Michelle R. Hribar

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Shortest path algorithms are required by several transportation applications; furthermore, the shortest path computation in these applications can account for a large percentage of the total execution time. Since these algorithms are very computationally intense, parallel processing can provide the compute power and memory required to solve large problems(More)
In order to be practically useful, computer applications for patients with cancer must be easily usable by people with limited computer literacy and impaired vision or dexterity. We describe the usability development process for an application that collects quality of life and symptom information from patients with cancer. Usability testing consisted of(More)
Computer-based, patient-reported symptom survey tools have been described for patients undergoing chemotherapy. We hypothesized that patients undergoing radiotherapy might also benefit, so we developed a computer application to acquire symptom ratings from patients and generate summaries for use at point of care office visits and conducted a randomized,(More)
Shortest path computation is required by a large number of applications such as VLSI, transportation and communication networks. These applications, which often use parallel processing, require an eecient parallel shortest path algorithm. The experimental work related to parallel shortest path algorithms has focused on the development of eecient, parallel(More)
Domain decomposition is an important step for parallel scienti c applications, in particular nite element analyses. A good decomposition will minimize both the time spent on local computation and on interprocessor communication. It is often the case that these two goals cannot be satis ed simultaneously. In this paper, we use analytical and experimental(More)
Shortest path computation is required by a large number of applications such as VLSI, transportation and communication networks. These applications, which are often very complex and have sparse networks, generally use parallel labeling shortest path algorithms. Such algorithms, when implemented on a distributed memory machine, require termination detection(More)
Shortest path computation is required by a large number of applications such as VLSI, transportation and communication networks. These applications, which are often very complex and have sparse networks, generally use parallel labeling shortest path algorithms. Such algorithms, when implemented on a distributed memory machine, require termination detection(More)
Porting applications to new high performance parallel and distributed computing platforms is a challenging task. Since writing parallel code by hand is time consuming and costly, porting codes would ideally be automated by using some parallelization tools and compilers. In this paper, we compare the performance of three parallelization tools and compilers(More)
Traac equilibrium analyses are generally very large and computationally intensive. Parallel processing provides the memory and computational power needed to solve the equilibrium problems in a reasonable amount of time. Because the shortest path solution is the major component of these equilibrium algorithms, we focus on developing an eecient parallel(More)