Costing JIT Traces

Tracing JIT compilation generates units of compilation that are easy to analyse and are known to execute frequently. The AJITPar project aims to investigate whether the information in JIT traces can be used to make better scheduling decisions or perform code transformations to adapt the code for a specific parallel architecture. To achieve this goal, a cost model must be developed to estimate the execution time of an individual trace. This paper presents the design and implementation of a system for extracting JIT trace information from the Pycket JIT compiler. We define three increasingly parametric cost models for Pycket traces. We perform a search of the cost model parameter space using genetic algorithms to identify the best weightings for those parameters. We test the accuracy of these cost models for predicting the cost of individual traces on a set of loop-based micro-benchmarks. We also compare the accuracy of the cost models for predicting whole program execution time over the Pycket benchmark suite. Our results show that the weighted cost model using the weightings found from the genetic algorithm search has the best accuracy

Non-standard liquidity measures and international interbank term structure dynamics

Throughout the financial crisis central banks experienced a situation where standard monetary measures failed to create stability and restore growth to the financial markets and the overall economy. Therefore new response methods where introduced. One of the key responses was to extend longer maturity loans through auctions supported by a wider range of collateral (The Term Auction Facility or TAF program). In the aftermath of the crisis in financial markets the effect of this monetary measure has been widely discussed. A key topic of interest is how it affected the term structure of interbank interest rates and whether it restored access to liquidity for financial institutions. In this thesis we develop and apply three statistical tests to study if the TAF had the intended effect on US interbank rates, and whether or not spillover effects to other markets have been seen as well. First we compute the frequency of a directional move following term auctions, and compare this with the frequency in the overall financial crisis. Then we compute the expected size in such a move following auction dates, and compare expected sizes in such moves during the rest of the financial crisis. Third we use an event study to look for abnormal movements following auction dates. Here we estimate an affine term structure model driven by a vector autoregressive model with the credit premium, liquidity premium and short rate as driving factors in an affine term structure model. The thesis has four major findings; First, we find that the probability of drops in interbank interest rates and spreads tended to be more likely and larger in size following the notification of information regarding the results of TAF-auctions. Second, the Term Auction Facility caused international spillover effects which varied from market to market. Specifically we found that unsecured loans with more than 5 months to maturity became less expensive compared to unsecured loans with less than 5 months to maturity. These results were found in the UK and EU, and were highly significant. The same results indicate that interest rate levels tended to fall, but these results were not significant. Third, interest rates on loans with more than 4 months to maturity dropped more than what could be expected, even when credit and liquidity factors could be perfectly predicted. This suggests that the results from TAF-auctions went a long way in reducing premiums on unsecured loans in the interbank marked with longer maturities (5-12 months). Last, the Term Auction Facility seem to have pulled down premiums on credit and liquidity beyond what could be expected following the notification of results from the TAF auctions. These effects were seen to spill over to the settlement day as well

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

Research has shown that convolutional neural networks contain significant redundancy, and high classification accuracy can be obtained even when weights and activations are reduced from floating point to binary values. In this paper, we present FINN, a framework for building fast and flexible FPGA accelerators using a flexible heterogeneous streaming architecture. By utilizing a novel set of optimizations that enable efficient mapping of binarized neural networks to hardware, we implement fully connected, convolutional and pooling layers, with per-layer compute resources being tailored to user-provided throughput requirements. On a ZC706 embedded FPGA platform drawing less than 25 W total system power, we demonstrate up to 12.3 million image classifications per second with 0.31 {\mu}s latency on the MNIST dataset with 95.8% accuracy, and 21906 image classifications per second with 283 {\mu}s latency on the CIFAR-10 and SVHN datasets with respectively 80.1% and 94.9% accuracy. To the best of our knowledge, ours are the fastest classification rates reported to date on these benchmarks.Comment: To appear in the 25th International Symposium on Field-Programmable Gate Arrays, February 201

Cross-conjugated 2,5-cyclohexadienone and related synthesis methods

The present invention relates to methods for the synthesis of galanthamine, morphine, intermediates, salts and derivatives thereof. In preferred embodiments, the invention relates to methods for improving the efficiency and overall yield of said morphine, morphine related derivatives and intermediates thereof. In further embodiments, the invention relates to methods for improving the efficiency and overall yield of galanthamine and intermediates thereof.Board of Regents, University of Texas Syste

