The classification, fusion, and parallelization of array languageprimitives

We present a classification scheme for array language primitives that quantifies the variation in parallelism and data locality that results from the fusion of any two primitives. We also present an algorithm based on this scheme that efficiently determines when it is beneficial to fuse any two primitives. Experimental results show that five LINPACK routines report 50% performance improvement from the fusion of array operators     

Unicast-based multicast communication in wormhole-routed networks

Multicast communication, in which the same message is delivered from a source node to an arbitrary number of destination nodes, is being increasingly demanded in parallel computing. System supported multicast services can potentially offer improved performance, increased functionality, and simplified programming, and may in turn be used to support various higher-level operations for data movement and global process control. This paper presents efficient algorithms to implement multicast communication in wormhole-routed direct networks, in the absence of hardware multicast support, by exploiting the properties of the switching technology. Minimum-time multicast algorithms are presented for n-dimensional meshes and hypercubes that use deterministic, dimension-ordered routing of unicast messages. Both algorithms can deliver a multicast message to m-1 destinations in [log ₂ m] message passing steps, while avoiding contention among the constituent unicast messages. Performance results of implementations on a 64-node nCUBE-2 hypercube and a 168-node Symult 2010 2-D mesh are given     

Quantization effects in digitally behaving circuit implementationsof Kohonen networks

Implementing a neural network on a digital or mixed analog and digital chip yields the quantization of the synaptic weights dynamics. This paper addresses this topic in the case of Kohonen's self-organizing maps. We first study qualitatively how the quantization affects the convergence and the properties, and deduce from this analysis the way to choose the parameters of the network (adaptation gain and neighborhood). We show that a spatially decreasing neighborhood function is far more preferable than the usually rectangular neighborhood function, because of the weight quantization. Based on these results, an analog nonlinear network, integrated in a standard CMOS technology, and implementing this spatially decreasing neighborhood function is then presented. It can be used in a mixed analog and digital circuit implementation.     

The design, fabrication, and testing of corrugated silicon nitridediaphragms

Silicon nitride corrugated diaphragms of 2 mm×2 mm×1 μm have been fabricated with 8 circular corrugations, having depths of 4, 10, or 14 μm. The diaphragms with 4-μm-deep corrugations show a measured mechanical sensitivity (increase in the deflection over the increase in the applied pressure) which is 25 times larger than the mechanical sensitivity of flat diaphragms of equal size and thickness. Since this gain in sensitivity is due to reduction of the initial stress, the sensitivity can only increase in the case of diaphragms with initial stress. A simple analytical model has been proposed that takes the influence of initial tensile stress into account. The model predicts that the presence of corrugations increases the sensitivity of the diaphragms, because the initial diaphragm stress is reduced. The model also predicts that for corrugations with a larger depth the sensitivity decreases, because the bending stiffness of the corrugations then becomes dominant. These predictions have been confirmed by experiments. The application of corrugated diaphragms offers the possibility to control the sensitivity of thin diaphragms by geometrical parameters, thus eliminating the effect of variations in the initial stress, due to variations in the diaphragm deposition process and/or the influence of temperature changes and packaging stress     

First break refraction event picking using fuzzy logic systems

First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen     

A coverage plan for health centres in Murewa district in Zimbabwe: an example of action research

Good access to health facilities providing good first-level health care remains problematic in many developing countries. It is a hindrance to effective and efficient functioning of the hospital, as outpatient departments become overcrowded with patients from areas without health centres. In many cases the quality of care delivered to these patients is poor because within the district health system the hospital is not the best place for the supply of comprehensive, integrated and continuous care. Eventually, high hospital involvement in first-level care can jeopardize the delivery of adequate referral care for those patients who desperately need the hospital's technology and expertise. This paper provides an account of the way this problem was investigated and managed by the district health management team in the Murewa district in north-east Zimbabwe. The design of a comprehensive 'master plan' or 'coverage plan' is presented as well as the problems and difficulties encountered. The Murewa experience highlights the relevance of a coverage plan for rational and coherent health infrastructure planning at district level. The approach followed by the Murewa team illustrates the use of action research as an integral part of the management of district health systems.     

Insertional re-activation of a chloramphenicol acetyltransferase misfolding mutant protein

The deletion of nine residues from the C-terminus of the bacterialchloramphenicol acetyltransferase (CAT) results in depositionof the mutant protein in cytoplasmic inclusion bodies and lossof chloramphenicol resistance in Escherichia coli. This foldingdefect is relieved by C-terminal fusion of the polypeptide withas few as two residues. Based on these observations, efficientpositive selection for the cloning of DNA fragments has beendemonstrated. The cloning vector encodes a C-terminally truncatedCAT protein. Restriction sites in front of the stop codon allowthe insertion of target DNA, resulting in the production ofproperly folded CAT fusion proteins and regained chloramphenicolresistance. The positive selection of recombinants is accomplishedby growth of transformants on chloramphenicol-containing agarplates. The method appears particularly convenient for the cloningof DNA fragments amplified by the PCR because minimal informationto restore CAT folding can be included in the primers. The cloningof random sequences shows that the folding defect can be relievedby fusion to a wide variety of peptides, providing great flexibilityto the positive selection system. This vector may also contributeto the determination of the role of the C-terminus in CAT folding.