A Process-Oriented Software Architecture Reconstruction Taxonomy

International audienceTo maintain and understand large applications, it is cru- cial to know their architecture. The first problem is that architectures are not explicitly represented in the code as classes and packages are. The second problem is that suc- cessful applications evolve over time so their architecture inevitably drifts. Reconstructing and checking whether the architecture is still valid is thus an important aid. While there is a plethora of approaches and techniques supporting architecture reconstruction, there is no comprehensive state of the art and it is often difficult to compare the ap- proaches. This article presents a first state of the art in soft- ware architecture reconstruction, with the desire to support the understanding of the field

Monitoring the CMS strip tracker readout system

The CMS Silicon Strip Tracker at the LHC comprises a sensitive area of approximately 200 m2 and 10 million readout channels. Its data acquisition system is based around a custom analogue front-end chip. Both the control and the readout of the front-end electronics are performed by off-detector VME boards in the counting room, which digitise the raw event data and perform zero-suppression and formatting. The data acquisition system uses the CMS online software framework to configure, control and monitor the hardware components and steer the data acquisition. The first data analysis is performed online within the official CMS reconstruction framework, which provides many services, such as distributed analysis, access to geometry and conditions data, and a Data Quality Monitoring tool based on the online physics reconstruction. The data acquisition monitoring of the Strip Tracker uses both the data acquisition and the reconstruction software frameworks in order to provide real-time feedback to shifters on the operational state of the detector, archiving for later analysis and possibly trigger automatic recovery actions in case of errors. Here we review the proposed architecture of the monitoring system and we describe its software components, which are already in place, the various monitoring streams available, and our experiences of operating and monitoring a large-scale system

Overview of the software architecture and data flow for the J-PET tomography device

Modern TOF-PET scanner systems require high-speed computing resources for efficient data processing, monitoring and image reconstruction. In this article, we present the data flow and software architecture for the novel TOF-PET scanner developed by the J-PET Collaboration. We discuss the data acquisition system, reconstruction framework and image reconstruction software. Also, the concept of computing outside hospitals in the remote centers such as Świerk Computing Centre in Poland is presented

Hardware/software 2D-3D backprojection on a SoPC platform

International audienceThe reduction of image reconstruction time is needed to spread the use of PET for research and routine clinical practice. In this purpose, this article presents a hardware/software architecture for the acceleration of 3D backprojection based upon an efficient 2D backprojection. This architecture has been designed in order to provide a high level of parallelism thanks to an efficient management of the memory accesses which would have been otherwise strongly slowed by the external memory. The reconstruction system is embedded in a SoPC platform (System on Programmable Chip), the new generation of reconfigurable circuit. The originality of this architecture comes from the design of a 2D Adaptative and Predictive Cache (2D-AP Cache) which has proved to be an efficient way to overcome the memory access bottleneck. Thanks to a hierarchical use of this cache, several backprojection operators can run in parallel, accelerating in this manner noteworthy the reconstruction process. This 2D reconstruction system will next be used to speed up 3D image reconstruction

Reconstruction of Software Component Architectures and Behaviour Models using Static and Dynamic Analysis

Model-based performance prediction systematically deals with the evaluation of software performance to avoid for example bottlenecks, estimate execution environment sizing, or identify scalability limitations for new usage scenarios. Such performance predictions require up-to-date software performance models. This book describes a new integrated reverse engineering approach for the reconstruction of parameterised software performance models (software component architecture and behaviour)

Three-dimensional reconstruction of intracoronary ultrasound images. Rationale, approaches, problems, and directions

Although intracoronary ultrasonography allows detailed tomographic imaging of the arterial wall, it fails to provide data on the structural architecture and longitudinal extent of arterial disease. This information is essential for decision making during therapeutic interventions. Three-dimensional reconstruction techniques offer visualization of the complex longitudinal architecture of atherosclerotic plaques in composite display. Progress in computer hardware and software technology have shortened the reconstruction process and reduced operator interaction considerably, generating three-dimensional images with delineation of mural anatomy and pathology. The indications for intravascular ultrasonography will grow as the technique offers the uni