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814 results for “Time Analysis”
The growth of COVID-19 scientific literature: A forecast analysis of different daily time series in specific settings
<p>Submitted to The ISSI 2021 Conference. The conference is organised by KU Leuven in close collaboration with the university of Antwerp under the auspices of ISSI – the International Society for Informetrics and Scientometrics (<a href="http://www.issi-society.org/">http://www.issi-society.org/</a>). </p> <p>We present a forecasting analysis on the growth of scientific literature related to COVID-19 expected for 2021. Considering the paramount scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the ARIMA model and use two different data sources: the Dimensions and World Health Organization COVID-19 databases. These two sources have the particularity of including in the metadata information on the date in which papers were indexed. We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by NLM source (PubMed and PMC), and by domain-specific repository (SSRN and MedRxiv). We conclude by discussing our findings.</p>
InSAR time series analysis results of ALOS-2/PALSAR-2 data for the post-eruptive displacement of the 2015 phreatic eruption of Hakone volcano, Japan
<p>This repository contains the InSAR products used in Doke et al., GRL (submitted).</p> <p> </p> <p><strong>Dataset 1</strong>: Surface velocity data estimated by InSAR time series analysis with NetCDF grid format.</p> <ol> <li>surface_velocity_p126.nc</li> <li>surface_velocity_p18.nc</li> </ol> <p> </p> <p><strong>Dataset 2</strong>: Time-series of LOS displacements in selected locations with text format.</p> <ol> <li>time_series_p126.txt</li> <li>time_series_p18.txt</li> </ol> <p> </p> <p><strong>Dataset 3</strong>: Inputs and results of model inversion with shapefile.</p> <p>Subsampled observation data, modeled (simulated) displacements, and other parameters are shown in attribute tables in shapefiles. Shapefiles that show the location of the estimated models are also included in ZIP files.</p> <ol> <li>point_source_deflation.zip</li> <li>sill_deflation.zip</li> </ol>
Spin-up time and internal variability analysis for overlapping time slices in a regional climate model
<p>In order to increase computational efficiency, several long-term regional climate simulations were split into overlappings time slices. These overlappings slices were used to explore the relative role of spin-up time and internal variability in the discontinuities that are produced once the slices are joined.</p> <p>This dataset was generated using the Weather Research and Forecasting (WRF) model and includes two sets of time slices for the periods 2002-2006 and 2006-2010 over the CORDEX South American domain at 0.44º horizontal resolution (SAM-44), regular on a rotated latitude-longitude projection. The data was forced by the scenario RCP 8.5 and driven by the Canadian Earth System model (CanESM2). The model configuration files are also attached.</p>
The Effect of a New Generation of Ankle Foot Orthoses on Sloped Walking in Children with Hemiplegia Using the Gait Real Time Analysis Interactive Lab (GRAIL)
<div>The dataset includes the kinematics and kinetics of gait uphill (+10 deg), level ground (0 deg), and downhill (-5 deg) in children with unilateral cerebral palsy who underwent a single session of walking using immersive virtual reality (GRAIL system by Motek), while wearing traditional ankle-foot orthosis (oldAFOs) and a new generation AFO (newCAMOt1).</div> <div>In column A of the file, you will find the patient ID, the type of orthosis used, and the walking condition (e.g., P01_oldAFO_flat0001 indicates that patient 01 performed the walking trial on level ground with the traditional orthosis).</div> <div>In column B of the file, you will find the laterality (R = right, L = left), the name of the analyzed variable, and the stride number (e.g., L_Moment Ankle Flex_step1 means that we are considering the moment at the left ankle of the first left stride).</div> <div>From column C to column CY, you will find the values at the 101 temporal instants of the analyzed variable.</div>
AutoML Applied to Time Series Analysis Tasks in Production Engineering
<p>The dataset is accompanying the paper "AutoML Applied to Time Series Analysis Tasks in Production<br>Engineering" (<a href="https://doi.org/10.1016/j.procs.2024.01.085" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.procs.2024.01.085</a>). It contains the experimental data referred to in the paper as "KIOptiPack".</p>
Supplemental Information on the Weighted Gene Co-expression Network Analysis performed for the work "Time-resolved oxidative signal convergence across the algae–embryophyte divide"
<p>Supplemental Information on the Weighted Gene Co-expression Network Analysis (WGNCA) performed for the work "Time-resolved oxidative signal convergence across the algae–embryophyte divide"</p> <p>The results are sorted by the three species analysed: the two algae <em><span>Zygnema circumcarinatum</span></em><span> SAG 698-1b (<em>Zygnema</em>) and <em>Mesotaenium endlicherianum </em></span><span>SAG 12.97 (<em>Mesotaenium</em>); and the bryophyte <em>Physcomitrium patens</em></span><span><em> </em>strain Gransden 2004 (<em>Physcomitrium</em>).</span></p>
The effect of wheelchair users on the egress time of pedestrian crowds: a systematic literature review and meta-analysis
<p>This dataset provides supplementary input data for a systematic literature review and meta-analysis, examining the effects of mobility-impaired individuals, specifically wheelchair users, on pedestrian egress times. It includes the following variables:</p> <ul> <li><strong>short_trial_name</strong>: A unique identifier for each trial.</li> <li><strong>independent variables</strong>: Factors such as the number of attendees, bottleneck width, and mobility profiles (e.g., individuals with or without wheelchair usage).</li> <li><strong>left_shifted_time</strong>: Standardized start time for egress, adjusted for comparability across trials.</li> <li><strong>lower_left_no_of_people</strong>: The number of individuals who passed through the bottleneck at the standardized start time.</li> <li><strong>right_shifted_time</strong>: Standardized end time for egress.</li> <li><strong>right_left_no_of_people</strong>: The number of individuals who passed through the bottleneck by the standardized end time.</li> </ul>
Supplementary Material on "Early timing analysis based on scenario requirements and platform models"
<p>This dataset provides supplementary material on the submission “Early timing analysis based on scenario requirements and platform models” to the SoSyM theme issue on Model-Driven Requirements Engineering. It provides software and models for illustrating the paper's example application results as well as more detailed evaluation data.</p> <p>MSD-CCSL-TimingAnalysis.zip contains our approach and encompasses the following artifacts (Java 8 and not later required; if needed modify the GemocStudio.ini and point the vm to a corresponding Java version via "-vm <PathToJava8>\jre\bin"):</p> <ul> <li>Development workspace: <ul> <li>ECL specification under /de.fraunhofer.iem.swt.msd.tam.dse/ecl/MSDLanguage.ecl</li> <li>MoCCML constraints under /de.fraunhofer.iem.swt.msd.tam.mocc/mocc/MSDLanguageComplete.moccml</li> <li>TAM profile under /de.fraunhofer.iem.swt.msd.tam.tamProfile/model/tam.profile.uml</li> </ul> </li> <li>Runtime workspace: <ul> <li>Models under "01_ExampleModels"</li> <li>Exemplary traces under "02_ExampleTraces"</li> <li>QVT-O Transformations (e.g., Preprocessing) needed when modifying the models</li> </ul> </li> </ul> <p>Papyrus-CCSLEditor-Measurement.zip contains the plugins and artifacts that we used for measuring the particular modeling operations for the evaluation of the hypothesis H2 (see further documents below). It requires Java 11; if needed modify the eclipse.ini and point the vm to a corresponding Java version via "-vm <PathToJava11>\jre\bin". Contained plugins and artifacts:</p> <ul> <li>Development workspace: <ul> <li>is.ru.cs.PapyrusActivityLogger: Our adapted version of ModRec, particularly extended by an Xtext document listener</li> <li>org.eclipse.gemoc.moccml.*: MoCCML editor prerequisites for the CCSL runtime model</li> <li>org.scenariotools.msd.profile and de.fraunhofer.iem.swt.msd.tam.tamProfile: Profiles that we partially use in the Papyrus runtime model</li> </ul> </li> <li>Runtime workspace: <ul> <li>CCSL Measuring Project: Measuring project for CCSL models</li> <li>Papyrus Measuring Project: Measuring project for Papyrus models</li> </ul> </li> </ul> <p>Further documents:</p> <ul> <li>MSD-CCSL-TimingAnalysisTutorial.pdf: Tutorial on starting the simulative timing analysis</li> <li>EvaluationData_H1_TimingEffectTestResults: Test results for the particular timing effects based on several models for hypothesis H1</li> <li>Files for hypothesis H2: <ul> <li>EvaluationData_H2.xlsx: Spreadsheet containing the particular model element amounts of MSD-spec-1--4 and CCSL-model-1--4, the measurements for the categorized atomic model operation kinds, the multiplication scheme for predicting the raw overall effort, and the measured transformation execution times</li> <li>EvaluationData_H2_MSD-specification-effort.pdf: PDF extract of the spreadsheet contents for the MSD specification effort and computation</li> <li>EvaluationData_H2_CCSL-model-effort.pdf: PDF extract of the spreadsheet contents for the CCSL model effort and computation</li> <li>EvaluationData_H2_transformationExecTimes.pdf: PDF extract of the spreadsheet contents for the transformation execution times</li> <li>EvaluationData_H2_MSD-specification_measurement-timestamps.txt: Raw timestamp logs for the conducted measurements for model operations on MSD specifications</li> <li>EvaluationData_H2_CCSL-model_measurement-timestamps.txt: Raw timestamp logs for the conducted measurements for model operations on CCSL models</li> </ul> </li> </ul>
