Data management plan for the grant, "CAREER: Reinventing Network-on-Chips of GPU-Accelerated Systems." Research seeking to reinvent on-chip networks for GPU-accelerated systems to remove a communication bottleneck. A major outcome of the project is a set of techniques that enable the development of effective and efficient network-on-chip architectures. Graphics processing units (GPUs) have rapidly evolved to become high-performance accelerators for data-parallel computing. To fully take advantage of the computing power of GPUs, on-chip networks need to provide timely data movement to satisfy the requests of data by the processing cores. Currently, there exists a big gap between the fast-growing processing power of the GPU processing cores and the slow-increasing on-chip network bandwidth. Because of this, GPU-accelerated systems are interconnect-dominated and the on-chip network becomes their performance bottleneck.

Data management plan for the grant, "Chemical-Guided Identification of Primary Metabolic Targets for Improvement of Hydroxy Fatty Acid Synthesis in Physaria fendleri." Research on the identification of primary metabolic targets using chemical-guided identification. The first objective of this research is to conduct metabolomics analysis on P. fendleri embryos cultured with two identified chemical regulators of fatty acid metabolism. The second objective of this research is to generate a metabolic flux map of embryos treated with these regulatory compounds in order to determine how metabolic rates and carbon flow can be manipulated to improve HFA production in this species and increase its commercial viability. With properties that could replace imported castor oil, research on the crop in discussion is situated directly in the scope of the USDA-AFRI Education and Workforce Development goals.

Data management plan for the grant, "Non-Genetic Inheritance of Hypoxia Tolerance in Fishes: Dynamics and Mechanisms." Research quantifying the inheritance of tolerance to low oxygen in a model fish and then determine the tolerance mechanisms, at organismal to molecular levels, that are passed on from parents to their offspring. The investigators will not only focus on conventional, well-studied genetic mechanisms for inheritance, but will explore so-called “epigenetic” forms of inheritance that may transfer parental characteristics for only a generation or two. Such “temporary inheritance” might actually require less energy and be more beneficial to a species than the more permanent form of genetic inheritance. This project will quantify non-genetic inheritance of hypoxia tolerance in zebrafish as a model organism and then identify underlying mechanisms, at organismal to molecular levels, in parents and in their progeny. Specifically, this project will quantify non-genetically inherited traits that allow hypoxia tolerance, determine “wash-in” and “wash-out” (i.e., the dynamics) of hypoxia-tolerant phenotypes across multiple generations, and establish epigenetic mechanism(s) of non-genetic inheritance in subsequent generations. The information provided by this project will allow biologists to better predict, and perhaps even mitigate, the negative consequences of future episodes of low oxygen in rivers and lakes.

This report describes an accountability framework for artificial intelligence (AI). The framework is organized around four complementary principles and describes key practices for federal agencies and other entities that are considering and implementing AI systems. Each practice includes a set of questions for entities, auditors, and third-party assessors to consider, along with audit procedures and types of evidence for auditors and third-party assessors to collect.