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| Research lines ::: |
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| Systems Simulation |
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| Concurrent, Parallel and Distributed Systems |
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| Systems Simulation |
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In this research line, we investigate methods and techniques for the computational simulation of computer systems and the use of simulation in their analysis, with a particular focus on parallel and distributed systems.
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Our current major project is the development of iSPD, a grid/cloud simulator based on iconic modeling, whose name stands for iconic Simulator of Parallel and Distributed systems. The project aims to address modeling limitations and challenges found in commonly used simulators, such as SimgGrid, GridSim, and CloudSim. The project has received funding from FAPESP and involves most members of the GSPD research group.
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Another research direction focuses on methods for automatically generating customized simulators from behavioral characteristics specified by users. We are currently investigating this approach in the context of discrete-event simulation. The resulting simulators are intended to provide accurate models while remaining easy to use, particularly through graphical interfaces that support system modeling.
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Another tool developed within this research line is RTsim (Real-Time Simulator), which is designed for the analysis and teaching of real-time scheduling algorithms and systems through their simulation. The tool has been under continuous development for several years and currently provides graphical interfaces for scheduler generation and task-dependency modeling. It also includes a component that allows students to experiment with schedules and verify their correctness.
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| Concurrent, Parallel and Distributed Systems |
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In this research area, we investigate new approaches for executing and evaluating computations on parallel and distributed systems. The projects in this area cover a broad range of topics and systems, sharing a common focus on improving the execution, management, and evaluation of computational workloads.
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Recent work has addressed a diverse set of topics, including the use of GPUs, job allocation in cloud environments, meta-scheduling, energy-aware task scheduling, fault tolerance, workflow workload evaluation, microservice performance evaluation, and application-oriented parallel algorithms.
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