Analysis of the root diameter distribution from time series images of real and simulated Cassava root systems
<p>The data was collected, simulated and analyzed in the framework of the CassavaStore project (a collaboration between IBG-2, Forschungszentrum Jülich, Germany and different institution from Thailand; for details see <a href="https://www.international-bioeconomy.org/cassavastore_eng">https://www.international-bioeconomy.org/cassavastore_eng</a>). Aim of this project is to get a better understanding of storage root development in cassava (<em>Manihot esculenta</em> Crantz) in order to optimize cassava growth with respect to variety breeding and growth management. The storage root is one of the main providers of starch in Thailand and therefore of high economic importance. Monitoring the formation of storage roots over time via quantification of the root diameter distribution of excavated root systems was one of the key aspects addressed in this project. To measure the diameters a software was developed that identifies roots in RGB images and analyzes the diameters along each identified root automatically. The published data contains 1) analyzed images from cassava roots that were acquired in a video box; 2) simulated virtual root model images with known root diameter distributions that were used to validate the analysis approach; 3) a description of the data and the folder structure.</p>
Data from: Research and exploratory analysis driven - time-data visualization (read-tv) software
<strong><em>read-tv</em></strong> <p>The main paper is about, <em>read-tv</em>, open-source software for longitudinal data visualization. We uploaded sample use case surgical flow disruption data to highlight <em>read-tv</em>'s capabilities. We scrubbed the data of protected health information, and uploaded it as a single CSV file. A description of the original data is described below.</p> Data source <p>Surgical workflow disruptions, defined as "<i>deviations from the natural progression of an operation thereby potentially compromising the efficiency or safety of care", </i>provide a window on the systems of work through which it is possible to analyze <u>mismatches between the work demands and the ability of the people to deliver the work</u>. They have been shown to be sensitive to different intraoperative technologies, surgical errors, surgical experience, room layout, checklist implementation and the effectiveness of the supporting team. The significance of flow disruptions lies in their ability to provide a hitherto unavailable perspective on the quality and efficiency of the system. This allows for a systematic, quantitative and replicable assessment of risks in surgical systems, evaluation of interventions to address them, and assessment of the role that technology plays in exacerbation or mitigation.</p> <p>In 2014, Drs Catchpole and Anger were awarded NIBIB R03 EB017447 to investigate flow disruptions in Robotic Surgery which has resulted in the detailed, multi-level analysis of over 4,000 flow disruptions. Direct observation of 89 RAS (robitic assisted surgery) cases, found a mean of 9.62 flow disruptions per hour, which varies across different surgical phases, predominantly caused by coordination, communication, equipment, and training problems.</p>
Adolescents' mental health and maladaptive behaviors before the Covid-19 pandemic and one-year after: analysis of trajectories over time and associated factors
<p>The database reports data about psychopathological indexes in a sample of adolescent students (N=153) assessed before Covid-19 pandemic (T0, November 2019-January 2020) and one year after (T1, April-May 2021).</p>
The conductivity profile of Earth-ionosphere cavity used in the paper "Finite-difference time-domain analysis of ELF radio wave propagation in the spherical Earth-ionosphere waveguide and its validation based on analytical solutions" by Volodymyr Marchenko, Andrzej Kulak, Janusz Mlynarczyk
<p>The file "Marchenko_FDTD_Paper_Conductivity_Profile.dat" contains the conductivity profile of Earth-ionosphere cavity. The first column provides the altitude (in km) and the second column provides the conductivity (in S/m).</p>
Data from: Girth increment changes in response to soil water availability in lowland dipterocarp forest in Borneo: an individualistic time-series analysis
<p><span>Time-series data offer a way of investigating the causes driving ecological processes as phenomena. To test for possible differences in water relations between species of different forest structural guilds at Danum (Sabah, NE Borneo), daily stem girth increments (gthi), of 18 trees across six species were regressed individually on soil moisture potential (SMP) and temperature (TEMP), accounting for temporal autocorrelation (in GLS-arima models), and compared between a wet and a dry period. The best-fitting significant variables were SMP the day before and TEMP the same day. The first resulted in a mix of positive and negative coefficients, the second largely positive ones. An adjustment for dry-period showers was applied. Interactions were stronger in dry than wet period. Negative relationships for overstorey trees can be interpreted in a reversed causal sense: fast transporting stems depleted soil water and lowered SMP. Positive relationships for understorey trees meant they took up most water at high SMP. The unexpected negative relationships for these small trees may have been due to their roots accessing deeper water supplies (if SMP was inversely related to that of the surface layer), and this was influenced by competition with larger neighbour trees. A tree-soil flux dynamics manifold may have been operating. Patterns of mean diurnal girth variation were more consistent among species, and time-series coefficients were negatively related to their maxima. Expected differences in response to SMP in the wet and dry periods did not clearly support a previous hypothesis differentiating drought and non-drought tolerant understorey guilds. Trees within species showed highly individual responses when tree size was standardized. Data on individual root systems and SMP at several depths are needed to get closer to the mechanisms that underlie the tree-soil water phenomena in these tropical forests. Neighborhood stochasticity importantly creates varying local environments experienced by individual trees.</span></p>
Datasets corresponding to "Real-time intelligent classification of COVID-19 and thrombosis via massive image-based analysis of platelet aggregates"
<p>Datasets corresponding to "Real-time intelligent classification of COVID-19 and thrombosis via massive image-based analysis of platelet aggregates"</p> <p> </p> <p>Please find below an explanation for the <strong>files </strong>in this repository:</p> <p><br> <br> <strong>DiseaseClassifPaper_Dataset_01.7z, DiseaseClassifPaper_Dataset_02.7z</strong></p> <p>Experimental data. To reproduce the analyses, unzip both files and put the content into a folder called "Dataset"</p> <p><strong>02_CNN_PhenotypeClassif.7z</strong></p> <p>CNN Phenotype classification. Model was trained using AIDeveloper. using manually labelled data. Labelled Data is contained in folder "03_GatedData". The AIDeveloper session file in "02_Model\M10_Nitta6l_32pix_8class_meta.xlsx" shows, which files correspond to which subpopulation. The final model "M10_Nitta6l_32pix_8class_448.model" and corresponding .pb files are also located in that folder.</p> <p><strong>03_ExampleMeasurement.zip</strong></p> <p>One measurement file and a corresponding scatterplot</p> <p><strong>04_Dataset_load.zip</strong></p> <p>The python script "03_ExtractFeatures.py" loads the list of available experiment files (01_Dataset_Table_v02.csv). The experiment files are contained in DiseaseClassifPaper_Dataset_01.7z, DiseaseClassifPaper_Dataset_02.7z. The scrip then evaluates each experiment file to obtain distribution parameters for Area and Solidity. These values are written to new "01_Dataset_Table_v03.csv".</p> <p><strong>05_RF_training</strong></p> <p>Scripts to train and evaluate the Random Forest model (using features contained in "01_Dataset_Table_v03.csv").</p> <p><strong>07_pytranskit</strong></p> <p>Scripts for training and evaluating CDT-PLDA classifier</p> <p> </p> <p> </p>
Microdata on vector abundance and IRS quality assurance (Estimating the impact of indoor residual spraying on sandfly abundance and incidence of visceral leishmaniasis in India from 2016 to 2022: an interrupted time-series analysis and modelling study)
<p>This repository contains the microdata on vector abundance and quality assurance of indoor residual spraying (IRS) that was used to estimate the impact of IRS on sandfly abundance and incidence of visceral leishmaniasis (VL) in India, as described in the paper "Estimating the impact of indoor residual spraying on sandfly abundance and incidence of visceral leishmaniasis in India from 2016 to 2022: an interrupted time-series analysis and modelling study" by Coffeng et al (<a href="https://doi.org/10.1016/S1473-3099(24)00420-1">https://doi.org/10.1016/S1473-3099(24)00420-1</a>). These data were collected as part of a BMGF-funded project led by dr. Michael Coleman at the Liverpool School for Tropical Medicine, as described in an earlier paper by Deb et al (<a href="https://doi.org/10.1371/journal.pntd.0009101">https://doi.org/10.1371/journal.pntd.0009101</a>).</p> <p>This repository does not include microdata on VL cases as these are owned by India's National Center for Vector Borne Disease Control (NCVBDC, <a href="https://ncvbdc.mohfw.gov.in/" target="_blank" rel="nofollow noreferrer noopener">https://ncvbdc.mohfw.gov.in/</a>).</p>
