1,720,972 research outputs found
On-line thermal emulation: How to speed-up your thermal controller design
No full textDynamic thermal management (DTM) is a key technology for future many-core systems. Indeed systems, as both server-class and embedded chip multiprocessors are thermally constrained. DTM design requires consideration for the chain of interactions between HW operating points, workload phases, power consumption, die temperature, HW monitor infrastructure, control policy. Hugely different time scales are involved, from microseconds to hours. Simulating performance of DTM solutions for a many-core system in a reasonable time is an open problem. In this paper we present an on-line thermal emulation framework based on the Intel Single-Chip-Cloud computer. In our framework a subset of the cores are used to on-line emulate the evolution of a generic thermal floorplan based on the real workload usage and operating point selected by the rest of the cores which emulate the target managed system. This enables design space exploration of dynamic thermal management solutions at the speed of real workload execution
SCC thermal model identification via advanced bias-compensated least-squares
No full textCompact thermal models and modeling strategies are today a cornerstone for advanced power management to counteract the emerging thermal crisis for many-core systems-on-chip. System identification techniques allow to extract models directly from the target device thermal response. Unfortunately, standard Least Squares techniques cannot effectively cope with both model approximation and measurement noise typical of real
systems. In this work, we present a novel distributed identification strategy capable of coping with real-life temperature sensor noise and effectively extracting a set of low-order predictive Thermal models for the tiles of Intel’s Single-chip-Cloud-Computer (SCC) many-core prototype
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Data set for anomaly detection on a HPC system
No full text<p>This data set contains the data collected on the DAVIDE HPC system (CINECA & E4 & University of Bologna, Bologna, Italy) in the period March-May 2018.</p>
<p>The data set has been used to train a autoencoder-based model to automatically detect anomalies in a semi-supervised fashion, on a real HPC system.</p>
<p>This work is described in:</p>
<p>1) "Anomaly Detection using Autoencoders in High Performance Computing Systems", <a href="https://arxiv.org/search/cs?searchtype=author&query=Borghesi%2C+A">Andrea Borghesi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bartolini%2C+A">Andrea Bartolini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lombardi%2C+M">Michele Lombardi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Milano%2C+M">Michela Milano</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Benini%2C+L">Luca Benini,</a> IAAI19 (proceedings in process) -- https://arxiv.org/abs/1902.08447</p>
<p>2) "Online Anomaly Detection in HPC Systems", <a href="https://arxiv.org/search/cs?searchtype=author&query=Borghesi%2C+A">Andrea Borghesi</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Libri%2C+A">Antonio Libri</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Benini%2C+L">Luca Benini</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Bartolini%2C+A">Andrea Bartolini, </a>AICAS19 (proceedings in process) -- https://arxiv.org/abs/1811.05269</p>
<p>See the git repository for usage examples & details --> https://github.com/AndreaBorghesi/anomaly_detection_HPC</p>
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