Loom: Exploiting Weight and Activation Precisions to Accelerate Convolutional Neural Networks

Loom (LM), a hardware inference accelerator for Convolutional Neural Networks (CNNs) is presented. In LM every bit of data precision that can be saved translates to proportional performance gains. Specifically, for convolutional layers LM's execution time scales inversely proportionally with the precisions of both weights and activations. For fully-connected layers LM's performance scales inversely proportionally with the precision of the weights. LM targets area- and bandwidth-constrained System-on-a-Chip designs such as those found on mobile devices that cannot afford the multi-megabyte buffers that would be needed to store each layer on-chip. Accordingly, given a data bandwidth budget, LM boosts energy efficiency and performance over an equivalent bit-parallel accelerator. For both weights and activations LM can exploit profile-derived perlayer precisions. However, at runtime LM further trims activation precisions at a much smaller than a layer granularity. Moreover, it can naturally exploit weight precision variability at a smaller granularity than a layer. On average, across several image classification CNNs and for a configuration that can perform the equivalent of 128 16b x 16b multiply-accumulate operations per cycle LM outperforms a state-of-the-art bit-parallel accelerator [1] by 4.38x without any loss in accuracy while being 3.54x more energy efficient. LM can trade-off accuracy for additional improvements in execution performance and energy efficiency and compares favorably to an accelerator that targeted only activation precisions. We also study 2- and 4-bit LM variants and find the the 2-bit per cycle variant is the most energy efficient

Modelling Subglacial Hydrology under Future Climate Scenarios in Wilkes Subglacial Basin, Antarctica

The Greenland and Antarctic ice sheets have differing climates, which makes surface melt a significant hydrological source in Greenland but not currently in Antarctica. Due to a changing climate and warming air temperatures, Antarctica is predicted to experience more surface meltwater in the future. This will likely lead to surface features common in Greenland today, such as supraglacial lakes and moulins, to also form over grounded ice in Antarctica. Moulins in particular are important because they will route this surface melt into basal drainage networks. The resulting change in subglacial drainage characteristics and water volumes will potentially have far-reaching impacts on ice dynamics, ice shelf melt, grounding line stability, and ultimately global sea level rise. To examine this, we model the hydrological system in Wilkes Subglacial Basin, East Antarctica using estimations of the future climate to incorporate moulins and surface melt. We use predictive data generated by the Community Climate System Model 4 (CCSM4) for surface runoff in Antarctica for the year 2100 as inputs to the Glacier Drainage System (GlaDS) subglacial hydrology model. We compare the modelling results from two different Representative Concentration Pathway (RCP) scenarios, RCP 2.6 and RCP 8.5. Moulin locations are predicted using current strain rates along preferential surface hydrology flow pathways and we also compare modelling results with different numbers and locations of moulins. We find that an increase in surface water input from none to RCP 2.6 to RCP 8.5 has a larger impact on basal drainage rates, channel extent, and water pressure near the grounding line. However, compared to increasing surface water inputs, we also find that increasing the number and extent of moulins can have an even larger impact on the subglacial hydrology system. This shows that both moulin formation and the evolution of the climate will play a role in the development of the subglacial hydrology system, which will be important for future ice flow speeds and ice shelf melt rates near the grounding line

STL: Surprisingly Tricky Logic (for System Validation)

Much of the recent work developing formal methods techniques to specify or learn the behavior of autonomous systems is predicated on a belief that formal specifications are interpretable and useful for humans when checking systems. Though frequently asserted, this assumption is rarely tested. We performed a human experiment (N = 62) with a mix of people who were and were not familiar with formal methods beforehand, asking them to validate whether a set of signal temporal logic (STL) constraints would keep an agent out of harm and allow it to complete a task in a gridworld capture-the-flag setting. Validation accuracy was $45\% \pm 20\%$ (mean $\pm$ standard deviation). The ground-truth validity of a specification, subjects' familiarity with formal methods, and subjects' level of education were found to be significant factors in determining validation correctness. Participants exhibited an affirmation bias, causing significantly increased accuracy on valid specifications, but significantly decreased accuracy on invalid specifications. Additionally, participants, particularly those familiar with formal methods, tended to be overconfident in their answers, and be similarly confident regardless of actual correctness. Our data do not support the belief that formal specifications are inherently human-interpretable to a meaningful degree for system validation. We recommend ergonomic improvements to data presentation and validation training, which should be tested before claims of interpretability make their way back into the formal methods literature

901-11 Late Clinical and Echocardiographic Follow-up After Left Ventricular Endoaneurysmorrhaphy

