A new parallel adaptive block-based Gauss-Jordan algorithm

Parallelism in adaptive execution environments requires a parallel adaptive programming methodology. In this paper, we present this methodology on the block-based Gauss-Jordan algorithm used in numeric analysis to solve linear systems. The application includes a work scheduling strategy and is in some way fault tolerant. It is implemented and experimented with the MARS parallel adaptive programming environment. The results show that an absolute efficiency of 92% is possible on a farm of DEC/ALPHA processors interconnected by a Gigaswitch network, an absolute efficiency of 67% can be obtained on an Ethernet network of SUN-Sparc 4 workstations and on each of these networks perfect relative efficiency is often reached. Moreover, some experimentations done on a network of heterogeneous machines show that the overhead induced by the management of the adaptivity is not important. Keywords:Gauss-Jordan Method, Adaptive Parallelism, Networks of Workstations (NOWs), Heterogeneous Systems, Fau..

Multi level programming Paradigm for Extreme Computing

Abstract: In order to propose a framework and programming paradigms for post-petascale computing, on the road to exascale computing and beyond, we introduced new languages, associated with a hierarchical multi-level programming paradigm, allowing scientific end-users and developers to program highly hierarchical architectures designed for extreme computing. In this paper, we explain the interest of such hierarchical multi-level programming paradigm for extreme computing and its well adaptation to several large computational science applications, such as for linear algebra solvers used for reactor core physic. We describe the YML language and framework allowing describing graphs of parallel components, which may be developed using PGAS-like language such as XMP, scheduled and computed on supercomputers. Then, we propose experimentations on supercomputers (such as the “K” and “Hooper” ones) of the hybrid method MERAM (Multiple Explicitly Restarted Arnoldi Method) as a case study for iterative methods manipulating sparse matrices, and the block Gauss-Jordan method as a case study for direct method manipulating dense matrices. We conclude proposing evolutions for this programming paradigm

Enablement of advanced silicon photonics optical passive library design leveraging silicon based RF passive development methodology

International audienceSilicon photonics technology emerged as a promising solution to address the technical challenges related to 100 Gb/s and 400 Gb/s optical link. Enabling the development of silicon photonics products requires the development of optical passive libraries integrated within conventional CAD tools used in the CMOS design flow. The optimization and modeling of silicon photonics optical passive is therefore a key point that can be addressed by leveraging methodologies that have been previously set up for optimizing RF passive in CMOS and BiCMOS technologies. In this paper, the relevance of such an approach is evaluated: the combination of FDTD electromagnetic simulations and a Design Of Experiments (DOE) prototyping have been used for optimizing scalable Grating Couplers (GCs) targeting Wavelength-Division Multiplexing applications (WDM). The obtained models for the GC have been successfully qualified experimentally