Experiences with component-oriented technologies in nuclear power plant simulators
Software—Practice & Experience
Computational error handling as aspects: a case study
Proceedings of the 1st workshop on Linking aspect technology and evolution
IEEE Transactions on Information Technology in Biomedicine
Parallel computing in java: looking for the most effective RMI implementation for clusters
PPAM'05 Proceedings of the 6th international conference on Parallel Processing and Applied Mathematics
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Modern systems for the analysis of image-based biomedical data, such as functional magnetic resonance imaging (fMRI), require fast computational techniques and rapid, robust development. Object-oriented programming languages such as Java and C++ provide the foundations for the development of complex data analysis applications. This case study explores the advantages and disadvantages of using these two programming environments for scientific computation as typified in the analysis of fMRI datasets. C++ is well suited for computational and memory optimization while Java is more compliant to the object-oriented paradigm, supports cross-platform development and has a rich set of application programming interface (API) classes. The same data model and algorithms were implemented in C++ and Java, and a user interface was developed with the Java API. Comparisons were made with respect to computational performance and ease of development. Benchmarks show that C++ generally outperforms Java, while Java is easier to use, leading to more robust code and shorter development times. However, with the advent of newer just-in-time compilers, Java performance is at times comparable to C++. The latest Java virtual machine technology is closing the gap and eventually Java should be a good compromise between efficient algorithm performance and effective application development. Copyright © 2004 John Wiley & Sons, Ltd.