WILLIAM B. HURST, PH.D.321 Madison Pl

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1 WILLIAM B. HURST, PH.D.321 Madison Pl Benton, AR T Bwbhurst411@gmail.com Current Research Projects Statement of Research Interests My most recent research was focused on High Performance Computing (HPC) systems. The problem I endeavored to solve involved the difficulties facing potential and existing HPC owners. After encountering the problems of evaluating the seemingly endless combinations of hardware components and software configurations that become aggregated into an HPC system, it became clear to me that these evaluations provided a significant purchasing obstacle to any prospective buyer. While it is obvious that the goal of every potential buyer is to get the best system possible while minimizing expenses, a method for determining the optimal system for a potential buyer provides a considerable degree of confusion. Add to this confusion mounting concerns for system expandability for servicing a growing customer base and trepidation begins to flood the buyer. The question is How does a potential buyer make the most intelligent decision on their future HPC purchase? My solution was to develop a freely accessible HPC simulator which would enable a potential buyer to test the impacts from different hardware components on the performance of an HPC system. The idea must have been a good one, because today there are many other researchers working towards the creation of the perfect HPC simulator; all of us in effect racing to a better solution. While we are all still improving our different simulator versions, we have not yet reached a final solution. There are still a great many improvements that can be made. Despite the fact that there is more work to be done, my last set of HPC system vs. HPC system simulator test runs were extremely successful. Utilizing job performance data from an existing live HPC system the simulator was able to predict the performance of a non-existent HPC system to such a high degree of accuracy as to achieve results that were statistically equivalent to the live HPC system, when it did exist. Now that this has been achieved, it is possible to test the impacts of different hardware component combinations upon the performance results. The accuracy of the HPC system simulator performance predictions for a non-existent 256 CPU system can be seen in the figures below, but they are perhaps best quantified through Table I. In each of the diagrams below, one can see a single instance of the data results from the live system experiment and three instances of the simulated system results. The variations

2 2 of the simulated systems are related to job scheduling variations within the simulations. One job scheduling simulation utilized the First-In-First-Out (FIFO) protocol, a second simulation set involved the prioritization of jobs based on the numbers of CPUs requested within the job (Priority FIFO), and a third simulation data set utilized a mathematical model best described through the Kendall notation identified as M/M/s Priority FIFO. This can be described as jobs arriving according to a Markovian distribution, with each of the jobs requiring service times according to a Markovian distribution, on an HPC system having s number of servers. Fig. 1. Results: 256 CPU HPC System Comparisons (a) Number of Jobs (b) Inter-Arrival Time (c) Queuing Time (d) Processing Time (e) Service Time (f) Arrival Rate

3 3 Fig. 2. Results: 256 CPU HPC System Comparisons (Continued...) (a) Intensity (b) Utilization TABLE I SIMULATOR PREDICTIVE ACCURACY Job HPC MMs Diff Pcnt Class Live Sim Error

4 4 Among some of the improvements that yet need to be made: Processing overhead added to simulations Resource management polling period Job backfilling Additional constraints of disk, swap and memory added to job scheduler parameters list The relevance of the work is that now that the HPC simulator has been created, you like others, can use the software to re-evaluate your existing systems, to evaluate future needs, to predict the performance of an existing system that has been expanded using similar hardware components, or to test the impacts of non-existent hardware designs; for example, unique combinations of multi-core CPUs, and GPGPUs that have not yet been designed. Research Project Plans Looking beyond the list of needed improvements to the simulator mentioned above, it is worth noting that this simulator was created with a full utilization of the definition of simulation as: Simulation: the technique of representing the real world by a computer program; a simulation should imitate the internal processes and not merely the results [1] Embedded within the simulator are concepts of operating system models, ready queues, cpu processing, I/O blocking, networking between machines, switches/router processing, client classes, a HPC head node and job scheduling. It is through this mirroring of live system algorithms within the simulator that makes it possible for the application of hardware parameter specifications to the appropriate hardware component simulation. The impacts from these variations can be tested upon system performance. Prior Research Software Bug Predictions through Component Life-Cycle Analysis For my Master degree in Computer Science, I worked with developing bug predictions using component life-cycle analysis. The predictions involved identifying the life-cycles of each of the 31 primary sub-component development threads contained within a single software product. I then proved that once the life-

5 5 cycles of the product sub-components were identified, predictions about future software bug reports became significantly more accurate. The primary software product used during this research process was libsvm [2] While life-cycle analysis had been performed before on software bug predictions, it had not been applied on a sub-component level using the libsvm software package. The contributions of this project was two-fold: one benefit was the demonstration of using a new software tool to perform bug prediction; and the second benefit was the discovery of the life-cycles for the sub-components within the software product. Text Search Analysis on Web Page Repositories For approximately one month, I researched enterprise level text search methods as they are applied to web page repositories. The experience illuminated for me the difficulties found in returning relevant information to web queries; difficulties that companies like Google and Yahoo face millions of times every day. Interest for this type of activity is of concern to corporations and even countries, because of the extremely large quantities of new data generated every year through web queries, text messages, s, graphics files, audio files and data transfers. One report from 2002 estimated that it was 5 exabytes. As a results, I concluded that new methods must be found to analyze, qualify, quantify and store these new volumes of data. It seemed to me like only an HPC system would be capable of the computational cycles required to analyze the overwhelming size of raw data generated. This conclusion only reinforced my previous interest in HPC systems. Sincerely, William B. Hurst, Ph.D. REFERENCES [1] wordnetweb.princeton.edu. Definitions of simulation on the web. perl/ webwn (2011). [2] Chang, C.-C. & Lin, C.-J. LIBSVM: a Library for Support Vector Machines (2001).