Alexandre DA SILVA VEITH

Alexandre DA SILVA VEITH

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Pages

Posts

Future Blog Post

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Blog Post number 4

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Blog Post number 3

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Blog Post number 2

less than 1 minute read

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Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Collaborative computing of parallel applications in P2P environments

Published in NEA 2015, 2015

Abstract

This book addresses the issue of “How to explore collaborative computing in P2P Grids to run BSP applications efficiently?”. To answer this question came the BSPonP2P model, which creates an environment with approaches based on the structured and unstructured models from the P2P networks. The combination of these models aims to streamline the management of communication and data on the network. Another difference of the proposed model is the use of the parallel programming model Bulk Synchronous Parallel (BSP), which creates an environment for executing processes, validating dependencies and improving communication between them. We use metrics required for the processes as memory, computing, communication, and also information from the infrastructure to establish a unique performance metric called PM. This metric is evaluated periodically to define migrations according to the launched superstep barriers. The results show that BSPonP2P uses the computational idleness, and brings performance gains to the executions.

Recommended citation: da Silva Veith, Alexandre; Righi, Rodrigo. R

talks

teaching

CR05: Advanced Topics in Scalable Data Management

Undergraduate course - Master 2, ENS-Lyon, Computer Science, 2018

General Presentation

Big data is becoming a bigger deal every day. Every day 2.5 Quintillion bytes of data are created. In 2016, big data will affect everyone. These lectures focus on a large point of view of the current data management. In charged of Lecture 8 (Data Stream Processing) and lecture 9 (Practical Session of Data Stream Processing).