Akintayo Holder

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n this paper we illustrate scalable parallel performance for the TimeWarp synchronization protocol on the L and P variants of the IBM BlueGene supercomputer. Scalable Time Warp performance for models that communicate a large percentage of the event population over the network has not been shown on more than a handful of processors. We present our design for(More)
The aim of our work is to investigate the performance and overall scalability of an optimistic discrete-event simulator on a Blue Gene/L supercomputer. We find that strong scaling out to 16,384 processors is possible. In terms of event-rate, we observed 853 million events per second on 16,384 processors for the PHOLD benchmark. This is 1.5 times faster than(More)
Recent advances in healthcare and bioscience technologies and proliferation of portable medical devices have produce massive amount of multimodal data, the need for parallel processing is apparent for mining these data sets, which can range anywhere from tens of gigabytes, to terabytes or even petabytes. AALIM (Advanced Analytics for Information Management)(More)
This paper focuses on parallelization of the classic static timing analysis (STA) algorithm for verifying timing characteristics of digital integrated circuits. Given ever-increasing circuit complexities, including the need to analyze circuits with billions of transistors, across potentially thousands of process corners, with accuracy tolerances down to the(More)
Methods Noninvasive monitoring data from 8 weeks of admissions in a 24-bed step-down unit (heart rate [HR], respiratory rate (RR; bioimpedance), oscillometric blood pressure (BP), peripheral oximetry (SpO2)) were recorded at 1/20Hz. VS deviation beyond stability thresholds (HR 40-140, RR 8-36, systolic BP 80-200, diastolic BP < 110, SpO2>85%) and persisting(More)
Methods Noninvasive VS data including ECG-derived heart rate (HR), respiratory rate (RR), systolic and diastolic blood pressure (BP), and pulse oxygen saturation (SpO2) is monitored to issue alerts whenever VS exceed any of preset stability thresholds [1]. Two experts independently annotated 40 of such alerts only using informative lowdimensional(More)
Parametric linear programming is the study of how optimal properties depend on data parametrizations. The study is nearly as old as the field of linear programming itself, and it is important since it highlights how a problem changes as what is often estimated data varies. We present what is a modern perspective on the classical analysis of the objective(More)
Recently, Time Warp has shown that it achieves good strong scaling to hundreds of thousands of processors on modern supercomputer systems. These results were achieved on the Cray and IBM Blue Gene supercomputing platforms. In this paper, we investigate the ROSS Time Warp cache memory performance on (i) a commodity shared-memory desktop system based on the(More)
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