speaker: Leonardo Bautista Gomez, Senior researcher at BSC, and Kai Keller, Software engineer at BSC
date: April 1st, 2020, 11 AM
abstract: Large scale infrastructures for distributed and parallel computing offer thousands of computing nodes to their users to satisfy their computing needs. As the need for massively parallel computing increases in industry and development, cloud infrastructures and computing centers are being forced to increase in size and to transition to new computing technologies. While the advantage for the users is clear, such evolution imposes significant challenges, such as energy consumption and fault tolerance. Fault tolerance is even more critical in infrastructures built on commodity hardware. Recent works have shown that large scale machines built with commodity hardware experience more failures than previously thought. In this webinar, Leonardo Bautista Gomez and Kai Keller, respectively Senior Researcher and Software Engineer at the Barcelona Supercomputing Center, will focus on how to guarantee high reliability to high-performance applications running in large infrastructures. In particular, they will cover all the technical content necessary to implement scalable multilevel checkpointing for tightly coupled applications. This will include an overview of the internals of the FTI library, and explain how multilevel checkpointing is implemented today, together with examples that the audience can test and analyze on their own laptops, so that they learn how to use FTI in practice, and ultimately transfer that knowledge to their production systems.
speaker: Herbert Owen, senior researcher at Barcelona Supercomputing Center
date: April 20th, 2020, 11.00 – 12.15 AM, Monday,
abstract: Wind resource assessment is performed before deciding to construct a new wind farm. Its objective is to obtain a better understanding of the flow over the potential site for a wind farm. It combines experimental data from a couple of wind mast that are the energy the wind farm can produce and enables to determine the optimal positions for the wind turbines. Currently, state of the art in the industry is to resort to Reynolds Averaged Navier Stokes (RANS) turbulence models for such simulations. While RANS models are computationally affordable and quite robust, they are known to have accuracy limitations for regions where separated flows are found, behind mountains for instance. Large Eddy Simulation (LES) can provide much more accurate results, at a much higher computational cost. With the advent of exascale computers, LES has become a viable alternative. In this talk, we will present the work we have been doing for Iberdrola during the last six years and the steps we are taking within EoCoE to push the limits towards much higher accuracies thanks to the efficient use of exascale resources.
speaker: Julien Bigot, Senior researcher at CEA
date: March 6th, 2020, 10:00 AM
abstract: Julien Bigot, tenured computer science researcher at CEA, will present the PDI data interface, a declarative API to decouple application codes from the Input / Output strategy to use. He will present its plugin system, which supports the selection of the best-suited existing IO library through a configuration file in each part of the code depending on the hardware available, the IO pattern, the problem size, etc. This webinar will demonstrate the advantage of this approach in term of software engineering and performance through the example of the Gysela5D code.
speaker: Pasqua D'Ambra, Senior Research Scientist at the National Research Council of Italy
date: 24/02/2020, 3PM
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
speaker: Fabio Durastante (CNR, Naples, Italy)
date: January 20th, 2020
abstract: This tutorial will address the basic functionalities of the PSBLAS library for the parallelization of computationally intensive scientific applications. We will delve into the parallel implementation of iterative solvers for sparse linear systems in a distributed memory paradigm, and look at the routines for multiplying sparse matrices by dense matrices, solving block diagonal systems with triangular diagonal entries, preprocessing sparse matrices, and several additional routines for dense matrix operations. We will discuss both the direct usage of the library in Fortran2003 and the usage of the C interfaces. The tutorial will include examples relative to the EoCoE-II application areas, and highlight how the PSBLAS environment can be used to obtain scalable parallel codes.