Search Results - "Griebler, Dalvan"

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  1. 1

    Micro-batch and data frequency for stream processing on multi-cores by Garcia, Adriano Marques, Griebler, Dalvan, Schepke, Claudio, Fernandes, Luiz Gustavo

    Published in The Journal of supercomputing (01-05-2023)
    “…Latency or throughput is often critical performance metrics in stream processing. Applications’ performance can fluctuate depending on the input stream. This…”
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    Journal Article
  2. 2

    The NAS Parallel Benchmarks for evaluating C++ parallel programming frameworks on shared-memory architectures by Löff, Júnior, Griebler, Dalvan, Mencagli, Gabriele, Araujo, Gabriell, Torquati, Massimo, Danelutto, Marco, Fernandes, Luiz Gustavo

    Published in Future generation computer systems (01-12-2021)
    “…The NAS Parallel Benchmarks (NPB), originally implemented mostly in Fortran, is a consolidated suite containing several benchmarks extracted from Computational…”
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  3. 3

    Performance and programmability of GrPPI for parallel stream processing on multi-cores by Garcia, Adriano Marques, Griebler, Dalvan, Schepke, Claudio, García, José Daniel, Muñoz, Javier Fernández, Fernandes, Luiz Gustavo

    Published in The Journal of supercomputing (2024)
    “…GrPPI library aims to simplify the burdening task of parallel programming. It provides a unified, abstract, and generic layer while promising minimal overhead…”
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  4. 4

    OpenMP as runtime for providing high-level stream parallelism on multi-cores by Hoffmann, Renato B., Löff, Júnior, Griebler, Dalvan, Fernandes, Luiz G.

    Published in The Journal of supercomputing (2022)
    “…OpenMP is an industry and academic standard for parallel programming. However, using it for developing parallel stream processing applications is complex and…”
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    Journal Article
  5. 5

    DSPBench: A Suite of Benchmark Applications for Distributed Data Stream Processing Systems by Bordin, Maycon Viana, Griebler, Dalvan, Mencagli, Gabriele, Geyer, Claudio F. R., Fernandes, Luiz Gustavo L.

    Published in IEEE access (2020)
    “…Systems enabling the continuous processing of large data streams have recently attracted the attention of the scientific community and industrial stakeholders…”
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  6. 6

    Simplifying and implementing service level objectives for stream parallelism by Griebler, Dalvan, Vogel, Adriano, De Sensi, Daniele, Danelutto, Marco, Fernandes, Luiz G.

    Published in The Journal of supercomputing (01-06-2020)
    “…An increasing attention has been given to provide service level objectives (SLOs) in stream processing applications due to the performance and energy…”
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  7. 7

    Towards Evaluating Proactive and Reactive Approaches on Reorganizing Human Resources in IoT-Based Smart Hospitals by Fischer, Gabriel Souto, Righi, Rodrigo da Rosa, Costa, Cristiano André da, Galante, Guilherme, Griebler, Dalvan

    Published in Sensors (Basel, Switzerland) (02-09-2019)
    “…Hospitals play an important role on ensuring a proper treatment of human health. One of the problems to be faced is the increasingly overcrowded patients care…”
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  8. 8

    Raising the Parallel Abstraction Level for Streaming Analytics Applications by Mencagli, Gabriele, Torquati, Massimo, Griebler, Dalvan, Danelutto, Marco, Fernandes, Luiz Gustavo L.

    Published in IEEE access (2019)
    “…In the stream processing domain, applications are represented by graphs of operators arbitrarily connected and filled with their business logic code. The APIs…”
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  9. 9

    Multi-Hospital Management: Combining Vital Signs IoT Data and the Elasticity Technique to Support Healthcare 4.0 by Fischer, Gabriel Souto, Ramos, Gabriel de Oliveira, Costa, Cristiano André da, Alberti, Antonio Marcos, Griebler, Dalvan, Singh, Dhananjay, Righi, Rodrigo da Rosa

    Published in IoT (01-06-2024)
    “…Smart cities can improve the quality of life of citizens by optimizing the utilization of resources. In an IoT-connected environment, people’s health can be…”
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  10. 10

