Publications
============

.. _Publications:

.. contents:: Table of Contents

This page lists the main published papers that used SPBench.

How To Cite
~~~~~~~~~~~

Use the following paper to cite SPBench:

- GARCIA, A. M.; GRIEBLER, D. J.; SCHEPKE, C.; FERNANDES, L. G. "SPBench: A Framework for Creating Benchmarks of Stream Processing Applications". COMPUTING, v. 1, p. 1, 2021, doi: 10.1007/s00607-021-01025-6. [`link <https://doi.org/10.1007/s00607-021-01025-6>`_]

.. code-block:: latex

    @article{GARCIA:Computing:22,
        title = {SPBench: a framework for creating benchmarks of stream processing applications},
        author = {Adriano Marques Garcia and Dalvan Griebler and Claudio Schepke and Luiz Gustavo Fernandes},
        url = {https://doi.org/10.1007/s00607-021-01025-6},
        doi = {10.1007/s00607-021-01025-6},
        year = {2022},
        date = {2022-01-01},
        journal = {Computing},
        volume = {In press},
        number = {In press},
        pages = {1-23},
        publisher = {Springer},
        abstract = {In a fast-changing data-driven world, real-time data processing systems are becoming ubiquitous in everyday applications. The increasing data we produce, such as audio, video, image, and, text are demanding quickly and efficiently computation. Stream Parallelism allows accelerating this computation for real-time processing. But it is still a challenging task and most reserved for experts. In this paper, we present SPBench, a framework for benchmarking stream processing applications. It aims to support users with a set of real-world stream processing applications, which are made accessible through an Application Programming Interface (API) and executable via Command Line Interface (CLI) to create custom benchmarks. We tested SPBench by implementing parallel benchmarks with Intel Threading Building Blocks (TBB), FastFlow, and SPar. This evaluation provided useful insights and revealed the feasibility of the proposed framework in terms of usage, customization, and performance analysis. SPBench demonstrated to be a high-level, reusable, extensible, and easy of use abstraction to build parallel stream processing benchmarks on multi-core architectures.},
        keywords = {},
        pubstate = {published},
        tppubtype = {article}
    }

Other papers using SPBench
~~~~~~~~~~~~~~~~~~~~~~~~~~

- GARCIA, A. M.; GRIEBLER, D. J.; SCHEPKE, C.; FERNANDES, L. G. "Evaluating Micro-batch and Data Frequency for Stream Processing Applications on Multi-cores". In: 2022 30th Euromicro International Conference on Parallel, Distributed and NetworkBased Processing (PDP), 2022, Valladolid. 2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2022. p. 10-17, doi: 10.1109/PDP55904.2022.00011. [`link <https://doi.org/10.1109/PDP55904.2022.00011>`_]

- GARCIA, A. M.; GRIEBLER, D. J.; SCHEPKE, C.; FERNANDES, L. G. "Introducing a Stream Processing Framework for Assessing Parallel Programming Interfaces", 2021 29th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 2021, pp. 84-88, doi: 10.1109/PDP52278.2021.00021. [`link <https://doi.org/10.1109/PDP52278.2021.00021>`_]
