Traveler: Navigating Task Parallel Traces for Performance Analysis.

Understanding the behavior of software in execution is a key step in identifying and fixing performance issues. This is especially important in high performance computing contexts where even minor performance tweaks can translate into large savings in terms of computational resource use. To aid performance analysis, developers may collect an execution trace-a chronological log of program activity during execution. As traces represent the full history, developers can discover a wide array of possibly previously unknown performance issues, making them an important artifact for exploratory performance analysis. However, interactive trace visualization is difficult due to issues of data size and complexity of meaning. Traces represent nanosecond-level events across many parallel processes, meaning the collected data is often large and difficult to explore. The rise of asynchronous task parallel programming paradigms complicates the relation between events and their probable cause. To address these challenges, we conduct a continuing design study in collaboration with high performance computing researchers. We develop diverse and hierarchical ways to navigate and represent execution trace data in support of their trace analysis tasks. Through an iterative design process, we developed Traveler, an integrated visualization platform for task parallel traces. Traveler provides multiple linked interfaces to help navigate trace data from multiple contexts. We evaluate the utility of Traveler through feedback from users and a case study, finding that integrating multiple modes of navigation in our design supported performance analysis tasks and led to the discovery of previously unknown behavior in a distributed array library.

The challenges of theory-software translation.

Background: Software is now ubiquitous within research. In addition to the general challenges common to all software development projects, research software must also represent, manipulate, and provide data for complex theoretical constructs. Ensuring this process of theory-software translation is robust is essential to maintaining the integrity of the science resulting from it, and yet there has been little formal recognition or exploration of the challenges associated with it. Methods: We thematically analyse the outputs of the discussion sessions at the Theory-Software Translation Workshop 2019, where academic researchers and research software engineers from a variety of domains, and with particular expertise in high performance computing, explored the process of translating between scientific theory and software. Results: We identify a wide range of challenges to implementing scientific theory in research software and using the resulting data and models for the advancement of knowledge. We categorise these within the emergent themes of design, infrastructure, and culture, and map them to associated research questions. Conclusions: Systematically investigating how software is constructed and its outputs used within science has the potential to improve the robustness of research software and accelerate progress in its development. We propose that this issue be examined within a new research area of theory-software translation, which would aim to significantly advance both knowledge and scientific practice.

Transcriptome Profiling of Beach Morning Glory (Ipomoea imperati) under Salinity and Its Comparative Analysis with Sweetpotato.

The response and adaption to salt remains poorly understood for beach morning glory [Ipomoea imperati (Vahl) Griseb], one of a few relatives of sweetpotato, known to thrive under salty and extreme drought conditions. In order to understand the genetic mechanisms underlying salt tolerance of a Convolvulaceae member, a genome-wide transcriptome study was carried out in beach morning glory by 454 pyrosequencing. A total of 286,584 filtered reads from both salt stressed and unstressed (control) root and shoot tissues were assembled into 95,790 unigenes with an average length of 667 base pairs (bp) and N50 of 706 bp. Putative differentially expressed genes (DEGs) were identified as transcripts overrepresented under salt stressed tissues compared to the control, and were placed into metabolic pathways. Most of these DEGs were involved in stress response, membrane transport, signal transduction, transcription activity and other cellular and molecular processes. We further analyzed the gene expression of 14 candidate genes of interest for salt tolerance through quantitative reverse transcription PCR (qRT-PCR) and confirmed their differential expression under salt stress in both beach morning glory and sweetpotato. The results comparing transcripts of I. imperati against the transcriptome of other Ipomoea species, including sweetpotato are also presented in this study. In addition, 6,233 SSR markers were identified, and an in silico analysis predicted that 434 primer pairs out of 4,897 target an identifiable homologous sequence in other Ipomoea transcriptomes, including sweetpotato. The data generated in this study will help in understanding the basics of salt tolerance of beach morning glory and the SSR resources generated will be useful for comparative genomics studies and further enhance the path to the marker-assisted breeding of sweetpotato for salt tolerance.