Materials

• The following are two presentation (in italian) related to the CARES project, funded under the FISR 2020 COVID




• USN (Urban Social Networks)
  

  USN is a tool for generating age-stratified and geo-referenced synthetic social networks. It uses gridded population density data, aggregated demographic data and, when available, estimated age-based social mixing patterns. It can be used for advanced simulations of dynamic processes that may be influenced by agents’ preferences and personal relations. Here is the link to the repository https://gitlab.com/cranic-group/usn




• DCBM_solver
  

  This software solves the system of equation arising from a maximum-entropy Degree-Corrected Block Model, or from the Fitness-Corrected Block Model implemented as part of the USN framework at https://gitlab.com/cranic-group/usn It allows to obtain the set of Lagrange's multipliers needed to compute the edge-probabilities of the DCBM/FCBM model. Here is the link to the repository https://gitlab.com/cranic-group/dcbm_solver




• BootCMatchGX
  

  BootCMatch for multi-GPU systems. Sparse solvers are one of the building blocks of any technology for reliable and high-performance scientific and engineering computing. In BootCMatchGX we make available an Algebraic MultiGrid (alpha-AMG) method for preconditioning algebraic linear systems Ax = b, where A is a symmetric positive definite (s.p.d.), large and sparse matrix. All the computational kernels for setup and application of the adaptive AMG method, as preconditioner of an efficient version of the Conjugate Gradient Krylov solver, were designed and tuned for hybrid MPI-CUDA programming environments when multiple distributed nodes hosting Nvidia GPUs are available Here is the link to the repository https://github.com/bootcmatch/BootCMatchGX