Analysis of thermal and dielectric loss features of lunar regolith considering real-time effect solar irradiance
<p>ESI data for "Analysis of thermal and dielectric loss features of lunar regolith considering real-time effect solar irradiance".</p>
Carbon Dioxide and Methane Flux Meta Analysis, Schaerer et al: Permafrost microbes unleashed: thaw reactors provide timely insights into greenhouse gas feedbacks for climate stewardship
<p>Meta-analysis results and workflow: <strong>Meta-Analysis-Report-V1.pdf</strong> </p> <p>raw data tables for input into meta-analysis:</p> <p><strong>co2_flux_by_layer_temp.csv</strong></p> <p><strong>co2_flux_by_layer_time.csv</strong></p> <p><strong>ch4_flux_by_layer_temp.csv</strong></p> <p><strong>ch4_flux_by_layer_time.csv</strong></p> <p><strong>co2_flux_by_headspace_temp.csv</strong></p> <p>(Data included in these tables was digitized using the R package metaDigitize)</p> <p>****</p> <p>We also attempted to summarize the raw data from 12 studies which is summarized in the <strong><em>Flux_Summary_Report </em></strong>document. we converted all units into mg C / g Soil * d (calculations are included in the <strong><em>co2_meta_analysis</em></strong> spreadsheet). For studies not reporting raw data or data tables (7/12 studies), we estimated the values from the figures manually. This typically resulted in an estimate of the mean flux of several replicates (all studies had 3-10 replicates). We filled in metadata as well as we could based on the information available in the papers, although there were many gaps. This information is summarized in the <strong><em>flux_data_compilation</em> </strong>spreadsheet.</p> <p>Studies in the raw data comparison include: Mackelprang 2011, Waldrop 2010 & 2021, Barbato 2022, Dang 2022, Muller 2018, Monteaux 2020, Dutta 2006, Lee 2012, O'Donnell 2009, Roy Chowdhury 2014, Trubl 2021.</p>
Vegetation greenesss data for the Aït Benhaddou Catchment, Morocco. Includes: 1984-2019 NDVI time series, breakpoint analysis results, and resillience indicator results, among others.
<p>This dataset is comprised of two main parts, both originating from different but related works. </p> <p>The NDVI timeseries and breakpoint analysis were originally developed by Vermeer (2021) for the MSc thesis: Vermeer, A. L. (2021). <em>Ecological stability in the face of climatic disturbances: a case study of a dryland ecosystem in the Moroccan High Atlas Mountains</em>. These data include a harmonized timeseries of Normalized Difference Vegetation Index from different Landsat missions at 30x30 meter resolution for the Aït Benhaddou catchment in Morocco. It also includes the output of a breakpoint analysis that was conducted using this dataset, which showcases different statistical breakpoints in NDVI after a severe drought that occured between 1998 and 2002. Shapefiles, a DEM and masks of irrigiated areas for the catchment are also included. For more information about these data, consult Vermeer (2021).</p> <p>The secondary part of this dataset was produced by Grootoonk (2024) for the MSc thesis: Grootoonk, W. (2024). <em>Relations between temporal resilience indicators and trend breakpoints in a dryland high-mountain catchment, </em>drawing upon the original dataset from Vermeer (2021). These data include Kendall's tau values for the resillience indicators variance and lag-one autocorrelation, computed using a rolling window for each pixel. Results for differerent window sizes (WS) for both indicators are included. </p> <p>Beyond these main results, a number of additional data sources are provided. These are Kendall's tau for precipitation variance in the area, produced using CHIRPS data (https://www.chc.ucsb.edu/data/chirps) and a NSI soil salinity map produced from Landsat imagery. See Grootoonk (2024) for more information. </p>
On the Timed Analysis of Big-Data Applications - Experimental Data
<p>This archive includes experimental data associated to the paper:</p> <p>On the Timed Analysis of Big-Data Applications. Accepted in <em>Proceedings of Nasa Formal Methods</em> (NFM 2018). <br> Marconi, F., Quattrocchi, G., Baresi, L., Bersani, M.M., Rossi, M.. 2018</p> <p>Specifically, it includes detailed data regarding the verification tasks reported in Section 4 (Implementation and Validation of the Model).<br> In reference to Table 1 of the paper, the archive is organized in the following way: there is one folder for each case study (sort_by_key, pagerank, kmeans) and, for each of these folders, there is a subfolder for each configuration considered in the paper.</p> <p>Here we report an overview of the verification tasks performed. The name of the tables correspond to the code of the setting and to the name of the folder, while the id of each entry corresponds to the folder name of each experiment.</p> <pre><code class="language-markdown">## SortByKey Experiments ### sort_by_key_C12_T100_rec260000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 12 | 91000 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91000_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91100 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91100_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91200 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91200_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91300 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91300_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91360 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91360_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91370 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91370_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91380 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91380_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91381 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91381_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91382 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91382_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91383 | timeout | None | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91383_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91384 | sat | 3.81 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91384_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91385 | sat | 3.34 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91385_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91386 | sat | 3.52 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91386_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91387 | sat | 3.42 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91387_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91388 | sat | 3.4 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91388_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91389 | sat | 3.43 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91389_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91390 | sat | 2.37 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91390_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91400 | sat | 3.38 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91400_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91500 | sat | 16.52 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91500_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91600 | sat | 6.8 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91600_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91700 | sat | 12.03 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91700_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91800 | sat | 5.62 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91800_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 91900 | sat | 5.54 | C1_t100_c12_c12_t100_nr260000000_tb20_no_l_d91900_tc_12_8_n_rounds_by1_t_task | the minimum SAT deadline is: 91384 ### sort_by_key_C12_T100_rec280000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 12 | 98200 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98200_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98300 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98300_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98400 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98400_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98402 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98402_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98403 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98403_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98404 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98404_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98405 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98405_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98406 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98406_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98407 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98407_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98408 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98408_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98409 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98409_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98410 | timeout | None | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98410_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98420 | sat | 3.48 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98420_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98430 | sat | 3.57 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98430_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98440 | sat | 6.68 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98440_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98450 | sat | 7.1 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98450_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98460 | sat | 37.07 