ABSTRACT
High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments.
ABSTRACT
Distinguishing ventricular extrasystoles from normal heartbeats is crucial to cardiac arrhythmia analysis. This paper proposes novel morphological descriptors, the major portrait partition area (MPPA) and point distribution percentage (PDP), which are extracted from the reconstructed phase space of the QRS complex. These measures can be linked to QRS width and prolonged ventricular contraction, and offer several advantages over traditional characterization of the QRS structure: it does not require QRS boundary detection, is robust under R-peak misalignment, and including some information from nearby points. The first four principal components of MPPA variables and PDPs in the first and the third quadrants of the phase space diagram were used as inputs of neural networks. The performance of networks in distinguishing premature ventricular contraction events from normal heartbeats were evaluated under a series of 50 cross-validations based on the electrocardiogram data taken from the MIT/BIH arrhythmia database. The sensitivity and specificity obtained using the aforementioned MPPA principal components and PDPs as inputs were similar to those obtained using wavelet features and Hermite coefficients. However, the phase space information performed better in situations of noise contaminations and waveform deformations.
Subject(s)
Algorithms , Diagnosis, Computer-Assisted/methods , Electrocardiography/methods , Heart Rate , Pattern Recognition, Automated/methods , Ventricular Premature Complexes/diagnosis , Ventricular Premature Complexes/physiopathology , Humans , Neural Networks, Computer , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-AssistedABSTRACT
Algorithm visualization is a unique research topic that integrates engineering skills such as computer graphics, system programming, database management, computer networks, etc., to facilitate algorithmic researchers in testing their ideas, demonstrating new findings, and teaching algorithm design in the classroom. Within the broad applications of algorithm visualization, there still remain performance issues that deserve further research, e.g., system portability, collaboration capability, and animation effect in 3D environments. Using modern technologies of Java programming, we develop an algorithm visualization and debugging system, dubbed GeoBuilder, for geometric computing. The GeoBuilder system features Java's promising portability, engagement of collaboration in algorithm development, and automatic camera positioning for tracking 3D geometric objects. In this paper, we describe the design of the GeoBuilder system and demonstrate its applications.
