleration by GPGPU strategies

The International Journal of High Performance Computing Applications, 2016

This paper presents the parallel implementation, using the Compute Unified Device Architecture (C... more This paper presents the parallel implementation, using the Compute Unified Device Architecture (CUDA) architecture, of the SCIARA-fv3 Complex Cellular Automata model for simulating lava flows. The computational model is based on a Bingham-like rheology and both flow velocity and the physical time corresponding to a computational step have been made explicit. The parallelization design has involved, among other issues, the application of strategies that can avoid incorrect computation results due to race conditions and achieving the best performance and occupancy of the underlying available hardware. Two hardware types were adopted for testing different versions of the CUDA implementations of the SCIARA-fv3 model, namely the GTX 580 and GTX 680 graphic processors. Despite its computational complexity, carried out experiments of the model parallelization have shown significant performance improvements, confirming that graphic hardware can represent a valid solution for the implementat...

CUDA Dynamic Active Thread List Strategy to Accelerate Debris Flow Simulations

2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015

Cellular Automata represent a formal frame for dynamical systems which evolve on the base of loca... more Cellular Automata represent a formal frame for dynamical systems which evolve on the base of local interactions. We here present first results of the CUDA parallelization of the SCIDDICA S3-hex Complex Cellular Automata model for simulating debris flows. In particular, a first strategy for the parallelization of the model is based on a straightforward one thread - one cell approach, where each cell in the cellular space is computed by a CUDA thread. A second approach concerns the adoption of a list of CA computational active cells which is handled step by step by an efficient stream compaction algorithm, in order to reduce the excessive use of computationally inactive threads. First results performed on different graphic processors have shown that, by adopting the different CUDA strategies, this kind of hardware can be effective for landslide risk mitigation.

Evolutionary Applications to Cellular Automata Models for Volcano Risk Mitigation

Communications in Computer and Information Science, 2014

A GPGPU accelerated evolutionary computation-based decision support system for defining and optim... more A GPGPU accelerated evolutionary computation-based decision support system for defining and optimizing volcanic hazard mitigation interventions is proposed. Specifically, the new Cellular Automata numerical model SCIARA-fv3 for simulating lava flows at Mt Etna (Italy) and Parallel Genetic Algorithms (PGA) have been applied for optimizing protective measures construction by morphological evolution. A case study is considered, where PGA are applied for the optimization of the position, orientation and extension of earth barriers built to protect a touristic facility located near the summit of Mt. Etna (Italy) volcano which was interested by the 2001 lava eruption. The methodology has produced extremely positive results and, in our opinion, can be applied within a broader risk assessment framework, having immediate and far reaching implications both in land use and civil defense planning.

Lava Flow Modeling by the Sciara-Fv3 Parallel Numerical Code

2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2014

The Open Computing Abstraction Layer for Parallel Complex Systems Modeling on Many-Core Systems

Journal of Parallel and Distributed Computing, 2018

h i g h l i g h t s • Domain Specific Language for structured grids modeling. • MPI/OpenMP/OpenCL... more h i g h l i g h t s • Domain Specific Language for structured grids modeling. • MPI/OpenMP/OpenCL implementations for execution on heterogeneous systems. • Efficient built-in data structures and parallel algorithms. • High computational performances achieved. • Possibility to devise the best parallel hardware platform for execution.

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Seamless acceleratin numerical regular grid methods on manycore systems

Parallel Execution of Cellular Automata through Space Partitioning: The Landslide Simulation Sciddicas3-Hex Case Study

2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2017

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A General Computational Formalism for Networks of Structured Grids

Lecture Notes in Computer Science, 2020

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A Tracking Algorithm for Particle-Like Moving Objects

2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2017

Applications of the OpenCAL scientific library in the context of CFD: Applications to debris flows

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), 2017

A first multi-GPU/multi-node implementation of the open computing abstraction layer

Journal of Computational Science, 2019

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Multi-agent System with Multiple Group Modelling for Bird Flocking on GPU

2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), 2016

Efficient Lava Flows Simulations with OpenCL: A Preliminary Application for Civil Defence Purposes

2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2015

The new SCIARA-fv3 numerical model and acceleration by GPGPU strategies

The International Journal of High Performance Computing Applications, 2016

CUDA Dynamic Active Thread List Strategy to Accelerate Debris Flow Simulations

2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015

Evolutionary Applications to Cellular Automata Models for Volcano Risk Mitigation

Communications in Computer and Information Science, 2014

Lava Flow Modeling by the Sciara-Fv3 Parallel Numerical Code

2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2014

The Open Computing Abstraction Layer for Parallel Complex Systems Modeling on Many-Core Systems

Journal of Parallel and Distributed Computing, 2018

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