Infarct expansion and aneurysm (LVA) formation has a poor prognosis. Traditional techniques of LVA resection may be associated with suboptimal results, and do not fully restore LV geometry. LV endoaneurysmorrhaphy(LVEA) is a newer operative technique which utilizes an endocardial patch to exclude the aneurysm and normalize LV geometry. Late clinical and echocardiographic features of these patients (pts) is unknown. We prospectively followed 51 consecutive pts who had undergone LVEA. Average duration of follow-up (F/U) was 4.6 years (range 2-10 years). All pts had clinical evaluation and review of medical records.ResultsThere were 2 (4%) peri-operative deaths, 2 (4%) in-hospital deaths, and 13 (24%) late deaths. Clinical improvement was noted in all 34 survivors:NYHAClassPre-opF/UCCSPre-opF/Un(%)n(%)n(%)n(%)I5(15)21(62)I12(35)29(85)II9(26)8(24)II3(9)5(15)III13(38)4(12)III5(15)0IV7(21)1(3)IV14(41)030 surviving pts had F/U 2D echocardiograms (2DE). Near normal LV geometry was restored in all pts, and no patch aneurysms were noted at late F/U. 24/30 2DEs were adequate for quantitative analysis. The average LVEF post-op was 40.2% using the modified biplane analysis.ConclusionsLV endoaneurysmorrhaphy was associated with a 72% overall survival after average 4.6 year F/U. All survivors had improvement in clinical status and normalization of LV geometry

Fluorescent Si Nanoparticle-Based Electrode for Sensing Biomedical Substances

We have been studying the miniaturization of silicon crystals and the transition from the solid state to the atomistic state. We demonstrated the existence of “sweet spots” in cluster size in the range 1–3nm that have enhanced chemical, structural, and photo stability. The particles are produced by an electrochemical etching process as dispersion in liquid, and they are reconstituted in films, patterns, alloys, or spread on chips to produce super chips. Unlike bulk, these Si nanoparticle configurations have a spectacular ability to glow in distinct RGB colors. In this paper we describe an electrode sensor built by decorating metal or heavily doped silicon electrode with nanoparticles. We demonstrated amperometric response of the electrode to glucose and compared the response to that of heavily doped silicon wafer decorated with GOx. The all silicon electrode shows improved sensitivity, selectivity and stability. Light induced modulation of the response allows phase sensitive detection. The device is suitable for miniaturization, which may enable in vivo use

Canby School District: Enrollment Forecast Update 2012-13 to 2021-22

The Population Research Center (PRC) has prepared district‐wide and individual school Enrollment Forecasts for the Canby School District (CSD) annually for the past six years. This study includes forecasts of district‐wide enrollment for the 10 years from 2012‐13 to 2021‐22 and forecasts for individual schools for the five years from 2012‐13 to 2016‐17. The 10 year horizon of the district‐wide forecast enhances opportunities for school districts to coordinate long range planning with city and county comprehensive plans, which may extend for 20 or more years. Overall K‐12 enrollment is forecast to increase by 364 students (8 percent) in the next 10 years. K‐12 enrollment loss of three students (0.1 percent) is forecast for 2012‐13 and only moderate growth, averaging 0.8 percent, is forecast for the remaining nine years of the forecast. K‐6 enrollments begin to grow gradually after 2012‐13, but grades 7‐8 enrollments remain flat or decline until 2017‐18, begin to grow in between 2017‐18 and 2019‐20, and decline slightly in the last two years of the forecast horizon. High school enrollment changes very little throughout the 10 year forecast period

Eagle Point School District Enrollment Forecasts 2014-15 to 2023-24

This report presents the results of a demographic study conducted by the Portland State University Population Research Center. The study includes analyses of population, housing and enrollment trends affecting the Eagle Point School District (EPSD) in recent years, forecasts of district‐wide enrollment by grade level and total enrollment of individual schools for the 2014‐ 15 to 2023‐24 school years

Efficient assembly and secretion of recombinant subviral particles of the four dengue serotypes using native prM and E proteins.

© 2009 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Flavivirus infected cells produce infectious virions and subviral particles, both of which are formed by the assembly of prM and E envelope proteins and are believed to undergo the same maturation process. Dengue recombinant subviral particles have been produced in cell cultures with either modified or chimeric proteins but not using the native forms of prM and E. Methodology/Principal Findings: We have used a codon optimization strategy to obtain an efficient expression of native viral proteins and production of recombinant subviral particles (RSPs) for all four dengue virus (DV) serotypes. A stable HeLa cell line expressing DV1 prME was established (HeLa-prME) and RSPs were analyzed by immunofluorescence and transmission electron microscopy. We found that E protein is mainly present in the endoplasmic reticulum (ER) where assembly of RSPs could be observed. Biochemical characterization of DV1 RSPs secretion revealed both prM protein cleavage and homodimerization of E proteins before their release into the supernatant, indicating that RSPs undergo a similar maturation process as dengue virus. Pulse chase experiment showed that 8 hours are required for the secretion of DV1 RSPs. We have used HeLa-prME to develop a semi-quantitative assay and screened a human siRNA library targeting genes involved in membrane trafficking. Knockdown of 23 genes resulted in a significant reduction in DV RSP secretion, whereas for 22 others we observed an increase of RSP levels in cell supernatant. Conclusions/Significance: Our data describe the efficient production of RSPs containing native prM and E envelope proteins for all dengue serotypes. Dengue RSPs and corresponding producing cell lines are safe and novel tools that can be used in the study of viral egress as well as in the development of vaccine and drugs against dengue virus.This work was supported by the 6th European Framework programme DENFRAME and by the Research Fund for the Control of Infectious Diseases of Hong Kong (RFCID#08070952)