Structure Of 18'-Epivinblastine

Methyl {3aR-[3a-alpha,4-beta,5-beta,5a-beta,9(3R*,-5S*,7R*,9R*),10bR,13a-alpha]}-4-(acetyloxy)-3a-ethyl-9-[5-ethyl-1,4,5,6,7,8,9,10-octahydro-5-hydroxy-9-(methoxycarbonyl)-2H-3,7-methanoazacycloundecino[5,4-b]indol-9-yl]-3a,4,5,5a,6,11,12,13a-octahydro-5-hydroxy-8-methoxy-6-methyl-lH-indolizino-[8,1-c,d]carbazole-5-carboxy?? late methanol solvate, C46H58N4O9.2CH3OH (1), M(r) = 875.07, monoclinic, P2(1), a = 10.2759 (12), b = 22.353 (3), c = 10.4051 (12) angstrom, beta = 106.502 (9)-degrees, V = 2291.6 (5) angstrom 3, Z = 2, D(x) = 1.27 g cm-3, Mo K-alpha radiation, lambda = 0.7107 angstrom, mu = 0.8397 cm-1, F(000) = 940, T = 198 K, R = 0.0470 for 2751 reflections, F(o) greater-than-or-equal-to 4-sigma-(F(o)). The C ring of the vindoline moiety is in the boat conformation with the hydroxy group and the tertiary N in the bowsprit positions resulting in a fairly short intramolecular hydrogen-bonding interaction. The relevant parameters for O3-H3...N9 are O...N 2.651 (6), H...N 1.94 (5) angstrom and O-H...N 147 (5)-degrees. The D and E rings are in the sofa and envelope conformations, respectively. The piperidine ring of the catharanthine portion of the molecule assumes the chair conformation while the conformation of the azacyclononene ring is a boat-chair. An intramolecular hydrogen bond between the indolino NH of the catharanthine moiety and methoxy O (O25) of the vindoline moiety is also observed. The relevant parameters for N16'-H16'...O25 are N...O 2.827 (6), H...N2.14 (6) angstrom and O-H...N 136 (5)-degrees.National Institutes of Health (GM 29801)ChemistryBiochemistr

Tensile properties of the transverse carpal ligament and carpal tunnel complex

A new sophisticated method that uses video analysis techniques together with a Maillon Rapide Delta to determine the tensile properties of the transverse carpal ligament–carpal tunnel complex has been developed. Six embalmed cadaveric specimens amputated at the mid-forearm and aged (mean (SD)): 82 (6.29) years were tested. The six hands were from three males (four hands) and one female (two hands). Using trigonometry and geometry the elongation and strain of the transverse carpal ligament and carpal arch were calculated. The cross-sectional area of the transverse carpal ligament was determined. Tensile properties of the transverse carpal ligament–carpal tunnel complex and Load–Displacement data were also obtained. Descriptive statistics, one-way ANOVA together with a post-hoc analysis (Tukey) and t-tests were incorporated. A transverse carpal ligament–carpal tunnel complex novel testing method has been developed. The results suggest that there were no significant differences between the original transverse carpal ligament width and transverse carpal ligament at peak elongation (P= 0.108). There were significant differences between the original carpal arch width and carpal arch width at peak elongation (P=0.002). The transverse carpal ligament failed either at the mid-substance or at their bony attachments. At maximum deformation the peak load and maximum transverse carpal ligament displacements ranged from 285.74 N to 1369.66 N and 7.09 mm to 18.55 mm respectively. The transverse carpal ligament cross-sectional area mean (SD) was 27.21 (3.41)mm2. Using this method the results provide useful biomechanical information and data about the tensile properties of the transverse carpal ligament–carpal tunnel complex

