34 research outputs found
Le cave della Lessinia (la pietra di Prun)
No full textNel territorio della Lessinia lo sfruttamento dei materiali lapidei risale alla protostoria. L'estrazione della pietra di Prun (lastame) inizia con l'età del ferro, per la costruzione di villaggi fortificati e case di tipo "retico". La successione di strati formanti il lastame appartiene alla Scaglia Rossa di età Cretacica superiore
Strike-slip contractional stepovers in the Southern Alps (northeastern Italy)
No full textStrike-slip pop-ups are seldom recognized because they are sites of rapid uplift and erosion. In addition, they can easily be confused with shortening structures of different age. In the Neogene central-eastern Southern Alps, the western termination of the ENE-trending Valsugana thrust is located at the interference with the suborthogonal Calisio Line, which is an inverted Permian normal fault. Just west of the Calisio Line the Mt. Cornetto di Folgaria (MCF) structural and topographic high is a large-scale pop-up localised at the restraining stepover between the sinistral Calisio and Schio-Vicenza strike-slip faults, which trend at high angle to the thrust belt. The MCF pop-up developed in post-Tortonian times, when the kinematics of these faults changed from dextral to sinistral. At a smaller scale, strike-slip restraining and releasing stepovers of pre-existing steep fault segments show that these inherited faults are kinematically linked and constitute an important mechanical anisotropy responsible for strain partitioning into strike-slip and dip-slip displacements. The analysis of the MCF pop-up and related minor structures suggests that in fold-and-thrust-belts affected by strike-slip faults at high angle to the belt axis, contractional structures related to strike-slip restraining bends and stepovers may be more common than what is usually thought
Recenti contributi alla conoscenza dell'idrostruttura del Bacino Termale Euganeo (Padova)
No full text
SEDEA: A sensible approach to account DRAM energy in multicore systems
No full textAs the energy cost in todays computing systems keeps increasing, measuring the energy becomes crucial in many scenarios. For instance, due to the fact that the operational cost of datacenters largely depends on the energy consumed by the applications executed, end users should be charged for the energy consumed, which requires a fair and consistent energy measuring approach. However, the use of multicore system complicates per-task energy measurement as the increased Thread Level Parallelism (TLP) allows several tasks to run simultaneously sharing resources. Therefore, the energy usage of each task is hard to determine due to interleaved activities and mutual interferences. To this end, Per-Task Energy Metering (PTEM) has been proposed to measure the actual energy of each task based on their resource utilization in a workload. However, the measured energy depends on the interferences from co-running tasks sharing the resources, and thus fails to provide the consistency across executions. Therefore, Sensible Energy Accounting (SEA) has been proposed to deliver an abstraction of the energy consumption based on a particular allocation of resources to a task.In this work we provide a realization of SEA for the DRAM memory system, SEDEA, where we account a task for the DRAM energy it would have consumed when running in isolation with a fraction of the on-chip shared cache. SEDEA is a mechanism to sensibly account for the DRAM energy of a task based on predicting its memory behavior. Our results show that SEDEA provides accurate estimates, yet with low-cost, beating existing per-task energy models, which do not target accounting energy in multicore system. We also provide a use case showing that SEDEA can be used to guide shared cache and memory bank partition schemes to save energy.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253) and National Key R&D Program of China under No.2016YFB1000204, by the European
HiPEAC Network of Excellence, by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P), by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the IBM-BSC Deep Learning Center initiative.
Also by the major scientific and technological project of Guangdong province (2014B010115003), and NSFC under
grant no 61702495, 61672511. M. Moret´o has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship number JCI-
2012-15047. J. Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717Peer ReviewedPostprint (author's final draft
SEDEA: A sensible approach to account DRAM energy in multicore systems
No full textAs the energy cost in todays computing systems keeps increasing, measuring the energy becomes crucial in many scenarios. For instance, due to the fact that the operational cost of datacenters largely depends on the energy consumed by the applications executed, end users should be charged for the energy consumed, which requires a fair and consistent energy measuring approach. However, the use of multicore system complicates per-task energy measurement as the increased Thread Level Parallelism (TLP) allows several tasks to run simultaneously sharing resources. Therefore, the energy usage of each task is hard to determine due to interleaved activities and mutual interferences. To this end, Per-Task Energy Metering (PTEM) has been proposed to measure the actual energy of each task based on their resource utilization in a workload. However, the measured energy depends on the interferences from co-running tasks sharing the resources, and thus fails to provide the consistency across executions. Therefore, Sensible Energy Accounting (SEA) has been proposed to deliver an abstraction of the energy consumption based on a particular allocation of resources to a task.In this work we provide a realization of SEA for the DRAM memory system, SEDEA, where we account a task for the DRAM energy it would have consumed when running in isolation with a fraction of the on-chip shared cache. SEDEA is a mechanism to sensibly account for the DRAM energy of a task based on predicting its memory behavior. Our results show that SEDEA provides accurate estimates, yet with low-cost, beating existing per-task energy models, which do not target accounting energy in multicore system. We also provide a use case showing that SEDEA can be used to guide shared cache and memory bank partition schemes to save energy.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253) and National Key R&D Program of China under No.2016YFB1000204, by the European
HiPEAC Network of Excellence, by the Spanish Ministry of Science and Innovation (contracts TIN2015-65316-P), by Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the IBM-BSC Deep Learning Center initiative.
Also by the major scientific and technological project of Guangdong province (2014B010115003), and NSFC under
grant no 61702495, 61672511. M. Moret´o has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship number JCI-
2012-15047. J. Abella has been partially supported by the Ministry of Economy and Competitiveness under Ramon y Cajal postdoctoral fellowship number RYC-2013-14717Peer Reviewe
Applicazioni del "gamma ray log" eseguito in un pozzo a carotaggio continuo nell'area termale euganea (Padova)
No full textSeismic reflection test within the euganean thermal basin (Abano Terme, Italy)
No full textFirenze, Abstrac
Note illustrative della Carta Geologica d'Italia alla scala 1:50.000, foglio 147 Padova Sud.
No full text