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98460_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98470 | sat | 10.33 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98470_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98480 | sat | 18.14 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98480_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98490 | sat | 10.78 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98490_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 98500 | sat | 3.43 | C1_t100_c12_c12_t100_nr280000000_tb20_no_l_d98500_tc_12_8_n_rounds_by1_t_task | the minimum SAT deadline is: 98420 ### sort_by_key_C12_T100_rec300000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 12 | 105200 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105200_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105300 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105300_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105400 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105400_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105420 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105420_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105430 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105430_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105440 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105440_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105441 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105441_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105442 | timeout | None | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105442_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105443 | sat | 3.33 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105443_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105444 | sat | 3.35 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105444_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105445 | sat | 3.3 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105445_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105446 | sat | 3.31 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105446_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105447 | sat | 3.37 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105447_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105448 | sat | 3.37 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105448_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105449 | sat | 3.3 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105449_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105450 | sat | 3.02 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105450_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105460 | sat | 3.03 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105460_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105470 | sat | 4.52 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105470_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105480 | sat | 4.54 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105480_tc_12_8_n_rounds_by1_t_task | | sort_by_key | 12 | 105490 | sat | 9.48 | C1_t100_c12_c12_t100_nr300000000_tb20_no_l_d105490_tc_12_8_n_rounds_by1_t_task | the minimum SAT deadline is: 105443 ### sort_by_key_C22_T100_rec260000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 22 | 70000 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d70000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 70500 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d70500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 71000 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d71000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 71500 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d71500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72000 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72250 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72250_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72500 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72750 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72750_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72885 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72885_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72890 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72890_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72895 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72895_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72898 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72898_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72899 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72899_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72900 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72900_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72901 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72901_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72902 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72902_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72903 | timeout | None | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72903_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72904 | sat | 9.35 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72904_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72905 | sat | 8.16 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72905_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72910 | sat | 8.15 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72910_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72915 | sat | 7.72 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72915_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72920 | sat | 7.55 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72920_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72925 | sat | 5.29 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72925_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72930 | sat | 10.23 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72930_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72935 | sat | 11.21 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72935_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72940 | sat | 10.98 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72940_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72945 | sat | 12.62 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72945_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72950 | sat | 12.55 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72950_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72955 | sat | 3.19 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72955_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72960 | sat | 2.62 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72960_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72965 | sat | 2.62 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72965_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72970 | sat | 2.63 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72970_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72975 | sat | 2.62 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72975_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72980 | sat | 2.72 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72980_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72985 | sat | 2.6 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72985_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72990 | sat | 2.55 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72990_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72995 | sat | 2.56 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d72995_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 73000 | sat | 3.2 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d73000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 74000 | sat | 6.34 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d74000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 75000 | sat | 3.88 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d75000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 76000 | sat | 4.6 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d76000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 77000 | sat | 4.15 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d77000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78000 | sat | 1.89 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d78000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 79000 | sat | 3.28 | C2_t100_c22_c22_t100_nr260000000_tb20_no_l_d79000_tc_22_10_n_rounds_by1_t_task | the minimum SAT deadline is: 72904 ### sort_by_key_C22_T100_rec280000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 22 | 78000 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78480 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78480_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78485 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78485_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78490 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78490_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78492 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78492_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78494 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78494_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78495 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78495_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78496 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78496_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78497 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78497_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78498 