Search Results - "Vella, Flavio"

Scaling betweenness centrality using communication-efficient sparse matrix multiplication by Solomonik, Edgar, Besta, Maciej, Vella, Flavio, Hoefler, Torsten

“…Betweenness centrality (BC) is a crucial graph problem that measures the significance of a vertex by the number of shortest paths leading through it. We…”
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multi-GPU aggregation-based AMG preconditioner for iterative linear solvers by Bernaschi, Massimo, Celestini, Alessandro, D'Ambra, Pasqua, Vella, Flavio

“…We present and release in open source format a sparse linear solver which efficiently exploits heterogeneous parallel computers. The solver can be easily…”
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Scalable Energy Games Solvers on GPUs by Formisano, Andrea, Gentilini, Raffaella, Vella, Flavio

“…Modeling the consumption of limited resources, e.g., time or energy, plays a central role on the design of reactive systems such as embedded controllers. To…”
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Strategies and systems towards grids and clouds integration:A DBMS-based solution by Mariotti, Mirko, Gervasi, Osvaldo, Vella, Flavio, Cuzzocrea, Alfredo, Costantini, Alessandro

“…Cloud and Grid computing share some essential driving ideas although the computing and economic models are very different. In this paper, we propose different…”
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Solutions to the st-connectivity problem using a GPU-based distributed BFS by Bernaschi, Massimo, Carbone, Giancarlo, Mastrostefano, Enrico, Vella, Flavio

“…The st-connectivity problem (ST-CON) is a decision problem that asks, for vertices and in a graph, if is reachable from . Although originally defined for…”
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Multilevel Parallelism for the Exploration of Large-Scale Graphs by Bernaschi, Massimo, Bisson, Mauro, Mastrostefano, Enrico, Vella, Flavio

“…We present the most recent release of our parallel implementation of the BFS and BC algorithms for the study of large scale graphs. Although our reference…”
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The AES Implantation Based on OpenCL for Multi/many Core Architecture by Gervasi, Osvaldo, Russo, Diego, Vella, Flavio

“…In this article we present a study on an implementation, named clAES, of the symmetric key cryptography algorithm Advanced Encryption Standard (AES) using the…”
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Gauss-Newton Natural Gradient Descent for Physics-Informed Computational Fluid Dynamics by Jnini, Anas, Vella, Flavio, Zeinhofer, Marius

“…We propose Gauss-Newton's method in function space for the solution of the Navier-Stokes equations in the physics-informed neural network (PINN) framework…”
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State of practice: evaluating GPU performance of state vector and tensor network methods by Vallero, Marzio, Vella, Flavio, Rech, Paolo

“…The frontier of quantum computing (QC) simulation on classical hardware is quickly reaching the hard scalability limits for computational feasibility…”
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cuVegas: Accelerate Multidimensional Monte Carlo Integration through a Parallelized CUDA-based Implementation of the VEGAS Enhanced Algorithm by Tolotti, Emiliano, Jnini, Anas, Vella, Flavio, Passerone, Roberto

“…This paper introduces cuVegas, a CUDA-based implementation of the Vegas Enhanced Algorithm (VEGAS+), optimized for multi-dimensional integration in GPU…”
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On the Efficacy of Surface Codes in Compensating for Radiation Events in Superconducting Devices by Vallero, Marzio, Casagranda, Gioele, Vella, Flavio, Rech, Paolo

“…Reliability is fundamental for developing large-scale quantum computers. Since the benefit of technological advancements to the qubit's stability is…”
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Multi-GPU aggregation-based AMG preconditioner for iterative linear solvers by Bernaschi, Massimo, Celestini, Alessandro, D'Ambra, Pasqua, Vella, Flavio

“…IEEE Transactions on Parallel and Distributed Systems (2023) We present and release in open source format a sparse linear solver which efficiently exploits…”
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High Performance Unstructured SpMM Computation Using Tensor Cores by Okanovic, Patrik, Kwasniewski, Grzegorz, Labini, Paolo Sylos, Besta, Maciej, Vella, Flavio, Hoefler, Torsten

“…High-performance sparse matrix-matrix (SpMM) multiplication is paramount for science and industry, as the ever-increasing sizes of data prohibit using dense…”
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Scaling Expected Force: Efficient Identification of Key Nodes in Network-Based Epidemic Models by Labini, Paolo Sylos, Jurco, Andrej, Ceccarello, Matteo, Guarino, Stefano, Mastrostefano, Enrico, Vella, Flavio

“…Structural centrality measures are often used to approximate or predict dynamical influence in a network. The recently proposed Expected Force of Infection…”
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The Landscape of GPU-Centric Communication by Unat, Didem, Turimbetov, Ilyas, Issa, Mohammed Kefah Taha, Sağbili, Doğan, Vella, Flavio, De Sensi, Daniele, Ismayilov, Ismayil

“…In recent years, GPUs have become the preferred accelerators for HPC and ML applications due to their parallelism and fast memory bandwidth. While GPUs boost…”
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Blocking Techniques for Sparse Matrix Multiplication on Tensor Accelerators by Labini, Paolo Sylos, Bernaschi, Massimo, Silvestri, Francesco, Vella, Flavio

“…Tensor accelerators have gained popularity because they provide a cheap and efficient solution for speeding up computational-expensive tasks in Deep Learning…”
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The potential of high-performance computing for the Internet of Sounds by Turchet, Luca, Vella, Flavio, Luigi, Sandro

“…High-Performance Computing (HPC) technology is impacting several industries, including the creative industries and those operating in the Internet of Things…”
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Scaling Expected Force: Efficient Identification of Key Nodes in Network-based Epidemic Models by Labini, Paolo Sylos, Jurco, Andrej, Ceccarello, Matteo, Guarino, Stefano, Mastrostefano, Enrico, Vella, Flavio

“…Centrality measures are fundamental tools of network analysis as they highlight the key actors within the network. This study focuses on a newly proposed…”
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Asynchronous Distributed-Memory Triangle Counting and LCC with RMA Caching by Strausz, Andras, Vella, Flavio, Di Girolamo, Salvatore, Besta, Maciej, Hoefler, Torsten

“…Triangle count and local clustering coefficient are two core metrics for graph analysis. They find broad application in analyses such as community detection…”
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Blocking Sparse Matrices to Leverage Dense-Specific Multiplication by Labini, Paolo Sylos, Bernaschi, Massimo, Nutt, Werner, Silvestri, Francesco, Vella, Flavio

“…Research to accelerate matrix multiplication, pushed by the growing computational demands of deep learning, has sprouted many efficient architectural…”
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