Ruth A. Aydt

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Developers of application codes for massively parallel computer systems face daunting performance tuning and optimization problems that must be solved if massively parallel systems are to fullll their promise. Recording and analyzing the dynamics of application program, system software, and hardware interactions is the key to understanding and the(More)
TeraGrid is a national-scale computational science facility supported through a partnership among thirteen institutions, with funding from the US National Science Foundation [1]. Initially created through a Major Research Equipment Facilities Construction (MREFC [2]) award in 2001, the TeraGrid facility began providing production computing, storage,(More)
This paper describes the program execution framework being developed by the Grid Application Development Software (GrADS) Project. The goal of this framework is to provide good resource allocation for Grid applications and to support adaptive reallocation if performance degrades because of changes in the availability of Grid resources. At the heart of this(More)
Rapid increases in computing and communication performance are exacerbating the long-standing problem of performance-limited input/output. Indeed, for many otherwise scalable parallel applications. input/output is emerging as a major performance bottleneck. The design of scalable input/output systems depends critically on the input/output requirements and(More)
As massively parallel, distributed memory systems replace traditional vector supercomputers, e ective application program optimization and system resource management become more than research curiosities | they are crucial to achieving substantial fractions of peak performance for scienti c application codes. By recording dynamic activity, either at the(More)
We present an auto-tuning system for optimizing I/O performance of HDF5 applications and demonstrate its value across platforms, applications, and at scale. The system uses a genetic algorithm to search a large space of tunable parameters and to identify effective settings at all layers of the parallel I/O stack. The parameter settings are applied(More)
The Internet and the growing availability of inexpensive yet powerful commodity hardware has changed our view of computing. Computational grids have emerged as a new paradigm for high-performance computing. Grids consist of geographically distributed computational resources, such as supercomputers, clusters of workstations, scientific instruments, storage(More)
As parallel systems expand in size and complexity, the absence of performance tools for these parallel systems exacerbates the already diicult problems of application program and system software performance tuning. Moreover, given the pace of technological change, we can no longer aaord to develop ad hoc, one-of-a-kind performance instrumentation software;(More)
The modest I/O configurations and file system limitations of many current high-performance systems preclude solution of problems with large I/O needs. I/O hardware and file system parallelism is the key to achieve high performance. We analyze the I/O behavior of several versions of two scientific applicationson the Intel Paragon XP/S. The versions involve(More)
Next Generation Sequencing technologies are limited by the lack of standard bioinformatics infrastructures that can reduce data storage, increase data processing performance, and integrate diverse information. HDF technologies address these requirements and have a long history of use in data-intensive science communities. They include general data file(More)