The fast-growing demand of computational fluid dynamics(CFD) application for computing resources stimulates the development of high performance computing(HPC) and meanwhile raises new requirements for the technology of parallel application performance monitor and analysis.In response to large-scale and long-time running for the application of CFD,online and scalable performance analysis technology is required to optimize the parallel programs as well as to improve their operational efficiency.As a result,this research implements a scalable infrastructure for online performance analysis on CFD application with homogeneous or heterogeneous system.The infrastructure is part of the parallel application performance monitor and analysis system(PAPMAS) and is composed of two modules which are scalable data transmission module and data storage module.The paper analyzes and elaborates this infrastructure in detail with respect to its design and implementation.Furthermore,some experiments are carried out to verify the rationality and high efficiency of this infrastructure that could be adopted to meet the practical needs.
Architecture analysis and design language (AADL) is an architecture description language standard for embedded real-time systems and it is widely used in safety-critical applications. For facilitating verification and analysis, model transformation is one of the methods. A synchronous subset of AADL and a general methodology for translating the AADL subset into timed abstract state machine (TASM) were studied . Based on the atlas transformation language (ATL) framework, the associated translating tool AADL2TASM was implemented by defining the meta-model of both AADL and TASM, and the ATL transformation rules. A case study with property verification of the AADL model was also presented for validating the tool.
