Kerncraft: A Tool for Analytic Performance Modeling of Loop Kernels

Achieving optimal program performance requires deep insight into the interaction between hardware and software. For software developers without an in-depth background in computer architecture, understanding and fully utilizing modern architectures is close to impossible. Analytic loop performance modeling is a useful way to understand the relevant bottlenecks of code execution based on simple machine models. The Roofline Model and the Execution-Cache-Memory (ECM) model are proven approaches to performance modeling of loop nests. In comparison to the Roofline model, the ECM model can also describes the single-core performance and saturation behavior on a multicore chip. We give an introduction to the Roofline and ECM models, and to stencil performance modeling using layer conditions (LC). We then present Kerncraft, a tool that can automatically construct Roofline and ECM models for loop nests by performing the required code, data transfer, and LC analysis. The layer condition analysis allows to predict optimal spatial blocking factors for loop nests. Together with the models it enables an ab-initio estimate of the potential benefits of loop blocking optimizations and of useful block sizes. In cases where LC analysis is not easily possible, Kerncraft supports a cache simulator as a fallback option. Using a 25-point long-range stencil we demonstrate the usefulness and predictive power of the Kerncraft tool.Comment: 22 pages, 5 figure

Counting linear extensions of posets with determinants of hook lengths

We introduce a class of posets, which includes both ribbon posets (skew shapes) and $d$-complete posets, such that their number of linear extensions is given by a determinant of a matrix whose entries are products of hook lengths. We also give $q$-analogues of this determinantal formula in terms of the major index and inversion statistics. As applications, we give families of tree posets whose numbers of linear extensions are given by generalizations of Euler numbers, we draw relations to Naruse-Okada's positive formulas for the number of linear extensions of skew $d$-complete posets, and we give polynomiality results analogous to those of descent polynomials by Diaz-L\'opez, Harris, Insko, Omar, and Sagan

Interferon-γ acutely augments inhibition of neocortical layer 5 pyramidal neurons

BACKGROUND: Interferon-γ (IFN-γ, a type II IFN) is present in the central nervous system (CNS) under various conditions. Evidence is emerging that, in addition to its immunological role, IFN-γ modulates neuronal morphology, function, and development in several brain regions. Previously, we have shown that raising levels of IFN-β (a type I IFN) lead to increased neuronal excitability of neocortical layer 5 pyramidal neurons. Because of shared non-canonical signaling pathways of both cytokines, we hypothesized a similar neocortical role of acutely applied IFN-γ. METHODS: We used semi-quantitative RT-PCR, immunoblotting, and immunohistochemistry to analyze neuronal expression of IFN-γ receptors and performed whole-cell patch-clamp recordings in layer 5 pyramidal neurons to investigate sub- and suprathreshold excitability, properties of hyperpolarization-activated cyclic nucleotide-gated current (Ih), and inhibitory neurotransmission under the influence of acutely applied IFN-γ. RESULTS: We show that IFN-γ receptors are present in the membrane of rat's neocortical layer 5 pyramidal neurons. As expected from this and the putative overlap in IFN type I and II alternative signaling pathways, IFN-γ diminished Ih, mirroring the effect of type I IFNs, suggesting a likewise activation of protein kinase C (PKC). In contrast, IFN-γ did neither alter subthreshold nor suprathreshold neuronal excitability, pointing to augmented inhibitory transmission by IFN-γ. Indeed, IFN-γ increased electrically evoked inhibitory postsynaptic currents (IPSCs) on neocortical layer 5 pyramidal neurons. Furthermore, amplitudes of spontaneous IPSCs and miniature IPSCs were elevated by IFN-γ, whereas their frequency remained unchanged. CONCLUSIONS: The expression of IFN-γ receptors on layer 5 neocortical pyramidal neurons together with the acute augmentation of inhibition in the neocortex by direct application of IFN-γ highlights an additional interaction between the CNS and immune system. Our results strengthen our understanding of the role of IFN-γ in neocortical neurotransmission and emphasize its impact beyond its immunological properties, particularly in the pathogenesis of neuropsychiatric disorders

Empirical ground-motion prediction equations for Northwestern Turkey using the aftershocks of the 1999 Kocaeli earthquake

We present ground motion models for northwestern Turkey using the aftershocks of the Mw 7.4, 1999 Kocaeli earthquake. We consider 4047 velocity and acceleration records for each component of motion, from 528 earthquakes recorded by stations belonging to regional networks. The ground motion models obtained provide peak ground velocity, peak ground acceleration, and spectral accelerations for 8 different frequencies between 1 and 10 Hz. The analysis of the error distribution shows that the record-to-record component of variance is the largest contribution to the standard deviation of the calibrated ground- motion models. Furthermore, a clear dependence of inter-event error on stress drop is observed. The empirical ground-motion prediction equations, derived for both the larger horizontal and vertical components, are valid in the local magnitude range from 0.5 to 5.9, and for hypocentral distances up to 190 km. Citation: Bindi, D., S. Parolai, H. Grosser, C. Milkereit, and E. Durukal (2007), Empirical ground-motion prediction equations for northwestern Turkey using the aftershocks of the 1999 Kocaeli earthquake