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78498_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78499 | timeout | None | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78499_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78500 | sat | 40.11 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78500_tc_22_10_n_rounds_by1_t_task_num_v | | sort_by_key | 22 | 78750 | sat | 1.33 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d78750_tc_22_10_n_rounds_by1_t_task_num_v | | sort_by_key | 22 | 79000 | sat | 9.14 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d79000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 80000 | sat | 2.27 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d80000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 81000 | sat | 1.98 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d81000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 82000 | sat | 5.89 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d82000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 83000 | sat | 8.81 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d83000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84000 | sat | 1.86 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d84000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 85000 | sat | 2.46 | C2_t100_c22_c22_t100_nr280000000_tb20_no_l_d85000_tc_22_10_n_rounds_by1_t_task | the minimum SAT deadline is: 78500 ### sort_by_key_C22_T100_rec300000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | sort_by_key | 22 | 5000 | unsat | 0.56 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d5000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 10000 | unsat | 0.44 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d10000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 12000 | unsat | 1.07 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d12000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 15000 | unsat | 1.72 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d15000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 20000 | unsat | 1.13 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d20000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 25000 | unsat | 3.71 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d25000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 30000 | unsat | 4.27 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d30000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 35000 | unsat | 15.73 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d35000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 40000 | unsat | 8.82 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d40000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 45000 | unsat | 15.27 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d45000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 50000 | unsat | 19.42 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d50000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 55000 | unsat | 39.81 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d55000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 60000 | unsat | 39.71 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d60000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 65000 | unsat | 87.48 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d65000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 70000 | unsat | 120.21 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d70000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 72500 | unsat | 172.18 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d72500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 74000 | unsat | 186.82 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d74000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 75000 | unsat | 120.49 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d75000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 76000 | unsat | 1175.84 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d76000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 76250 | unsat | 1167.23 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d76250_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 77500 | unsat | 2091.15 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d77500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 78250 | unsat | 3000.66 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d78250_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 80000 | unsat | 34239.41 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d80000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 81250 | unsat | 79433.55 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d81250_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 82500 | unsat | 198577.62 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d82500_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 83000 | unsat | 183847.9 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d83000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 83750 | unsat | 245288.49 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d83750_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84000 | unsat | 276617.22 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84000_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84100 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84100_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84101 | unsat | 253379.92 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84101_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84102 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84102_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84103 | unsat | 254808.3 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84103_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84104 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84104_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84105 | unsat | 269304.76 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84105_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84106 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84106_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84107 | unsat | 242278.6 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84107_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84108 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84108_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84109 | unsat | 260411.26 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84109_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84110 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84110_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84111 | unsat | 259311.3 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84111_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84112 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84112_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84113 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84113_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84114 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84114_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84115 | unsat | 230687.19 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84115_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84116 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84116_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84117 | unsat | 281773.79 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84117_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84118 | timeout | None | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84118_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84119 | unsat | 272785.32 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84119_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84120 | sat | 4.09 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84120_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84121 | sat | 3.98 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84121_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84122 | sat | 4.01 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84122_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84123 | sat | 4.28 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84123_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84124 | sat | 4.24 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84124_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84125 | sat | 4.22 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84125_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84126 | sat | 4.25 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84126_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84127 | sat | 4.39 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84127_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84128 | sat | 4.23 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84128_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84129 | sat | 4.14 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84129_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84130 | sat | 4.07 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84130_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84131 | sat | 4.24 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84131_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84132 | sat | 4.42 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84132_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84133 | sat | 4.32 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84133_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84134 | sat | 4.31 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84134_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84135 | sat | 4.33 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84135_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84136 | sat | 4.26 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84136_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84137 | sat | 4.01 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84137_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84138 | sat | 3.82 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84138_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84139 | sat | 4.07 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84139_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84140 | sat | 4.38 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84140_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84141 | sat | 8.74 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84141_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84142 | sat | 8.98 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84142_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84143 | sat | 9.1 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84143_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84144 | sat | 9.09 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84144_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84145 | sat | 9.19 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84145_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84146 | sat | 9.1 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84146_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84147 | sat | 8.82 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84147_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84148 | sat | 6.54 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84148_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84149 | sat | 6.56 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84149_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84150 | sat | 6.59 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84150_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84151 | sat | 6.84 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84151_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84152 | sat | 6.87 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84152_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84153 | sat | 6.97 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84153_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84154 | sat | 6.88 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84154_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84155 | sat | 6.98 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84155_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84156 | sat | 6.71 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84156_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84157 | sat | 6.75 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84157_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84158 | sat | 6.42 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84158_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84159 | sat | 6.62 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84159_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84160 | sat | 6.75 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84160_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84161 | sat | 6.95 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84161_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84162 | sat | 7.03 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84162_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84163 | sat | 6.98 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84163_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84164 | sat | 7.08 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84164_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84165 | sat | 6.93 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84165_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84166 | sat | 6.81 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84166_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84167 | sat | 6.47 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84167_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84168 | sat | 6.66 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84168_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84169 | sat | 6.73 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84169_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84171 | sat | 6.8 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84171_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84172 | sat | 6.81 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84172_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84173 | sat | 6.71 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84173_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84174 | sat | 3.56 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84174_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84175 | sat | 3.26 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84175_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84176 | sat | 3.52 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84176_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84177 | sat | 3.6 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84177_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84178 | sat | 3.02 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84178_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84179 | sat | 3.6 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84179_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84180 | sat | 3.62 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84180_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84181 | sat | 3.59 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84181_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84182 | sat | 3.62 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84182_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84183 | sat | 6.72 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84183_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84184 | sat | 6.58 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84184_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84186 | sat | 6.59 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84186_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84187 | sat | 6.85 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84187_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84188 | sat | 6.56 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84188_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84189 | sat | 6.88 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84189_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84190 | sat | 6.84 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84190_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84191 | sat | 6.86 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84191_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84192 | sat | 6.94 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84192_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84193 | sat | 6.93 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84193_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84194 | sat | 6.91 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84194_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84195 | sat | 6.84 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84195_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84196 | sat | 6.99 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84196_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84197 | sat | 6.89 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84197_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84198 | sat | 6.95 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84198_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84200 | sat | 8.04 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84200_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 | 84300 | sat | 11.06 | C2_t100_c22_c22_t100_nr300000000_tb20_no_l_d84300_tc_22_10_n_rounds_by1_t_task | | sort_by_key | 22 </code></pre> <p> </p> <pre><code class="language-markdown"> ## PageRank Experiments ### pagerank_C28_T128_rec200000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 28 | 61000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d61000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 61500 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d61500_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 62000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d62000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 62500 | sat | 7805.0 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d62500_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 63000 | sat | 330.87 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d63000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 63500 | sat | 79.78 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr200000000_tb45_no_l_d63500_tc_28_12_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 62500 ### pagerank_C28_T128_rec300000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 28 | 93000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d93000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 94000 | sat | 192.86 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d94000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 94001 | sat | 7331.63 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d94001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 94501 | sat | 1934.68 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d94501_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 