| Bibtype | Inproceedings |
|---|---|
| Bibkey | Lindemann/etal/2018a |
| Author | Thomas Lindemann and Jonas Kauke and Jens Teubner |
| Title | Efficient Stream Processing of Scientific Data |
| Booktitle | Proc. of the Joint HardBD & Active '18 Workshop |
| Address | Paris, France |
| Abstract | Modern particle physics produces volumes of experimental data that challenge any data processing system. To illustrate, the trigger system of the LHCb experiment at CERN must sustain a data rate of 4 TB/s, yet maintain real-time characteristics.
In this work, we report on ELPACO, a distributed event processing platform for scientific data. Its key characteristics are excellent scalability and high resource efficiency. ELPACO inherits its favorable scalability from Apache Storm, which we used as a basis for our platform. For resource efficiency, we tailored ELPACO to Eriador, a parallel, ARM-based hardware substrate with excellent energy/performance characteristics. With experiments on realistic data, we confirm a linear scalability (throughput vs. core count) and a 2.5× improvement in energy efficiency compared to existing solutions. |
| Month | april |
| Year | 2018 |
| Projekt | SFB876-C5 |
| Bibtex | Here you can get this literature entry as BibTeX format. |
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