Grupo de Modelagem de Aplicações Paralelas

@inproceedings{PIEPER:SBLP:19,
title = {Structured Stream Parallelism for Rust},
author = {Ricardo Pieper and Dalvan Griebler and Luiz G. Fernandes},
doi = {10.1145/3355378.3355384},
year = {2019},
date = {2019-10-01},
booktitle = {23st Brazilian Symposium on Programming Languages (SBLP)},
pages = {8},
publisher = {ACM},
address = {Salvador, Brazil},
series = {SBLP'19},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{VOGEL:PARCO:19,
title = {Seamless Parallelism Management for Multi-core Stream Processing},
author = {Adriano Vogel and Dalvan Griebler and Marco Danelutto and Luiz Gustavo Fernandes},
year = {2019},
date = {2019-09-01},
booktitle = {Parallel Computing is Everywhere, Proceedings of the International Conference on Parallel Computing (ParCo)},
pages = {10},
publisher = {IOS Press},
address = {Prague, Czech Republic},
series = {ParCo'19},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{ROCKENBACH:PARCO:19,
title = {High-Level Stream Parallelism Abstractions with SPar Targeting GPUs},
author = {Dinei A. Rockenbach and Dalvan Griebler and Marco Danelutto and Luiz Gustavo Fernandes},
year = {2019},
date = {2019-09-01},
booktitle = {Parallel Computing is Everywhere, Proceedings of the International Conference on Parallel Computing (ParCo)},
pages = {10},
publisher = {IOS Press},
address = {Prague, Czech Republic},
series = {ParCo'19},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{VOGEL:adaptive-overhead:AutoDaSP:19,
title = {Minimizing Self-Adaptation Overhead in Parallel Stream Processing for Multi-Cores},
author = {Adriano Vogel and Dalvan Griebler and Marco Danelutto and Luiz Gustavo Fernandes},
year = {2019},
date = {2019-08-01},
booktitle = {Euro-Par 2019: Parallel Processing Workshops},
pages = {12},
publisher = {Springer},
address = {Göttingen, Germany},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@article{GRIEBLER:JS:19,
title = {Simplifying and implementing service level objectives for stream parallelism},
author = {Dalvan Griebler and Adriano Vogel and Daniele De Sensi and Marco Danelutto and Luiz Gustavo Fernandes},
url = {https://doi.org/10.1007/s11227-019-02914-6},
doi = {10.1007/s11227-019-02914-6},
issn = {0920-8542},
year = {2019},
date = {2019-06-01},
journal = {Journal of Supercomputing},
pages = {1-26},
publisher = {Springer},
abstract = {An increasing attention has been given to provide service level objectives (SLOs) in stream processing applications due to the performance and energy requirements, and because of the need to impose limits in terms of resource usage while improving the system utilization. Since the current and next-generation computing systems are intrinsically offering parallel architectures, the software has to naturally exploit the architecture parallelism. Implement and meet SLOs on existing applications is not a trivial task for application programmers, since the software development process, besides the parallelism exploitation, requires the implementation of autonomic algorithms or strategies. This is a system-oriented programming approach and requires the management of multiple knobs and sensors (e.g., the number of threads to use, the clock frequency of the cores, etc.) so that the system can self-adapt at runtime. In this work, we introduce a new and simpler way to define SLO in the application’s source code, by abstracting from the programmer all the details relative to self-adaptive system implementation. The application programmer specifies which parts of the code to parallelize and the related SLOs that should be enforced. To reach this goal, source-to-source code transformation rules are implemented in our compiler, which automatically generates self-adaptive strategies to enforce, at runtime, the user-expressed objectives. The experiments highlighted promising results with simpler, effective, and efficient SLO implementations for real-world applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}