94502 | sat | 2856.96 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb55_no_l_d94502_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 95000 | sat | 221.22 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d95000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 95001 | sat | 173.91 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d95001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 96001 | sat | 87.89 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d96001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 97001 | sat | 70.07 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr300000000_tb45_no_l_d97001_tc_28_12_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 94000 ### pagerank_C28_T128_rec400000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 28 | 118000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d118000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 119000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d119000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 119001 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d119001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 120000 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d120000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 120001 | timeout | None | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d120001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 120002 | sat | 138.84 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d120002_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 120003 | sat | 272.19 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d120003_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 120004 | sat | 2072.06 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d120004_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 121000 | sat | 580.28 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d121000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 121001 | sat | 55.8 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d121001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 122000 | sat | 301.84 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d122000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 122001 | sat | 187.93 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d122001_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 124000 | sat | 51.47 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d124000_tc_28_12_n_rounds_by1_t_task_num_v | | pagerank | 28 | 131000 | sat | 46.01 | exp_n4_c28_p140_SPARKSEQ_5_rounds_replica_c28_t128_nr400000000_tb45_no_l_d131000_tc_28_12_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 120002 ### pagerank_C48_T128_rec200000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 48 | 5000 | unsat | 20.91 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d5000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 10000 | unsat | 1002.53 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d10000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 15000 | unsat | 407.96 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d15000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 20000 | unsat | 667.32 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d20000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 25000 | unsat | 1263.14 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d25000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 30000 | unsat | 3561.83 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d30000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 35000 | unsat | 12742.87 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d35000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 37000 | unsat | 44051.41 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d37000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 40000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d40000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 43000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d43000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 45000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d45000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46050 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46050_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46100 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46100_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46200 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46200_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46250 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46250_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46750 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46750_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 46900 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d46900_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 47000 | sat | 59.41 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d47000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 48000 | sat | 39.88 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d48000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 49000 | sat | 31.35 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d49000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 50000 | sat | 45.02 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d50000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 51000 | sat | 43.73 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d51000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 52000 | sat | 36.25 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d52000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 52500 | sat | 40.5 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d52500_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 53500 | sat | 40.61 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d53500_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 54000 | sat | 39.9 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr200000000_tb45_no_l_d54000_tc_48_16_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 47000 ### pagerank_C48_T128_rec300000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 48 | 64000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d64000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65050 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65050_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65100 | sat | 1282.46 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65100_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65200 | sat | 102.8 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65200_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65250 | sat | 75.45 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65250_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65500 | sat | 39.15 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65500_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65750 | sat | 78.42 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65750_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 65900 | sat | 33.61 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d65900_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 66000 | sat | 96.91 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d66000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 67000 | sat | 56.04 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d67000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 68000 | sat | 65.88 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d68000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 69000 | sat | 40.79 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d69000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 70000 | sat | 51.82 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d70000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 72000 | sat | 49.1 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d72000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 73000 | sat | 26.86 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr300000000_tb45_no_l_d73000_tc_48_16_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 65100 ### pagerank_C48_T128_rec400000000 | Application | Cores | Deadline | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:| | pagerank | 48 | 85000 | timeout | None | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d85000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 86000 | sat | 278.68 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d86000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 87000 | sat | 55.3 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d87000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 88000 | sat | 55.59 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d88000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 89000 | sat | 42.06 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d89000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 90000 | sat | 51.77 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d90000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 91000 | sat | 45.12 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d91000_tc_48_16_n_rounds_by1_t_task_num_v | | pagerank | 48 | 92000 | sat | 38.55 | exp_n4_c48_p128_SPARKSEQ_3_rounds_c48_t128_nr400000000_tb45_no_l_d92000_tc_48_16_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 86000 </code></pre> <p> </p> <pre><code class="language-markdown">## K-Means Experiments ### kmeans_C24_T18_rec80000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 24 | 79000 | 50 | sat | 61854.62 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d79000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 79500 | 50 | sat | 18414.51 