    Providing high‐level self‐adaptive abstractions for stream parallelism on multicores by Vogel, Adriano, Griebler, Dalvan, Fernandes, Luiz Gustavo

    Published in Software, practice & experience (01-06-2021)
    “…Stream processing applications are common computing workloads that demand parallelism to increase their performance. As in the past, parallel programming…”
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    Journal Article
  11. 11

    GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism by Rockenbach, Dinei A., Araujo, Gabriell, Griebler, Dalvan, Fernandes, Luiz Gustavo

    Published in Computer standards and interfaces (01-03-2025)
    “…The evolution of Graphics Processing Units (GPUs) has allowed the industry to overcome long-lasting problems and challenges. Many belong to the stream…”
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  12. 12

    General-purpose data stream processing on heterogeneous architectures with WindFlow by Mencagli, Gabriele, Torquati, Massimo, Griebler, Dalvan, Fais, Alessandra, Danelutto, Marco

    “…Many emerging applications analyze data streams by running graphs of communicating tasks called operators. To develop and deploy such applications, Stream…”
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  13. 13

    Self‐adaptation on parallel stream processing: A systematic review by Vogel, Adriano, Griebler, Dalvan, Danelutto, Marco, Fernandes, Luiz Gustavo

    Published in Concurrency and computation (10-03-2022)
    “…Summary A recurrent challenge in real‐world applications is autonomous management of the executions at run‐time. In this vein, stream processing is a class of…”
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  14. 14

    Assessing Application Efficiency and Performance Portability in Single-Source Programming for Heterogeneous Parallel Systems by Ernstsson, August, Griebler, Dalvan, Kessler, Christoph

    “…We analyze the performance portability of the skeleton-based, single-source multi-backend high-level programming framework SkePU across multiple different…”
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  15. 15

    A parallel programming assessment for stream processing applications on multi-core systems by Andrade, Gabriella, Griebler, Dalvan, Santos, Rodrigo, Fernandes, Luiz Gustavo

    Published in Computer standards and interfaces (01-03-2023)
    “…Multi-core systems are any computing device nowadays and stream processing applications are becoming recurrent workloads, demanding parallelism to achieve the…”
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  16. 16

    SPBench: a framework for creating benchmarks of stream processing applications by Garcia, Adriano Marques, Griebler, Dalvan, Schepke, Claudio, Fernandes, Luiz Gustavo

    Published in Computing (01-05-2023)
    “…In a fast-changing data-driven world, real-time data processing systems are becoming ubiquitous in everyday applications. The increasing data we produce, such…”
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  17. 17

    Benchmarking parallel programming for single-board computers by Hoffmann, Renato B., Griebler, Dalvan, Righi, Rodrigo da Rosa, Fernandes, Luiz G.

    Published in Future generation computer systems (01-12-2024)
    “…Within the computing continuum, SBCs (single-board computers) are essential in the Edge and Fog, with many featuring multiple processing cores and GPU…”
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  18. 18

    NAS Parallel Benchmarks with CUDA and beyond by Araujo, Gabriell, Griebler, Dalvan, Rockenbach, Dinei A., Danelutto, Marco, Fernandes, Luiz G.

    Published in Software, practice & experience (01-01-2023)
    “…NAS Parallel Benchmarks (NPB) is a standard benchmark suite used in the evaluation of parallel hardware and software. Several research efforts from academia…”
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  19. 19

    Enhancing self-adaptation for efficient decision-making at run-time in streaming applications on multicores by Vogel, Adriano, Danelutto, Marco, Torquati, Massimo, Griebler, Dalvan, Fernandes, Luiz Gustavo

    Published in The Journal of supercomputing (01-10-2024)
    “…Parallel computing is very important to accelerate the performance of computing applications. Moreover, parallel applications are expected to continue…”
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  20. 20

    Online and transparent self-adaptation of stream parallel patterns by Vogel, Adriano, Mencagli, Gabriele, Griebler, Dalvan, Danelutto, Marco, Fernandes, Luiz Gustavo

    Published in Computing (01-05-2023)
    “…Several real-world parallel applications are becoming more dynamic and long-running, demanding online (at run-time) adaptations. Stream processing is a…”
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