Source parameters and seismic moment-magnitude scaling for Northwestern Turkey

Abstract The source parameters of 523 aftershocks (0.5 ML 5.9) of the 1999 Kocaeli earthquake are determined by performing a two-step spectral fitting procedure. The source spectrum, corrected for both site and propagation effects, is described in terms of a standard x-square model multiplied by an exponential term of frequency. The latter term is introduced to estimate the high-frequency (f 12 Hz) fall-off of the acceleration source spectra by computing the j parameter. The seismic moments obtained range between 1.05 1014 and 2.41 1017 N m, whereas the Brune stress drops are between 0.002 and 40 MPa. The j value varies between 0.00 and 0.08 sec, indicating a decay of the acceleration level at the higher frequency part of the spectrum greater than that assumed by the x 2 model. Both the stress drop and the j parameter show the tendency of increasing with aftershock magnitude. No evidence of self-similarity breakdown is observed between the source radius and M0. Finally, both the seismic moment and the moment magnitude are compared with the local magnitude to derive new moment–magnitude relationships for the area

Regularity properties of distributions through sequences of functions

We give necessary and sufficient criteria for a distribution to be smooth or uniformly H\"{o}lder continuous in terms of approximation sequences by smooth functions; in particular, in terms of those arising as regularizations $(T\ast\phi_{n})$.Comment: 10 page

Classes of generalized functions with finite type regularities

We introduce and analyze spaces and algebras of generalized functions which correspond to Hölder, Zygmund, and Sobolev spaces of functions. The main scope of the paper is the characterization of the regularity of distributions that are embedded into the corresponding space or algebra of generalized functions with finite type regularities

Single copy/knock-in models of ALS SOD1 in C. elegans suggest loss and gain of function have different contributions to cholinergic and glutamatergic neurodegeneration

Mutations in Cu/Zn superoxide dismutase 1 (SOD1) lead to Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disease that disproportionately affects glutamatergic and cholinergic motor neurons. Previous work with SOD1 overexpression models supports a role for SOD1 toxic gain of function in ALS pathogenesis. However, the impact of SOD1 loss of function in ALS cannot be directly examined in overexpression models. In addition, overexpression may obscure the contribution of SOD1 loss of function in the degeneration of different neuronal populations. Here, we report the first single-copy, ALS knock-in models in C. elegans generated by transposon- or CRISPR/Cas9- mediated genome editing of the endogenous sod-1 gene. Introduction of ALS patient amino acid changes A4V, H71Y, L84V, G85R or G93A into the C. elegans sod-1 gene yielded single-copy/knock-in ALS SOD1 models. These differ from previously reported overexpression models in multiple assays. In single-copy/knock-in models, we observed differential impact of sod-1 ALS alleles on glutamatergic and cholinergic neurodegeneration. A4V, H71Y, G85R, and G93A animals showed increased SOD1 protein accumulation and oxidative stress induced degeneration, consistent with a toxic gain of function in cholinergic motor neurons. By contrast, H71Y, L84V, and G85R lead to glutamatergic neuron degeneration due to sod-1 loss of function after oxidative stress. However, dopaminergic and serotonergic neuronal populations were spared in single-copy ALS models, suggesting a neuronal-subtype specificity previously not reported in invertebrate ALS SOD1 models. Combined, these results suggest that knock-in models may reproduce the neurotransmitter-type specificity of ALS and that both SOD1 loss and gain of toxic function differentially contribute to ALS pathogenesis in different neuronal populations.Peer reviewe

Parvalbumin interneurons are differentially connected to principal cells in inhibitory feedback microcircuits along the dorso-ventral axis of the medial entorhinal cortex

The medial entorhinal cortex (mEC) shows a high degree of spatial tuning, predominantly grid cell activity, which is reliant on robust, dynamic inhibition provided by local interneurons (INs). In fact, feedback inhibitory microcircuits involving fast-spiking parvalbumin (PV) basket cells (BCs) are believed to contribute dominantly to the emergence of grid cell firing in principal cells (PrCs). However, the strength of PV BC-mediated inhibition onto PrCs is not uniform in this region, but high in the dorsal and weak in the ventral mEC. This is in good correlation with divergent grid field sizes, but the underlying morphologic and physiological mechanisms remain unknown. In this study, we examined PV BCs in layer (L)2/3 of the mEC characterizing their intrinsic physiology, morphology and synaptic connectivity in the juvenile rat. We show that while intrinsic physiology and morphology are broadly similar over the dorsoventral axis, PV BCs form more connections onto local PrCs in the dorsal mEC, independent of target cell type. In turn, the major PrC subtypes, pyramidal cell (PC) and stellate cell (SC), form connections onto PV BCs with lower, but equal probability. These data thus identify inhibitory connectivity as source of the gradient of inhibition, plausibly explaining divergent grid field formation along this dorsoventral axis of the mEC