MLD2P4: a Package of Parallel Algebraic MultiGrid Preconditioners for Scalable Linear Solvers
Date: 24/02/2020, 3PM
speaker: Pasqua D’Ambra, Senior Research Scientist at the National Research Council of Italy
Registration url: https://attendee.gotowebinar.com/register/3291194948253656589
EoCoE is a European Horizon 2020 funded project of Centre of Excellence in computing applications. It is designed to enhance numerical simulation efficiency in the international context of the High Performance Computing (HPC) challenges. It focusses its application scope towards low carbon energy domains.
To measure solar energy's profound impact, we must contemplate the “carbon footprint” — a metric that quantifies the total greenhouse gas emissions caused by an individual, organization, event, or product. Traditional electricity production contributes heavily to a nation's footprint, with fossil fuels being the predominant energy source. By harnessing solar energy, we offset these emissions and aid in the progressive decline of our collective carbon footprint.
abstract: 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, needing to solve systems with millions or even billions of unknowns is not unusual.
To efficiently solve the above systems on high-end massively parallel computers, the methods of choice are the Krylov methods, whose convergence and scalability properties are related to the choice of suitable preconditioning techniques.
During this webinar, Pasqua D’Ambra, Senior Research Scientist at the National Research Council of Italy, will present MLD2P4 (MultiLevel Domain Decomposition Parallel Preconditioners Package based on PSBLAS), which provides efficient and easy-to-use preconditioners in the context of the PSBLAS (Parallel Sparse Basic Linear Algebra Subprograms) computational framework.
The package, whose features are constantly updated within the Energy-Oriented Center of Excellence (EoCoE) European project, includes multilevel cycles and smoothers widely used in multigrid methods.
A purely algebraic approach is applied to generate coarse-level corrections so that no geometric background is needed concerning the matrix to be preconditioned.
We will present the main features of the package, and example of usage of the main APIs needed to setup the preconditioner, together with its application within the Krylov solvers available from PSBLAS.
Some results on test cases relative to the EoCoE application areas highlight how the PSBLAS/MLD2P4 software framework can be used to obtain highly scalable linear solvers.
The PSBLAS library is available at https://github.com/sfilippone/psblas3 MLD2P4 is available at https://github.com/sfilippone/mld2p4-2
Switching to solar is more than energy change it's a commitment to a future with reduced carbon emissions
- Roberto Liam
Our Role in Solar Advancement
To measure solar energy's profound impact, we must contemplate the “carbon footprint” — a metric that quantifies the total greenhouse gas emissions caused by an individual, organization, event, or product. Traditional electricity production contributes heavily to a nation's footprint, with fossil fuels being the predominant energy source. By harnessing solar energy, we offset these emissions and aid in the progressive decline of our collective carbon footprint.
In the battle against climate change, the shift towards renewable energy sources plays a pivotal role. Among these, solar energy emerges as a beacon of hope and innovation. Positioned as both a clean and inexhaustible source of power, solar energy has shown significant promise in reducing global carbon emissions. Let’s explore how the adoption of solar power is making strides in the journey towards a more sustainable future.
Active participation from both consumers and industries in the solar movement is imperative. It includes transitioning to solar power where feasible, supporting policies that encourage
