{"id":837,"date":"2023-08-12T22:08:54","date_gmt":"2023-08-12T22:08:54","guid":{"rendered":"https:\/\/cloud.ic.uff.br\/?page_id=837"},"modified":"2023-08-17T10:50:52","modified_gmt":"2023-08-17T10:50:52","slug":"2nd-wcloud-hpc-online","status":"publish","type":"page","link":"https:\/\/cloud.ic.uff.br\/index.php\/2nd-wcloud-hpc-online\/","title":{"rendered":"2nd WCloud-HPC (Online)"},"content":{"rendered":"\n
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Come join our 2nd Virtual Cloud and HPC Workshop (WCloud-HPC)!
Registration link: click here!<\/a><\/p>\n\n\n\n

The 2nd WCloud-HPC is part of the 2021 Winter School of the Graduate Program in Computing (PPGC\/UFF).<\/p>\n\n\n\n

The PPGC\/UFF Winter School’s main objective is to offer courses and tutorials on technologies, tools, methods or processes that can contribute to the development of master’s and doctoral research in the various areas of concentration. In addition to the Research Methodology in Computing course, which presents basic notions of methodologies applied to scientific research in computing, together with support tools, tutorials and short courses are offered, which address complementary topics, and a cycle of seminars that presents research topics in Computing.<\/p>\n\n\n\n

The event will follow Brasilia time (GMT -3) and will feature the following activities:<\/p>\n\n\n\n

Schedule of activities for the first day (09\/16\/2021)<\/h2>\n\n\n\n
Time<\/th>Activity<\/th><\/tr><\/thead>
13:00<\/td>Opening<\/td><\/tr>
13:10<\/td>
Lecture: Efficient Data Management on a Cloud with Geo-Distributed Data Centers (Claude Tadonki<\/span>)<\/summary>

Abstract: Cloud computing has emerged as a flexible support for high-performance computing activities. There are several reasons or arguments for choosing this paradigm that mainly come from the standpoint of costs and technical safety. However, in any case, the main concern in high-performance computing is the runtime efficiency, which includes both the efficiency of the tasks and that of the corresponding data accesses. The latter is critical in the context of geographically distributed data centers because they are typically located in different places far from each other, which might imply a heavy network activity to have the data available at the right location whenever they are needed by the running tasks. One of the advantages of Cloud computing from the user standpoint is that, through the virtualization, explicit scheduling details are seamlessly managed on the provider\u2019s side. This is also the case of data management, which includes physical storage strategies and explicit migrations. In order to avoid the severe penalty of an inadequate default data management mechanism in the context of geo-distributed centers, it is worth considering a more skillful organization. We first propose an efficient data placement strategy by considering the characteristics of the tasks and their allocation onto the data centers. Then, we suggest a dynamic procedure for data provisioning using explicit redundancy and efficient choice of the providers. This talk will present the context and the problem, followed by our solutions and related thoughts.<\/p><\/details><\/em>Available at: https:\/\/youtu.be\/ZHt4__nog20<\/a><\/td><\/tr>

14:00<\/td>Coffee Break<\/td><\/tr>
14:30<\/td>Postdoctoral and Postgraduate Work Presentation Session

– Understanding the I\/O bottlenecks of an HPC system<\/em> (Luan Teylo<\/span>)
– Towards Optimizing Computational Costs of Federated Learning in Clouds<\/em> (Rafaela Brum<\/span>)
– Fluid Computing<\/em> (Rui Rodrigues)
– Diff Sequences Spark: SARS-CoV-2 Sequences Comparison on Amazon EC2 Cloud<\/em> (Alan L. Nunes<\/span>)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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Schedule of activities for the second day (09\/17\/2021)<\/h2>\n\n\n\n
Time<\/th>Activity<\/th><\/tr><\/thead>
12:00<\/td>
Lecture: Towards Next-Generation Stream Processing Systems (Gabriele Mencagli)<\/summary>

Abstract: Data Stream Processing is an emerging computing paradigm characterized by the continuous analysis of data streams. Several application domains are of special interest for stream processing, such as financial trading, sensor networks, environmenal monitoring, network analysis and many others. Modern Stream Processing Systems are designed to exploit at best scale-out environments such as a Cloud, where horizontal scalability is addressed by spreading the applications in multiple nodes. However, there is the urgent need to target different computing environments like scale-up servers and machines equipped with co-processors (e.g., GPUs and FPGAs), both in the form of traditional hosts as well as resource-constrained edge and IoT embedded devices. This talk will try to explain the most promising research perspectives in this stream processing evolution, with a special focus on the ongoing research conducted for this purpose at the University of Pisa.<\/p><\/details><\/em>Available at: https:\/\/youtu.be\/PvqUTseL6PI<\/a><\/td><\/tr>

13:00<\/td>Break<\/td><\/tr>
14:00<\/td>Postgraduate and Scientific Initiation Work Presentation Session

– Resource Elasticity in Clouds<\/em> (Daniel Sodr\u00e9 and Jos\u00e9 Victor Silva)
– Multiple Alignment of Genetic Sequences<\/em> (Mario Jo\u00e3o Junior)
– Moving HPC Workloads to the Cloud: DNA Sequence Comparison Case<\/em> (Diego Soares)<\/td><\/tr><\/tbody><\/table><\/figure>\n