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Nowadays, High Performance Computing (HPC) systems commonly used in bioinformatics, such as genome sequencing, incorporate multi-processor architectures. Typically, most bioinformatics applications are multi-threaded and dominated by memory-intensive operations, which are not designed to take full advantage of these HPC capabilities. Therefore, the application end-user is responsible for optimizing...
Though an abundance of novel "data transformation" technologies have been developed (such as compression, level-of-detail, layout optimization, and indexing), there remains a notable gap in the adoption of such services by scientific applications. In response, we develop an in situ data transformation framework in the ADIOS I/O middleware with a "plug in" interface, thus greatly...
I/O bottlenecks in HPC applications are becoming a more pressing problem as compute capabilities continue to outpace I/O capabilities. While double-precision simulation data often must be stored losslessly, the loss of some of the fractional component may introduce acceptably small errors to many types of scientific analyses. Given this observation, we develop a precision level of detail (APLOD) library,...
The ability to efficiently handle massive amounts of data is necessary for the continuing development towards exascale scientific data-mining applications and database systems. Unfortunately, recent years have shown a growing gap between the size and complexity of data produced from scientific applications and the limited I/O bandwidth available on modern high-performance computing systems. Utilizing...
Efficient handling of large volumes of data is a necessity for exascale scientific applications and database systems. To address the growing imbalance between the amount of available storage and the amount of data being produced by high speed (FLOPS) processors on the system, data must be compressed to reduce the total amount of data placed on the file systems. General-purpose loss less compression...
Continuous changes in requirements of a multi-tiered project can significantly deteriorate the maintenance process. This is mainly due to incompatibility between application design and newly introduced requirements. This paper presents a potential application framework, Athamas, which provides a scalable way to agilely adapt to changing data requirements. A currently functional initiative of Athamas...
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