Partial redundancy elimination for access expressions by speculative code motion

We present a new memory access optimization for Java to perform aggressive code motion for speculatively optimizing memory accesses by applying partial redundancy elimination (PRE) techniques. First, to reduce as many barriers as possible and to enhance code motion, we perform alias analysis to identify all the regions in which each object reference is not aliased. Secondly, we find all the possible barriers. Finally, we perform code motions in three steps. For the first step, we apply a non‐speculative PRE algorithm to move load instructions and their following instructions in the backwards direction of the control flow graph. For the second step, we apply a speculative PRE algorithm to move some of them aggressively before the conditional branches. For the third step, we apply our modified version of a non‐speculative PRE algorithm to move store instructions in the forward direction of the control flow graph and to even move some of them after the merge points. We implemented our new algorithm in our production‐level Java just‐in‐time compiler. Our experimental results show that our speculative algorithm improves the average (maximum) performance by 13.1% (90.7%) for jBYTEmark and 1.4% (4.4%) for SPECjvm98 over the fastest algorithm previously described, while it increases the average (maximum) compilation time by 0.9% (2.9%) for both benchmark suites. Copyright © 2004 John Wiley & Sons, Ltd.     

Development and industrial application of soft sensors with on-line Bayesian model updating strategy

This paper deals with the issues associated with the development of data-driven models as well as model update strategy for soft sensor applications. A practical yet effective solution is proposed. Key process variables that are difficult to measure are commonly encountered in practice due to limitations of measurement techniques. Even with appropriate instruments, some measurements are only available through off-line laboratory analysis with typical sampling intervals of several hours. Soft sensors are inferential models that can provide continuous on-line prediction of hidden variables; such models are capable of combining real-time measurements with off-line lab data. Due to the prevalence of plant-model mismatch, it is important to update the model using the latest reference data. In this paper, parameters of data-driven models are estimated using particle filters under the framework of expectation–maximization (EM) algorithms. A Bayesian methodology for model calibration strategy is formulated. The proposed framework for soft sensor development is applied to an industrial process to provide on-line prediction of a quality variable.     

A Bayesian approach to design of adaptive multi-model inferential sensors with application in oil sand industry

In the context of process industries, online monitoring of quality variables is often restricted by inadequacy of measurement techniques or low reliability of measuring devices. Therefore, there has been a growing interest in the development of inferential sensors to provide frequent online estimates of key process variables on the basis of their correlation with real-time process measurements. Representation of multi-modal processes is one of the challenging issues that may arise in the design of inferential sensors. In this paper, Bayesian procedures for the development and implementation of adaptive multi-model inferential sensors are presented. It is shown that the application of a Bayesian scheme allows for accommodating the overlapping operating modes and facilitating the inclusion of prior knowledge. The effectiveness of the proposed procedures are first demonstrated through a simulation case study. The efficacy of the method is further highlighted by a successful industrial application of an adaptive multi-model inferential sensor designed for real-time monitoring of a key quality variable in an oil sands processing unit.     

The data-driven microprocessor

Processor performance limitations that can be solved by data-flow processing are discussed. Data-flow-based software and multiprocessors are considered. A data-driven, 32-bit, five-chip set that performs real-time signal and distributed parallel processing without a system clock or centralized control unit is presented. Language processing and processor applications are examined     

High drive current NMOS with Si-SiGe heterostructure low electric field channel

A drive-current enhancement in NMOS with a compressively strained SiGe structure, which had been a difficult challenge for CMOS integration with strained SiGe high-hole-mobility PMOS, was successfully achieved using a Si-SiGe heterostructure low electric field channel of optimum thickness. A 4-nm-thick Si low-field-channel NMOS with a 4-nm-thick Si/sub 0.8/Ge/sub 0.2/ layer improved drive current by 10% with a 20% reduction in gate leakage current compared with Si-control, while suppressing threshold-voltage rolloff characteristic degradation, and demonstrated excellent I/sub on/--I/sub off/ characteristics of I/sub on/ = 1 mA//spl mu/m for I/sub off/ = 100 nA//spl mu/m. These results are the best in ever reported NMOS with a compressively strained SiGe structure and indicate that a Si-SiGe heterostructure low-field-channel NMOS integrated with a compressively strained SiGe channel PMOS is a promising candidate for high-speed CMOS in 65-nm node logic technology.     

