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Full-Text Articles in Computer Engineering
Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain
Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain
All Computer Science and Engineering Research
The streaming model is a popular model for writing high-throughput parallel applications. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In this report, we consider the problem of mapping streaming pipelines — streaming applications where the graph is a linear chain — in order to maximize throughput. In a parallel setting, subsets of stages, called components can be mapped onto different computing resources. The through-put of an application is determined by the throughput of the slowest component. Therefore, if some stage is much slower than others, then it may …
Automated Color Calibration Of Display Devices, Andrew Shulman
Automated Color Calibration Of Display Devices, Andrew Shulman
All Computer Science and Engineering Research
If you compare two identical images on two different monitors, they will likely appear different. Every display device is supposed to adhere to a particular set of standards regulating the color and intensity of the image it outputs. However, in practice, very few do. Color calibration is the practice of modifying the signal path such that the colors produced more closely match reference standards. This is essential for graphics professionals who are mastering original content. They must ensure that the source material appears correct when viewed on a reference monitor. When viewed on a consumer panel, however, some error will …
Ewa Model With Recency Effect And Limited Memory, Hang Xie
Ewa Model With Recency Effect And Limited Memory, Hang Xie
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Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings.
Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.
Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.
All Computer Science and Engineering Research
Upsampling is required prior to the summation step in most receive digital beamforming implementations to produce an accurate summed RF line or vector. This is true in both annular and linear array systems where receive echos are digitized first and then time delayed in the digital domain to achieve proper signal alignment. The efficient, parallel, real-time upsampling circuit presented here produces M upsampled values per ADC clock, where M is the desired upsampling factor. A circuit implementation that upsamples by a factor of M=4 is presented as an example of the more general technique.
Kernel Density Metric Learning, Yujie He, Wenlin Chen, Yixin Chen
Kernel Density Metric Learning, Yujie He, Wenlin Chen, Yixin Chen
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This paper introduces a supervised metric learning algorithm, called kernel density metric learning (KDML), which is easy to use and provides nonlinear, probability-based distance measures. KDML constructs a direct nonlinear mapping from the original input space into a feature space based on kernel density estimation. The nonlinear mapping in KDML embodies established distance measures between probability density functions, and leads to correct classification on datasets for which linear metric learning methods would fail. Existing metric learning algorithms, such as large margin nearest neighbors (LMNN), can then be applied to the KDML features to learn a Mahalanobis distance. We also propose …
Parallel Real-Time Scheduling Of Dags, Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, Christopher Gill
Parallel Real-Time Scheduling Of Dags, Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, Christopher Gill
All Computer Science and Engineering Research
Recently, multi-core processors have become mainstream in processor design. To take full advantage of multi-core processing, computation-intensive real-time systems must exploit intra-task parallelism. In this paper, we address the open problem of real-time scheduling for a general model of deterministic parallel tasks, where each task is represented as a directed acyclic graph (DAG) with nodes having arbitrary execution requirements. We prove processor-speed augmentation bounds for both preemptive and non-preemptive real-time scheduling for general DAG tasks on multi-core processors. We first decompose each DAG into sequential tasks with their own release times and deadlines. Then we prove that these decomposed tasks …
Simple Analytic Performance Models For Streaming Data Applications Deployed On Diverse Architectures, Jonathan C. Beard, Roger D. Chamberlain, Mark A. Franklin
Simple Analytic Performance Models For Streaming Data Applications Deployed On Diverse Architectures, Jonathan C. Beard, Roger D. Chamberlain, Mark A. Franklin
All Computer Science and Engineering Research
Modern hardware is inherently heterogeneous. With heterogeneity comes multiple abstraction layers that hide underlying complex systems. While hidden, this complexity makes quantitative performance modeling a difficult task. Designers of high-performance streaming applications for heterogeneous systems must contend with unpredictable and often non-generalizable models to predict performance of a particular application and hardware mapping. This paper outlines a computationally simple approach that can be used to model the overall throughput and buffering needs of a streaming application on heterogeneous hardware. The model presented is based upon a hybrid maximum flow and decomposed discrete queueing model. The utility of the model is …
Real-Time Multi-Core Virtual Machine Scheduling In Xen, Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, Insup Lee
Real-Time Multi-Core Virtual Machine Scheduling In Xen, Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, Insup Lee
All Computer Science and Engineering Research
Recent years have witnessed two major trends in the development of complex real-time systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multicore processors are increasingly being used in real-time systems. The integration of real-time systems as virtual machines (VMs) atop common multicore platforms raises significant new research challenges in meeting the real-time performance requirements of multiple systems.
Scanner: An Efficient And Accurate Trimming Tool For Illumina Next Generation Sequencing Reads, Xiang Zhou
Scanner: An Efficient And Accurate Trimming Tool For Illumina Next Generation Sequencing Reads, Xiang Zhou
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Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an exact match of the 3’ adapter sequence. In this report, …
Self-Adapting Mac Layer For Wireless Sensor Networks, Mo Sha, Meng Xu, Chenyang Lu, Linh T.X. Phan, Tae-Suk Kim, Taerim Park
Self-Adapting Mac Layer For Wireless Sensor Networks, Mo Sha, Meng Xu, Chenyang Lu, Linh T.X. Phan, Tae-Suk Kim, Taerim Park
All Computer Science and Engineering Research
The integration of wireless sensors with mobile phones is gaining momentum as an enabling platform for numerous emerging applications. These mobile systems face dynamic environments where both application requirements and ambient wireless conditions change frequently. Despite the existence of many MAC protocols however, none can provide optimal performance along multiple dimensions, in particular when the conditions are frequently changing. Instead of pursuing a one-MAC-fit all approach we present a Self-Adapting MAC Layer (SAML) comprising (1) a Reconfigurable MAC Architecture (RMA) that can switch to different MAC protocols at run time and (2) a learning-based MAC Selection Engine that selects the …