A Low Level Component Model enabling Resource Specialization of HPC Applications
type: Dataset
description: Scientific applications are still getting more complex, e.g. to improve their accuracy by taking into account more phenomena. Moreover, computing infrastructures are continuing their fast evolution. Therefore, software engineering is becoming a major issue to achieve easiness of development, portability, simple maintenance, while achieving high performance. Software component model is a promising approach, which enables to manipulate the software architecture of an application. However, existing models do not capture enough resource specificities. This paper proposes a low level component model (L2C) that supports directly native connectors such as MPI, shared memory and method invocation. L2C is intended to be used as a back end by a ''compiler'' (such as HLCM) to generate an application assembly specific to a given machine. This paper shows on a typical domain decomposition use case that \llc can achieve the same performance as native implementations, while gaining benefits such as enabling resource specialization capabilities.
identifier: Report N°: RR-7966
issued: 2026-05-18T09:51:17.055103
language: en
modified: 2026-05-18T09:51:17.055110
contact point: Organization
  fn: CCSD
keyword: component
keyword: domain-decomposition
keyword: grid5000
keyword: hpc
keyword: infoeu-reposemanticsreport
keyword: infoinfo-dccomputer-science-csdistributed-parallel-and-cluster-computing-csdc
keyword: l2c
keyword: reports
keyword: software-architecture
landing page: https://inria.hal.science/hal-00698573

A Low Level Component Model enabling Resource Specialization of HPC Applications
type: Distribution
format: HTML
issued: 2026-05-18T09:51:17.133616
modified: 2026-05-18T09:51:17.008501
access URL: https://inria.hal.science/hal-00698573

test_moissonnage_selune
type: Agent