Simplifying Control Flow in Compiler-Generated Parallel Code

Optimizing compilers for data-parallel languages such as High Performance Fortran perform a complex sequence of transformations. However, the effects of many transformations are not independent, which makes it challenging to generate high quality code. In particular, some transformations introduce conditional control flow, while others make some conditionals unnecessary by refining program context. Eliminating unnecessary conditional control flow during compilation can reduce code size and remove a source of overhead in the generated code. This paper describes algorithms to compute symbolic constraints on the values of expressions used in control predicates and to use these constraints to identify and remove unnecessary conditional control flow. These algorithms have been implemented in the Rice dHPF compiler and we show that these algorithms are effective in reducing the number of conditionals and the overall size of generated code. Finally, we describe a synergy between control flow simplification and data-parallel code generation based on loop splitting which achieves the effects of more narrow data-parallel compiler optimizations such as vector message pipelining and the use of overlap areas.     

Objective estimation of pain based on facial expression,vital signs and body movements

An intelligent automaton should always arrive at its goal automatically while avoiding the obstacles in a two-dimensional (2D) world. If the automaton does not know the shape or location of any obstacle in the world, it gathers information on its neighbourhood from some sensor, and according to the sensor information, it avoids the closer obstacles. In this situation, a sensor-based path-planning algorithm is used to determine the automaton's action flexibly according to changes in the sensor information. By this method, the automaton usually avoids the closer obstacles on the basis of the local information but it may circulate around some of the obstacles in the world because of the locality of the sensor information. If deadlock occurs, the automaton does not arrive at the goal at all. To overcome this drawback, we address a sufficient condition for designing a family of deadlock-free sensor-based path-planning algorithms in an uncertain world. Within this family, the automaton basically goes straight to the goal. If the automaton occasionally finds a hit point against an unfamiliar obstacle via the touch sensor, it traces the obstacle by touch and in time it finds a way to go straight to the goal again around the obstacle. Even under those conditions the automaton continues to trace the obstacle until its Euclidean distance to the goal is smaller than a distance index which is decreasing asymptotically. This is the sufficient condition, under which the automaton leaves the obstacle to go straight to the goal. This asymptotical approach of the leave point to the goal guarantees that the algorithm family will be deadlock-free. In the family, the automaton always goes straight to the goal if it does not trace any obstacle in the world. Thus, if the leave point comes asymptotically close to the goal, the circular space where the automaton can hit some obstacle in future decreases asymptotically. Therefore the circular space finally goes out of existence and consequently the automaton arrives at the goal. As a result, the family ensures the convergence of the automaton to the goal in an uncertain 2D world.     

Automation for High-throughput Identification and Picking of GFP Expressing Colonies

Green fluorescent protein (GFP) has many applications as a marker in living cells, and has become widely used as a reporter gene in microbial, plant and animal cells. Screening microbial colonies for GFP expression enables various types of assays (e.g. for secretory mutations). However, this is laborious, non-quantitative and potentially hazardous to the operator (due to UV illumination) when performed manually. In order to address this the GloPix robot was developed. The imaging system discriminates between colonies based on the level of fluorescence activity and the picking function automatically transfers cells to microplate wells. Measuring fluorescent activity allows quantitation of fluorescent tag concentration/expression.     

Emotive qualities in lip-synchronized robot speech

This paper explores the expression of emotion in synthesized speech for an anthropomorphic robot. We have adapted several key emotional correlates of human speech to the robot's speech synthesizer to allow the robot to speak in either an angry, calm, disgusted, fearful, happy, sad or surprised manner. We have evaluated our approach thorough acoustic analysis of the speech patterns for each vocal affect and have studied how well human subjects perceive the intended affect. The robot lip synchronizes in real-time to enhance the delivery of its expressive utterances.     

CONCEPTUAL MODELING BASED ON LOGICAL EXPRESSION AND EVOLVEMENT

Aiming at the problem of abstract and polytype information modeling in product conceptual design, a method of conceptual modeling based on logical expression and evolvement is presented. Based on the logic expressions of the product conceptual design information, a function/logic/structure mapping model is set up. First, the function semantics is transformed into logical expressions through function/logic mapping. Second, the methods of logical evolvement are utilized to describe the function analysis, function/structure mapping and structure combination. Last, the logical structure scheme is transformed into geometrical sketch through logic/structure mapping. The conceptual design information and modeling process are described uniformly with logical methods in the model, and an effective method for computer aided conceptual design based on the model is implemented.     

“The Spotting Accelerator™”, Customizable Head Assembly For Advanced Microarraying

Microarraying technologies have emerged as key tools for determining genomic expression. The quality of gene arrays is reliant on spotting pins for production of uniform spots, which are consistent in volume, shape, size and alignment.Point Technologies, Inc., has developed an advanced spotting technology. Emphasis has been placed on producing the “perfect spots” customized to each microarraying application. Uniform surface texturing such as highly polished or matte finishes, and hydrophilic/hydrophobic zonal coating is produced using Point Technologies' proprietary micro-machining technology. Microfabrication also permits the production of advanced pin designs, and high density, high throughput print-head assemblies of 1536 pins and greater. Point Technologies specializes in the micro-electrochemical machining of spotting pins in any size, shape and configuration.Presented data will demonstrate spotting pin design solutions, such as: variety of tip dimensions, surface finishes, specialized coatings, and material options instrumental in producing the ideal spot size, shape and spot density during extended usage.     

Automated in situ hybridisation using Tecan robotics: a kick-start for Functional Genomics

High throughput parallel organic synthesis is now a common practice in discovery chemistry research. Argonaut's modular reaction cassette technology is aimed at parallel synthesis of focused small molecule libraries. The Trident™ automated platform has been designed to perform high throughput organic synthesis using this modular reaction cassette under truly inert conditions and in a robust, reproducible manner. This enables one to generate high quality libraries of small molecules and to access chemistry not normally amenable to automation.Recently we have introduced a Sample Processing Station (SPS), which enhances the upstream and downstream sample handling capabilities of the Trident™ platform. Enhanced software capabilities also provide the Trident™ synthesizer with powerful reaction development and optimization capabilities. Application of this technology in the synthesis of a small library of 1,2-diarylbenzimidazoles using solution-phase chemistry is presented. A number of product purification and isolation protocols using polymer-bound scavengers are discussed.     

Acquisition of multi-modal expression of slip through pick-up experiences

To realize adaptive and robust manipulation, a robot should have several sensing modalities and coordinate their outputs to achieve the given task based on underlying constraints in the real environment. This paper discusses acquisition of multi-modal expression of slip consisting of vibration, pressure and vision sensations through pick-up experiences. A sensor network is proposed to acquire the expression, whose learning ability is demonstrated by a real experiment. The applicability of the learned network is also demonstrated by experiments to realize robust and adaptive picking.