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Using GUI-based workflows for data analysis is an iterative process. During each iteration, an analyst makes changes to the workflow to improve it, generating a new version each time. The results produced by executing these versions are materialized to help users refer to them in the future. In many cases, a new version of the workflow, when submitted for execution, produces a result equivalent to that of a previous one. Identifying such equivalence can save computational resources and time by reusing the materialized result. One way to optimize the performance of executing a new version is to compare the current version with a previous one and test if they produce the same results using a workflow version equivalence verifier. As the number of versions grows, this testing can become a computational bottleneck. In this paper, we present Raven, an optimization framework to accelerate the execution of a new version request by detecting and reusing the results of previous equivalent versions with the help of a version equivalence verifier. Raven ranks and prunes the set of prior versions to quickly identify those that may produce an equivalent result to the version execution request. Additionally, when the verifier performs computation to verify the equivalence of a version pair, there may be a significant overlap with previously tested version pairs. Raven identifies and avoids such repeated computations by extending the verifier to reuse previous knowledge of equivalence tests. We evaluated the effectiveness of Raven compared to baselines on real workflows and datasets. 

β -Gallium oxide (Ga2O3) is an extensively investigated ultrawide-bandgap semiconductor for potential applications in power electronics and radio frequency switching. The room temperature bulk electron mobility (∼200cm2V−1s−1) is comparatively low and is limited by the 30 phonon modes originating from its 10-atom primitive cell. The theoretically calculated saturation velocity in bulk is 1–2×107cms−1 (comparable to GaN) and is limited by the low field mobility. This work explores the high field electron transport (and hence the velocity saturation) in the 2DEG based on the first principles calculated parameters. A self-consistent calculation on a given heterostructure design gives the confined eigenfunctions and eigenenergies. The intrasubband and the intersubband scattering rates are calculated based on the Fermi’s golden rule considering longitudinal optical (LO) phonon–plasmon screening. The high field characteristics are extracted from the full-band Monte Carlo simulation of heterostructures at 300 K. The overall system is divided into a 2D and a 3D region mimicking the electrons in the 2DEG and the bulk, respectively. The electron transport is treated through an integrated Monte Carlo program which outputs the steady state zone population, transient dynamics, and the velocity–field curves for a few heterostructure designs. The critical field for saturation does not change significantly from bulk values, however, an improved peak velocity is calculated at a higher 2DEG density. The velocity at low 2DEG densities is impacted by the antiscreening of LO phonons which plays an important role in shaping the zone population. A comparison with the experimental measurements is also carried out and possible origins of the discrepancies with experiments is discussed.

 

Collaborative data analytics is becoming increasingly important due to the higher complexity of data science, more diverse skills from different disciplines, more common asynchronous schedules of team members, and the global trend of working remotely. In this demo we will show how Texera supports this emerging computing paradigm to achieve high productivity among collaborators with various backgrounds. Based on our active joint projects on the system, we use a scenario of social media analysis to show how a data science task can be conducted on a user friendly yet powerful platform by a multi-disciplinary team including domain scientists with limited coding skills and experienced machine learning experts. We will present how to do collaborative editing of a workflow and collaborative execution of the workflow in Texera. We will focus on data-centric features such as synchronization of operator schemas among the users during the construction phase, and monitoring and controlling the shared runtime during the execution phase.