BEEBS: Open Benchmarks for Energy Measurements on Embedded Platforms

This paper presents and justifies an open benchmark suite named BEEBS, targeted at evaluating the energy consumption of embedded processors. We explore the possible sources of energy consumption, then select individual benchmarks from contemporary suites to cover these areas. Version one of BEEBS is presented here and contains 10 benchmarks that cover a wide range of typical embedded applications. The benchmark suite is portable across diverse architectures and is freely available. The benchmark suite is extensively evaluated, and the properties of its constituent programs are analysed. Using real hardware platforms we show case examples which illustrate the difference in power dissipation between three processor architectures and their related ISAs. We observe significant differences in the average instruction dissipation between the architectures of 4.4x, specifically 170uW/MHz (ARM Cortex-M0), 65uW/MHz (Adapteva Epiphany) and 88uW/MHz (XMOS XS1-L1)

High-Resolution Spectroscopy of Ursa Major Moving Group Stars

We use new and extant literature spectroscopy to address abundances and membership for UMa moving group stars. We first compare the UMa, Coma, and Hyades H-R diagrams via a homogeneous set of isochrones, and find that these three aggregates are essentially coeval. Our spectroscopy of cool UMa dwarfs reveals striking abundance anomalies--trends with Teff, ionization state, and excitation potential--like those recently seen in young cool M34, Pleaides, and Hyades dwarfs. In particular, the trend of rising 7774 Ang-based OI abundance with declining Teff is markedly subdued in UMa compared to the Pleiades, suggesting a dependence on age or metallicity. Despite disparate sources of Li data,our homogeneous analysis indicates that UMa members evince remarkably small scatter in the Li-Teff plane for Teff>5200 K. Significant star-to-star scatter suggested by previous studies is seen for cooler stars. Comparison with the consistently determined Hyades Li-Teff trend reveals differences qualitatively consistent with this cluster's larger [Fe/H] (and perhaps slightly larger age). However, quantitative comparison with standard stellar models indicates the differences are smaller than expected, suggesting the action of a fourth parameter beyond age, mass, and [Fe/H] controlling Li depletion.Comment: To appear in Publ. Astron. Soc. Pacif. (September 2005

Training Behavior of Sparse Neural Network Topologies

Improvements in the performance of deep neural networks have often come through the design of larger and more complex networks. As a result, fast memory is a significant limiting factor in our ability to improve network performance. One approach to overcoming this limit is the design of sparse neural networks, which can be both very large and efficiently trained. In this paper we experiment training on sparse neural network topologies. We test pruning-based topologies, which are derived from an initially dense network whose connections are pruned, as well as RadiX-Nets, a class of network topologies with proven connectivity and sparsity properties. Results show that sparse networks obtain accuracies comparable to dense networks, but extreme levels of sparsity cause instability in training, which merits further study.Comment: 6 pages. Presented at the 2019 IEEE High Performance Extreme Computing (HPEC) Conference. Received "Best Paper" awar

Fe I and Fe II Abundances of Solar-Type Dwarfs in the Pleiades Open Cluster

We have derived Fe abundances of 16 solar-type Pleiades dwarfs by means of an equivalent width analysis of Fe I and Fe II lines in high-resolution spectra obtained with the Hobby - Eberly Telescope and High Resolution Spectrograph. Abundances derived from Fe II lines are larger than those derived from Fe I lines (herein referred to as over-ionization) for stars with Teff < 5400 K, and the discrepancy (deltaFe = [Fe II/H] - [Fe I/H]) increases dramatically with decreasing Teff, reaching over 0.8 dex for the coolest stars of our sample. The Pleiades joins the open clusters M 34, the Hyades, IC 2602, and IC 2391, and the Ursa Major moving group, demonstrating ostensible over-ionization trends. The Pleiades deltaFe abundances are correlated with Ca II infrared triplet and Halpha chromospheric emission indicators and relative differences therein. Oxygen abundances of our Pleiades sample derived from the high-excitation O I triplet have been previously shown to increase with decreasing Teff, and a comparison with the deltaFe abundances suggests that the over-excitation (larger abundances derived from high excitation lines relative to low excitation lines) and over-ionization effects that have been observed in cool open cluster and disk field main sequence (MS) dwarfs share a common origin. Star-to-star Fe I abundances have low internal scatter, but the abundances of stars with Teff < 5400 K are systematically higher compared to the warmer stars. The cool star [Fe I/H] abundances cannot be connected directly to over-excitation effects, but similarities with the deltaFe and O I triplet trends suggest the abundances are dubious. Using the [Fe I/H] abundances of five stars with Teff > 5400 K, we derive a mean Pleiades cluster metallicity of [Fe/H] = +0.01 +/- 0.02.Comment: 32 pages, 7 figures, 7 tables; accepted by PAS

Action potential energy efficiency varies among neuron types in vertebrates and invertebrates.

The initiation and propagation of action potentials (APs) places high demands on the energetic resources of neural tissue. Each AP forces ATP-driven ion pumps to work harder to restore the ionic concentration gradients, thus consuming more energy. Here, we ask whether the ionic currents underlying the AP can be predicted theoretically from the principle of minimum energy consumption. A long-held supposition that APs are energetically wasteful, based on theoretical analysis of the squid giant axon AP, has recently been overturned by studies that measured the currents contributing to the AP in several mammalian neurons. In the single compartment models studied here, AP energy consumption varies greatly among vertebrate and invertebrate neurons, with several mammalian neuron models using close to the capacitive minimum of energy needed. Strikingly, energy consumption can increase by more than ten-fold simply by changing the overlap of the Na+ and K+ currents during the AP without changing the APs shape. As a consequence, the height and width of the AP are poor predictors of energy consumption. In the Hodgkin–Huxley model of the squid axon, optimizing the kinetics or number of Na+ and K+ channels can whittle down the number of ATP molecules needed for each AP by a factor of four. In contrast to the squid AP, the temporal profile of the currents underlying APs of some mammalian neurons are nearly perfectly matched to the optimized properties of ionic conductances so as to minimize the ATP cost