High-Level Programming for Medical Imaging on Multi-GPU Systems Using the SkelCL Library

Application development for modern high-performance systems with Graphics Processing Units (GPUs) relies on low-level programming approaches like CUDA and OpenCL, which leads to complex, lengthy and error-prone programs. In this paper, we present SkelCL – a high-level programming model for systems with multiple GPUs and its implementation as a library on top of OpenCL. SkelCL provides three main enhancements to the OpenCL standard: 1) computations are conveniently expressed using parallel patterns (skeletons); 2) memory management is simplified using parallel container data types; 3) an automatic data (re)distribution mechanism allows for scalability when using multi-GPU systems. We use a real-world example from the field of medical imaging to motivate the design of our programming model and we show how application development using SkelCL is simplified without sacrificing performance: we were able to reduce the code size in our imaging example application by 50% while introducing only a moderate runtime overhead of less than 5%

Meeting the Need for ETL Documentation: A Model-driven Framework for Customizable Documentation Generation

Within Business Intelligence systems (BI systems), ETL (extract, transform and load) processes move numerous data from heterogeneous sources to a data warehouse and become more complex with growing enterprise size. To keep costs and expenditure of time for maintenance and evolution of those systems slight, ETL processes should be documented. A well-documented system also leads to higher transparency regarding the origin and processing of data, which increases the system’s acceptance by business users. However, the preparation of high-quality software documentation is sophisticated and therefore it usually only takes place in the design or development phase of BI systems. To ensure that the documentation is always updated, an automatic generation is advantageous. The paper at hand presents a conceptual framework for automated configurable ETL documentation generation. The presented framework creates benefits for BI systems developers as well as business users