Evaluation of core characteristics of magnetic phase shifters for thyristor amplifiers

The exciting current characteristic is suggested as a new method of evaluating the core characteristic. The phase shifting characteristic and the difference between a positive and negative waveform of a balanced half-wave type magnetic phase shifter are calculated by using the exciting current characteristics of cores employed in it. From these theoretical analyses, it can be determined that the difference of a positive and negative waveform is caused by a difference of exciting current characteristics of two cores used in it, and it becomes larger in proportion to larger control-circuit resistance. An experiment was performed using two pairs of cores, in which one pair of exciting currents are identical and the other pair differ. Theoretical results are in good agreement with the experimental results.     

Intergranular stress corrosion cracking initiation model of austenite stainless steels used in BWRs for optimized water chemistry control

A calculation model on intergranular stress corrosion cracking (IGSCC) initiation time of materials used in boiling water reactors (BWRs) has been developed to evaluate effectiveness of water chemistry control for mitigation of the IGSCC. The model was composed of four terms which determine passive film break time: (1) a chemical term based on electrochemical corrosion potential (ECP) and impurity concentration; (2) a mechanical term based on strain rate; (3) a material term based on sensitization; and (4) an irradiation term based on acceleration of corrosion by γ-rays and neutron irradiation. The contribution of the chemical term in the passive film break was calculated based on a deterministic local corrosion model. Then, the local corrosion model was modified by adding mechanical acceleration of the film rupture to treat the IGSCC phenomenon. The model could reproduce the behavioral tendency seen in the slow strain rate tensile test on high carbon contents with sensitization heat treatment (for example, 620°C × 24 h). Under BWR operating conditions, IGSCC initiation time could be extended by a factor of 5 by lowering the electric conductivity from 1.0 to 0.06 μS/cm. If the ECP was reduced below the critical potential by a mitigation method, the IGSCC initiation time was predicted to become sufficiently long for pipings and components.     

Computed tomography reconstruction from two transmission measurements for iodine-marked cancer detection

The authors invented the transXend detector, which measures X-rays as electric currents, and then gives the energy distribution of the X-rays after an unfolding process. In a previous paper, it was shown that the material thickness distributions can be estimated with the transXend detector by using reference points plotted from the electric current ratios, such as the I ₂/I ₁ ? I ₃/I ₁ graph, where I_i denotes the electric current measured by the i-th segment of the transXend detector. In this paper, the tomographic images of iodine, aluminum, and the acrylic those surround the other two materials are reconstructed from their material thickness distributions, which are estimated from two X-ray incidence directions. The X-ray event ratios are also used to estimate the material thickness distributions.     

Effects of water chemistry and potential distribution on electrochemical corrosion potential measurements in 553 K pure water

The effects of water chemistry distribution on the potential of a reference electrode and of the potential distribution on the measured potential should be known qualitatively to obtain accurate electrochemical corrosion potential (ECP) data in BWRs. First, the effects of oxygen on a platinum reference electrode were studied in 553 K pure water containing dissolved hydrogen (DH) concentration of 26–105 μg kg^?1 (ppb). The platinum electrode worked in the same way as the theoretical hydrogen electrode under the condition that the molar ratio of DH to dissolved oxygen (DO) was more than 10 and that DO was less than 100 ppb. Second, the effects of potential distribution on the measured potential were studied by using the ECP measurement part without platinum deposition on the surfaces connected to another ECP measurement part with platinum deposition on the surfaces in 553 K pure water containing 100–130 ppb of DH or 100–130 ppb of DH plus 400 ppb of hydrogen peroxide. Measured potentials for each ECP measurement part were in good agreement with literature data for each surface condition. The lead wire connecting point did not affect the measured potential. Potential should be measured at the nearest point from the reference electrode in which case it will be not affected by either the potential distribution or the connection point of the lead wire in pure water.     

Low-dose exposure energy-resolved X-ray computed tomography using a contrast agent with a high-energy K-edge

X-ray computed tomography (CT) with iodine contrast agent is widely employed to locate cancers. However, this method has shortcomings such as high-radiation dose exposure, iodine side effects, and a beam hardening effect. We have been working on the energy-resolved CT measurement method using a novel X-ray detection system, the “transXend” detector, which measures X-rays as electric currents and gives the energy distribution of incident X-rays after analysis. In the present study, we propose a method for low-dose exposure CT that involves the combination of the energy-resolved CT method, which is free from the beam hardening effect, and a harmless contrast agent with high-energy K-edge absorption, such as gold nanoparticles expected as a future contrast agent. Comparisons of radiation dose exposures as functions of aluminum filter thickness at the exit aperture of an X-ray tube and the K-edge energies of contrast agents are described.