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d79500_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 80000 | 50 | sat | 14840.75 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d80000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 85000 | 50 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d85000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 90000 | 50 | sat | 14590.33 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d90000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 100000 | 50 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr80000000_tb50_no_l_d100000_tc_24_6_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 79000 ### kmeans_C24_T18_rec120000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 24 | 105000 | 50 | sat | 152363.81 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d105000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 105000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb80_no_l_d105000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 106000 | 50 | sat | 43759.32 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d106000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 106500 | 50 | sat | 22230.43 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d106500_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 107000 | 50 | sat | 25027.5 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d107000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 108000 | 50 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d108000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 110000 | 50 | sat | 40917.73 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d110000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 110000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb80_no_l_d110000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 115000 | 50 | sat | 12142.65 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d115000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 115000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb80_no_l_d115000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 120000 | 50 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d120000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 120000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb80_no_l_d120000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 50 | sat | 14259.95 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb50_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 60 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb60_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 70 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb70_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 80 | sat | 14189.62 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb80_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 90 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr120000000_tb90_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 105000 ### kmeans_C24_T18_rec160000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 24 | 140000 | 50 | sat | 40930.77 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr160000000_tb50_no_l_d140000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 140000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr160000000_tb80_no_l_d140000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 50 | sat | 21741.22 | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr160000000_tb50_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | | kmeans | 24 | 150000 | 80 | err/timeout | None | kmeans_exp_n2_c24_p24_SPARK_FSEQ_4_rounds_c24_t18_nr160000000_tb80_no_l_d150000_tc_24_6_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 140000 ### kmeans_C32_T24_rec80000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 32 | 63000 | 80 | sat | 26400.12 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr80000000_tb80_no_l_d63000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 65000 | 80 | sat | 10414.91 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr80000000_tb80_no_l_d65000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 70000 | 80 | sat | 5554.03 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr80000000_tb80_no_l_d70000_tc_32_8_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 63000 ### kmeans_C32_T24_rec120000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 32 | 82000 | 60 | sat | 2692.91 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb60_no_l_d82000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 82000 | 100 | running | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb100_no_l_d82000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 83000 | 60 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb60_no_l_d83000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 83000 | 100 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb100_no_l_d83000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 90000 | 60 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb60_no_l_d90000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 90000 | 100 | sat | 60535.12 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb100_no_l_d90000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 50 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb50_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 60 | sat | 1240.52 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb60_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 70 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb70_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 80 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb80_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 90 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb90_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 150000 | 100 | sat | 1957.42 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr120000000_tb100_no_l_d150000_tc_32_8_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 82000 ### kmeans_C32_T24_rec160000000 | Application | Cores | Deadline |Time Bound | Outcome | Verification Time | id | |-------|:-------:|:------:|:--------:|:--------:|:------:|:------:| | kmeans | 32 | 103000 | 50 | sat | 47624.75 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb50_no_l_d103000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 103000 | 80 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb80_no_l_d103000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 105000 | 50 | sat | 38614.93 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb50_no_l_d105000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 105000 | 80 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb80_no_l_d105000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 110000 | 50 | sat | 11604.73 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb50_no_l_d110000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 120000 | 50 | sat | 11559.37 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb50_no_l_d120000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 120000 | 80 | sat | 27413.19 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb80_no_l_d120000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 50 | sat | 1811.52 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb50_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 60 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb60_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 70 | sat | 2423.68 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb70_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 80 | sat | 952.42 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb80_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 90 | sat | 1300.52 | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb90_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | | kmeans | 32 | 200000 | 100 | err/timeout | None | kmeans_exp_n2_c32_p32_SPARKSEQ_4_rounds_c32_t24_nr160000000_tb100_no_l_d200000_tc_32_8_n_rounds_by1_t_task_num_v | the minimum SAT deadline is: 103000 </code></pre> <p> </p>
Time-generalized multivariate analysis of EEG responses reveals a cascading architecture of semantic mismatch processing
<p>This entry includes the required data to conduct the analysis from our paper. It includes recordings, a look-up csv for target word onsets and montage file. Github page for analysis code: https://github.com/heikele/GAT_n4-p6</p> <p> </p> <p>Abstract from submitted paper:</p> <p>Event-related brain potentials have a strong impact on neurocognitive models, as they inform about the temporal sequence of cognitive processes. Nevertheless, their value for deciding among alternative cognitive architectures is partly limited by component overlap and the possibility of ambiguity regarding component identity. Here, we apply temporally-generalized multivariate pattern analysis – a recently-proposed machine learning method capable of tracking the evolution of neurocognitive processes over time – to constrain possible alternative architectures underlying the processing of semantic incongruency in sentences. In a spoken sentence paradigm, we replicate established N400/P600 correlates of semantic mismatch. Time-generalized decoding indicatesthat early vs. late mismatch-sensitive processes are (i) distinct in their neural substrate, arguing against recurrent or latency-shifted single process architectures, and (ii) partially overlapping in time, inconsistent withpredictions of strictly serial models. These results are in accordance withan incremental-cascading neurocognitive organization of semantic mismatch processing. We propose time-generalized multivariate decoding as a valuable tool for neurocognitive language studies.</p> <p> </p> <p>Keywords: EEG; ERP; semantic mismatch; N400; P600; multivariate pattern analysis; generalization across time decoding</p>
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