AutoAccel: Automated Accelerator Generation and Optimization with Composable, Parallel and Pipeline Architecture

CPU-FPGA heterogeneous architectures are attracting ever-increasing attention in an attempt to advance computational capabilities and energy efficiency in today's datacenters. These architectures provide programmers with the ability to reprogram the FPGAs for flexible acceleration of many workloads. Nonetheless, this advantage is often overshadowed by the poor programmability of FPGAs whose programming is conventionally a RTL design practice. Although recent advances in high-level synthesis (HLS) significantly improve the FPGA programmability, it still leaves programmers facing the challenge of identifying the optimal design configuration in a tremendous design space. This paper aims to address this challenge and pave the path from software programs towards high-quality FPGA accelerators. Specifically, we first propose the composable, parallel and pipeline (CPP) microarchitecture as a template of accelerator designs. Such a well-defined template is able to support efficient accelerator designs for a broad class of computation kernels, and more importantly, drastically reduce the design space. Also, we introduce an analytical model to capture the performance and resource trade-offs among different design configurations of the CPP microarchitecture, which lays the foundation for fast design space exploration. On top of the CPP microarchitecture and its analytical model, we develop the AutoAccel framework to make the entire accelerator generation automated. AutoAccel accepts a software program as an input and performs a series of code transformations based on the result of the analytical-model-based design space exploration to construct the desired CPP microarchitecture. Our experiments show that the AutoAccel-generated accelerators outperform their corresponding software implementations by an average of 72x for a broad class of computation kernels

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder

Autism spectrum disorder (ASD) encompasses a complex presentation of symptoms that include deficits in social interaction and repetitive or stereotyped interests/behaviors. In keeping with the increasing recognition of both the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate their neural mechanisms based on the functional connectivity of four known neural networks (i.e., the default-mode network, the dorsal attention network, the salience network, and the executive control network)

Evaluation of Effects of Ultrasonic Pretreatment on Biogas Production Potential from Corn Ethanol By-products

This paper reviews the biochemical methane potential (BMP) production from anaerobic digestion of corn-ethanol by-products including dried distiller grain with solubles (DDGS), centrifuge solids, thin stillage, and corn-syrup as well as evaluating the effects of ultrasonic pretreatment on biogas production from these feedstocks. Ultrasonic pretreatment was applied with three amplitude settings of 33% (52.8 µm pp ), 66% (105.6 µm pp ), and 100% (160 µm pp ) as well as five time settings of 10, 20, 30, 40, and 50 seconds, respectively, to each of the four by-products before setting up a bench top BMP trial. Biogas production was measured and analyzed for methane content and accumulated methane production. Without ultrasound pretreatment, corn-syrup had the highest methane production potential (408 ml/g VS added) compare to the other by-products. Methane production was increased by 25 and 12% for the ultrasound pretreated DDGs samples and solids samples, respectively, compared with untreated samples. The ultrasonic pretreatment of ethanol co-products was shown to increase methane production from the anaerobic digestion of these products. The ultrasonic pre-treatment of solids co-products (DDGS and centrifuge solids) was far more effective than on liquid co-products (syrup and thin stillage). An energy balance showed that ultrasonic pretreatment of DDGS provided 70% more energy than was required to operate the ultrasonic unit. An energy balance for other co-products however, indicated that the ultrasonic pre-treatment required more energy than was generated by the process in terms of additional biogas production

Characterization of Ultrasonic Treatment of Ethanol Co-Products for Enhanced Biogas Production

This study evaluates the change in particle size of dry-milling corn ethanol co-products by using ultrasonic energy to increase the production of the biogas from the anaerobic digestion of ethanol dry-milling co-products, namely: dried distiller grain with solubles (DDGS), solids, thin stillage, and corn-syrup. The co-product samples were treated with various ultrasonic conditions and compared to non-treated samples (control sample). The ultrasonic amplitude was varied from 52.8 µm pp to 160 µm pp and the sonication time was varied from 10 to 50s. The samples were characterized with scanning electron and optical microscopy (SEM, OM) and particle distribution analysis (PDA). It was found that with solid/liquid suspensions (DDGS, solids), there was a significant decrease in particle size, increasing the surface area to volume ratio, to possibly enhance biogas yield during anaerobic digestion of these materials. In the case of thin stillage and corn syrup, the results were surprising in that an increase in particle size was seen

Effect of Ultrasonic Pretreatment on Methane Production Potential from Corn Ethanol Coproducts

This article addresses the biochemical methane potential (BMP) production from anaerobic digestion of corn-ethanol coproducts including dried distiller grain with solubles (DDGS), distiller\u27s wet grains (DWG), thin stillage, and condensed distiller\u27s solubles (CDS) as well as evaluating the effects of ultrasonic pretreatment on methane production from these feedstocks. Ultrasonic pretreatment was applied with three amplitude settings of 33% (52.8 µmpp), 66% (105.6 µmpp), and 100% (160 µmpp) as well as five time settings (10, 20, 30, 40, and 50 s) to each of the four coproducts prior to conducting benchtop BMP trials. Ultrasonic pretreatment reduced mean particle size of DDGS and DWG by 45% and 43%, respectively. Without ultrasound pretreatment, CDS had the highest methane production potential (407 mL g-1 VS added) compared to the other coproducts. Ultrasonic pretreatment of DWG co-products (DDGS and DWG) resulted in greater increases in methane production than on liquid coproducts (CDS and thin stillage). Methane yields were increased by 25% and 12% for the ultrasound pretreated DDGS and DWG, respectively, compared with untreated samples. An energy balance for the DWG, thin stillage, and CDS coproducts indicated that ultrasonic pretreatment required more energy than was generated by the process in terms of additional biogas production. However, an energy balance for ultrasonic pretreatment of DDGS provided 70% more energy than was required to operate the ultrasonic unit