Modulation der DNA-Mechanik durch Methylierung und Transkriptionsfaktoren

Genregulation gibt der Zelle die Kontrolle über Struktur und Funktion, und ist die Basis für zelluläre Differenzierung, Morphogenese und die Vielseitigkeit und Anpassungsfähigkeit von jedem Organismus. Um zu begreifen, wie eine Zelle ihre Funktion organisiert und wie sich ganz individuelle Organismen ausbilden, obwohl die gleichen genetischen Informationen vorhanden sind, muss man die Regulation der Genexpression im Detail verstehen. Diese Regulation wirkt an verschiedenen Stellen der Genexpression und besteht aus einer Vielzahl von komplexen Prozessen, die untereinander verbunden sind. Somit ist das Verständnis der zugrundeliegenden molekularen Mechanismen und ihres Zusammenspiels für Biologie und Biophysik von großer Bedeutung. Ziel dieser Arbeit ist die Untersuchung von Wechselwirkungen und Wechselwirkungskräften zwischen Biomolekülen, die an der Genregulation und der Epigenetik, auf der Ebene der Transkription beteiligt sind. Insbesondere konnten Protein-DNA-Wechselwirkungen und der Einfluss epigenetischer DNA-Modifikationen quantifiziert werden. Für die Messungen wurde ein molekularer Kraftsensor und als dessen Erweiterung ein molekularer Analog-Digital-Wandler entwickelt. Diese molekularen Sensoren ermöglichen die direkte Messung der Wechsel- wirkungskräfte zwischen DNA und Liganden. Mit dem molekularen Kraftsensor können außerdem hochparallel Messungen durchgeführt werden, wobei durch den symmetrischen, molekularen Aufbau zudem eine sehr hohe Sensitivität erreicht wird. Die Verwendung dieser Methode ermöglichte es, den Einfluss der epigenetisch modifizierten Basen Methylcytosin und Hydroxymethylcytosin („5. und 6. Base der DNA“) auf die mechanische Stabilität der DNA- Doppelhelix zu untersuchen. Es wird gezeigt, dass mit dem aus DNA-Oligomeren aufgebauten molekularen Kraftsensor Protein-DNA-Wechselwirkungen detektiert und deren Dissoziationskonstanten bestimmt werden können. Unter anderem wird die Wechselwirkung der Endonuklease EcoRI mit ihrer DNA- Erkennungssequenz quantifiziert. Hierfür wurden molekulare Kraftsensoren in Zipper- und Scher-Geometrie entworfen. Bei dem neu entwickelten Aufbau des Kraftsensors mit integriertem Förster-Resonanzenergietransfer-Farbstoffpaar genügt schon eine Fläche von 25 !m2, um die Stärke von Ligand-DNA-Wechselwirkungen bestimmen zu können. Diese Fläche liegt deutlich unterhalb der Messfleckgröße aktueller DNA-Mikroarrays. Damit erfüllt der molekulare Kraftsensor bezüglich der Messfleckdichte die Voraussetzung für moderne Hochdurchsatz- Methoden. In einem zweiten Schritt wird der molekulare Kraftsensor zu einem „molekularen Analog- Digital-Wandler“ erweitert. In Analogie zum elektronischen Flash-Analog-Digital-Wandler, bei dem mehrere Komparatoren mit unterschiedlichen Referenzschaltungen parallel geschaltet sind, werden beim molekularen Analog-Digital-Wandler parallel räumlich getrennte, molekulare Kraftsensoren mit unterschiedlich stabilen Referenz-Wechselwirkungen zur Bestimmung einer unbekannten molekularen Wechselwirkung verwendet. Durch eine Kompensationsmessung wird dann die Kraft von Ligand-DNA-Wechselwirkungen bestimmt. Es werden die Wechsel- wirkungen eines Pyrrol-Imidazol Hairpin-Polyamides, der Endonuklease EcoRI und des Transkriptionsfaktors p53 zur jeweiligen DNA-Erkennungssequenz vermessen. Eine hoch- parallele Version mit Messfleckgrößen mit einem Durchmesser von minimal 15 !m konnte realisiert werden. Abgeleitet vom Bell-Evans-Modell wurde ein analytisches Modell zur Beschreibung des molekularen Analog-Digital-Wandlers entwickelt. Neben den Protein-DNA-Wechselwirkungen werden die epigenetisch modifizierten DNA- Basen Methylcytosin (mC) und Hydroxymethylcytosin (hmC) untersucht. Es wird der Nachweis erbracht, dass sich die mechanische Stabilität der DNA-Doppelhelix bei Separation in zwei Einzelstränge in beiden Fällen signifikant um mehrere Pikonewton ändert. Die Stärke des Effekts ist abhängig von der DNA-Sequenz und der Richtung der angelegten Kraft. Durch Einzelmolekül-Kraftspektroskopie wird eine Reduzierung der Potentialweite durch mC aufgezeigt. Außerdem konnte mit Hilfe von Molekulardynamik-Simulationen der Effekt für mC und teilweise auch für hmC auf molekularer Ebene aufgeklärt werden. Es wird ein Modell entwickelt, das erklärt, wie dieser Effekt einen Einfluss auf die Genregulation ausüben kann

Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures

Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast database comprising 90,000 microstructures drawn from nine different stochastic models, and compute their effective diffusivity and permeability as well as various microstructural descriptors. To the best of our knowledge, this is the largest and most diverse dataset created for studying the influence of 3D microstructure on mass transport. In particular, we establish microstructure-property relationships using analytical prediction formulas, artificial (fully-connected) neural networks, and convolutional neural networks. Again, to the best of our knowledge, this is the first time that these three statistical learning approaches are quantitatively compared on the same dataset. The diversity of the dataset increases the generality of the determined relationships, and its size is vital for robust training of convolutional neural networks. We make the 3D microstructures, their structural descriptors and effective properties, as well as the code used to study the relationships between them available open access

MAES:a ROS 2-compatible simulation tool for exploration and coverage algorithms

With the aim of allowing the efficient and realistic simulation of swarm algorithms for exploration and coverage, we present the tool Multi-Agent Exploration Simulator (MAES), which is an open-source physics-based discrete step multi-robot simulator. MAES features movement in a continuous 2D space, realistic physics based on the Unity framework, advanced visualization techniques such as heatmaps, custom wireless signal degradation, both randomly generated and custom user-provided maps, and a ROS (Robot Operating System) interface. This latter characteristic could allow to port the simulated algorithms to real-world robots. We present performance tests, conducted with rather modest hardware, showing that MAES is able to simulate up to 5 robots in ROSMode (using the ROS integration) and up to 120 robots in UnityMode (development performed directly into the C# Unity Editor). A usability test was conducted which hinted that the target audience of robotics researchers and developers is able to quickly install, setup, and use MAES for implementing simple robot logic.</p