Tentacle performance ******************** The performance of Tentacle has been evaluated on its scaling characteristics when running in a distributed enviroment, as well as the quantification accuracy of the abundance estimation features. All evaluations and tests are described in the article (see :ref:`citing`). .. _Scaling performance: Scaling performance =================== Tentacle scales very well with increasing computing resources. The following figure shows how the throughput of Tentacle scales when increasing the number of utilized worker nodes. For complete test details, refer to :ref:`citing`. The evaluation results data and code to generate the figures are available for download from `figshare `_. A non-interactive version of the IPython notebook can also be `viewed in your browser `_. .. figure:: ./img/scaling.png :scale: 100% :alt: Tentacle scaling with increasing number of nodes Tentacle scales well with increasing number of nodes. .. _Quantification accuracy: Quantification accuracy ======================= The accuracy of quantification and coverage was also estimated. The following two figures show the expected and measured coverage and quantification results. For complete test details, please refer to :ref:`citing` and the IPython notebook which contains the code to generate the figures. The evaluation results data and code to generate the figures are available for download from `figshare `_. A non-interactive version of the IPython notebook can also be `viewed in your browser `_. Unforatunately, Sphinx does not allow embedding PDF imagery, so the following figures are only available as links to PDF figures. .. figure:: ./img/increases.pdf :scale: 50% :alt: Coverage and quantification accuracy Tentacle achieves very good coverage and quantification accuracy. .. figure:: ./img/violins.pdf :scale: 50% :alt: Distribution of measured quantification results on a semi-synthetic test case. The distribution of the measured quantification levels.