Neurogenesis is enhanced by stroke in multiple new stem cell niches along the ventricular system at sites of high BBB permeability

AbstractPrevious studies have established the subventricular (SVZ) and subgranular (SGZ) zones as sites of neurogenesis in the adult forebrain (Doetsch et al., 1999a; Doetsch, 2003a). Work from our laboratory further indicated that midline structures known as circumventricular organs (CVOs) also serve as adult neural stem cell (NSC) niches (Bennett et al., 2009, 2010). In the quiescent rat brain, NSC proliferation remains low in all of these sites. Therefore, we recently examined whether ischemic stroke injury (MCAO) or sustained intraventricular infusion of the mitogen bFGF could trigger an up-regulation in NSC proliferation, inducing neurogenesis and gliogenesis. Our data show that both stroke and bFGF induce a dramatic and long-lasting (14day) rise in the proliferation (BrdU+) of nestin+Sox2+GFAP+ NSCs capable of differentiating into Olig2+ glial progenitors, GFAP+nestin-astrocyte progenitors and Dcx+ neurons in the SVZ and CVOs. Moreover, because of the upsurge in NSC number, it was possible to detect for the first time several novel stem cell niches along the third (3V) and fourth (4V) ventricles. Importantly, a common feature of all brain niches was a rich vasculature with a blood–brain-barrier (BBB) that was highly permeable to systemically injected sodium fluorescein. These data indicate that stem cell niches are more extensive than once believed and exist at multiple sites along the entire ventricular system, consistent with the potential for widespread neurogenesis and gliogenesis in the adult brain, particularly after injury. We further suggest that because of their leaky BBB, stem cell niches are well-positioned to respond to systemic injury-related cues which may be important for stem-cell mediated brain repair

Responses of Extreme Discharge to Changes in Surface-Air and Dewpoint Temperatures in Utah: Seasonality and Mechanisms

The changes in stream discharge extremes due to temperature and seasonality are key metrics in assessing the effects of climate change on the hydrological cycle. While scaling is commonly applied to temperature and precipitation due to the physical connections between temperature and moisture (i.e., Clausius–Clapeyron), the scaling rate of stream discharge extremes to air and dewpoint temperatures has not been evaluated. To address this challenge, we assess the scaling rates between stream discharge and air temperature and between stream discharge and dewpoint temperature in Utah using a well-designed statistical framework. While there are deviations from the Clausius–Clapeyron (CC) relationship in Utah using discharge data based on stream gauges and gridded climate data, we identify positive scaling rates of extreme discharge to temperatures across most of the state. Further diagnosis of extreme discharge events reveals that regional factors combined with topography are responsible for the marked seasonality of scaling, with most areas of Utah driven by spring snowmelt tied to high temperatures. The exception is far southwestern areas, being largely driven by winter rain-on-snow events. Our research highlights a measurable portion of stream discharge extremes associated with higher temperatures and dewpoints, suggesting that climate change could facilitate more extreme discharge events despite reductions to mean flows

Observation of Quantum Effects in sub Kelvin Cold Reactions

There has been a long-standing quest to observe chemical reactions at low temperatures where reaction rates and pathways are governed by quantum mechanical effects. So far this field of Quantum Chemistry has been dominated by theory. The difficulty has been to realize in the laboratory low enough collisional velocities between neutral reactants, so that the quantum wave nature could be observed. We report here the first realization of merged neutral supersonic beams, and the observation of clear quantum effects in the resulting reactions. We observe orbiting resonances in the Penning ionization reaction of argon and molecular hydrogen with metastable helium leading to a sharp increase in the absolute reaction rate in the energy range corresponding to a few degrees kelvin down to 10 mK. Our method is widely applicable to many canonical chemical reactions, and will enable a breakthrough in the experimental study of Quantum Chemistry

Stochastic modeling of superconducting qudits in the dispersive regime

The field of superconducting quantum computing, based on Josephson junctions, has recently seen remarkable strides in scaling the number of logical qubits. In particular, the fidelities of one- and two-qubit gates have reached the breakeven point with the novel error mitigation and correction methods. Parallel to these advances is the effort to expand the Hilbert space within a single junction or device by employing high-dimensional qubits, otherwise known as qudits. Research has demonstrated the possibility of driving higher-order transitions in a transmon or designing innovative multimode superconducting circuits, termed multimons. These advances can significantly expand the computational basis while simplifying the interconnects in a large-scale quantum processor. In this work we extend the measurement theory of a conventional superconducting qubit to that of a qudit, focusing on modeling the dispersive quadrature measurement in an open quantum system. Under the Markov assumption, the qudit Lindblad and stochastic master equations are formulated and analyzed; in addition, both the ensemble-averaged and the quantum-jump approach of decoherence analysis are detailed with analytical and numerical comparisons. We verify our stochastic model with a series of experimental results on a transmon-type qutrit, verifying the validity of our high-dimensional formalism.Comment: 16-page main text, 6 figures, 15-page appendice