This document provides an overview of the benchmark ? HPGMG ? for ranking large scale general purpose computers for use on the Top500 list [8]. We provide a rationale for the need for a replacement for the current metric HPL, some background of the Top500 list and the challenges of developing such a metric; we discuss our design philosophy and methodology, and an overview of the specification of the benchmark. The primary documentation with maintained details on the specification can be found at hpgmg.org and the Wiki and benchmark code itself can be found in the repository https://bitbucket.org/hpgmg/hpgmg.

The Kok effect - an abrupt decline in quantum yield (QY) of net CO₂ assimilation at low photosynthetic photon flux density (PPFD) - is widely used to estimate respiration in the light (R), which assumes the effect is caused by light suppression of R. A recent report suggested much of the Kok effect can be explained by declining chloroplastic CO₂ concentration (c_c ) at low PPFD. Several predictions arise from the hypothesis that the Kok effect is caused by declining c_c , and we tested these predictions in Vicia faba. We measured CO₂ exchange at low PPFD, in 2% and 21% oxygen, in developing and mature leaves, which differed greatly in R in darkness. Our results contradicted each of the predictions based on the c_c effect: QY exceeded the theoretical maximum value for photosynthetic CO₂ uptake; QY was larger in 21% than 2% oxygen; and the change in QY at the Kok effect breakpoint was unaffected by oxygen. Our results strongly suggest the Kok effect arises largely from a progressive decline in R with PPFD that includes both oxygen-sensitive and -insensitive components. We suggest an improved Kok method that accounts for high c_c at low PPFD.

Rates of change in intrinsic water use efficiency (W) of trees relative to those in atmospheric [CO₂] (c_a) have been mostly assessed via short-term studies (e.g., leaf analysis, flux analysis) and/or step increases in c_a (e.g., FACE studies). Here we use compiled data for abundances of carbon isotopes in tree stems to show that on decadal scales, rates of change (dW/dc_a) vary with location and rainfall within the global tropics. For the period 1915-1995, and including corrections for mesophyll conductance and photorespiration, dW/dc_a for drier tropical forests (receiving ~ 1000 mm rainfall) were at least twice that of the wettest (receiving ~ 4000 mm). The data also empirically confirm theorized roles of tropical forests in changes in atmospheric ¹³C/¹²C ratios (the ¹³C Suess Effect). Further formal analysis of geographic variation in decade-to-century scale dW/dc_a will be needed to refine current models that predict increases in carbon uptake by forests without hydrological cost.

Calculations of X-ray wave propagation in large objects are needed for modeling diffractive X-ray optics and for optimization-based approaches to image reconstruction for objects that extend beyond the depth of focus. We describe three methods for calculating wave propagation with large arrays on parallel computing systems with distributed memory: (1) a full-array Fresnel multislice approach, (2) a tiling-based short-distance Fresnel multislice approach, and (3) a finite difference approach. We find that the first approach suffers from internode communication delays when the transverse array size becomes large, while the second and third approaches have similar scaling to large array size problems (with the second approach offering about three times the compute speed).

Structured-grid adaptive mesh refinement (SAMR) is an approach to mesh generation that supports structured access to data and adaptive mesh refinement for discretized partial differential equations (PDEs). Solution algorithms often require that an inverse of an operator be applied, a system of algebraic equations must be solved, and this process is often the primary computational cost in an application. SAMR is well suited to geometric multigrid solvers, which can be effective, but often do not adapt well to complex geometry including material coefficients. Algebraic multigrid (AMG) is more robust in the face of complex geometry, in both boundary conditions and internal material interfaces. AMG requires a stored matrix linearization of the operator. We discuss an approach, and an implementation in the Chombo block-structured AMR framework, for constructing composite grid matrices from a SAMR hierarchy of grids for use in linear solvers in the PETSc numerical library. We consider a case study with the Chombo-based BISICLES ice sheet modeling application.

We explored use of Recurrence Quantification Analysis (RQA) of speech rhythm data from mental-health counseling sessions for prediction of quality of psychotherapy. Time-series of inter-syllable intervals (ISIs) were extracted from 239 counseling sessions conducted by 12 therapists who repeatedly interacted with 30 clients. We found a negative association between recurrence metrics and client-rated session quality and a negative link between percent of laminarity and therapist-rated session quality, after controlling for self-reported client depression and distress measures and duration of speech sound within a session. Placing value on reduced recurrence in patterns of ISIs, and especially reduced degree of a dyadic system remaining in the same speech-rhythm pattern may be indicative of a desire for variation in content and strategies of client-therapist interaction. These exploratory findings point to the possibility of RQA-based automated systems to capture the ‘footprint’ of the non-verbal dynamic that is indicative of successful mental-health counseling.

The immersed boundary (IB) method is a widely used approach to simulating fluid-structure interaction (FSI). Although explicit versions of the IB method can suffer from severe time step size restrictions, these methods remain popular because of their simplicity and generality. In prior work (Guy et al., Adv Comput Math, 2015), some of us developed a geometric multigrid preconditioner for a stable semi-implicit IB method under Stokes flow conditions; however, this solver methodology used a Vanka-type smoother that presented limited opportunities for parallelization. This work extends this Stokes-IB solver methodology by developing smoothing techniques that are suitable for parallel implementation. Specifically, we demonstrate that an additive version of the Vanka smoother can yield an effective multigrid preconditioner for the Stokes-IB equations, and we introduce an efficient Schur complement-based smoother that is also shown to be effective for the Stokes-IB equations. We investigate the performance of these solvers for a broad range of material stiffnesses, both for Stokes flows and flows at nonzero Reynolds numbers, and for thick and thin structural models. We show here that linear solver performance degrades with increasing Reynolds number and material stiffness, especially for thin interface cases. Nonetheless, the proposed approaches promise to yield effective solution algorithms, especially at lower Reynolds numbers and at modest-to-high elastic stiffnesses.

A defined set of genetic instructions encodes functionality in complex organisms. Delineating these unique genetic signatures is essential to understanding the formation and functionality of specialized tissues. Vision, one of the five central senses of perception, is initiated by the retina and has evolved over time to produce rod and cone photoreceptors that vary in a species-specific manner, and in some cases by geographical region resulting in higher order visual acuity in humans. RNA-sequencing and use of existing and de novo transcriptome assemblies allowed ocular transcriptome mapping from a diverse set of rodent and primate species. Global genomic refinements along with systems-based comparative and co-expression analyses of these transcriptome maps identified gene modules that correlated with specific features of rod versus cone retinal cellular composition. Organization of the ocular transcriptome demonstrated herein defines the molecular basis of photoreceptor architecture and functionality, providing a new paradigm for neurogenetic analyses of the mammalian retina in health and disease.

Biological nitrogen fixation (BNF) by crop legumes reduces demand for industrial nitrogen fixation (INF). Nonetheless, rates of BNF in agriculture remain low, with strong negative feedback to BNF from reactive soil nitrogen (N) and drought. We show that breeding for yield has resulted in strong relationships between photosynthesis and leaf N in non-leguminous crops, whereas grain legumes show strong relations between leaf N and water use efficiency (WUE). We contrast these understandings with other studies that draw attention to the water costs of grain legume crops, and their potential for polluting the biosphere with N. We propose that breeding grain legumes for reduced stomatal conductance can increase WUE without compromising production or BNF. Legume crops remain a better bet than relying on INF.