Estimation of Probabilistic Bounds on Phase CPI and Relevance in WCET Analysis

Estimating program worst case execution time(WCET) accurately and efficiently is a challenging task. Several programs exhibit phase behavior wherein cycles per instruction (CPI) varies in phases during execution. Recent work has suggested the use of phases in such programs to estimate WCET with minimal instrumentation. However the suggested model uses a function of mean CPI that has no probabilistic guarantees. We propose to use Chebyshev's inequality that can be applied to any arbitrary distribution of CPI samples, to probabilistically bound CPI of a phase. Applying Chebyshev's inequality to phases that exhibit high CPI variation leads to pessimistic upper bounds. We propose a mechanism that refines such phases into sub-phases based on program counter(PC) signatures collected using profiling and also allows the user to control variance of CPI within a sub-phase. We describe a WCET analyzer built on these lines and evaluate it with standard WCET and embedded benchmark suites on two different architectures for three chosen probabilities, p={0.9, 0.95 and 0.99}. For p= 0.99, refinement based on PC signatures alone, reduces average pessimism of WCET estimate by 36%(77%) on Arch1 (Arch2). Compared to Chronos, an open source static WCET analyzer, the average improvement in estimates obtained by refinement is 5%(125%) on Arch1 (Arch2). On limiting variance of CPI within a sub-phase to {50%, 10%, 5% and 1%} of its original value, average accuracy of WCET estimate improves further to {9%, 11%, 12% and 13%} respectively, on Arch1. On Arch2, average accuracy of WCET improves to 159% when CPI variance is limited to 50% of its original value and improvement is marginal beyond that point.

Reconciling transactional conflicts with compiler's help

Software transactional memory(STM) is a promising programming paradigm for shared memory multithreaded programs. While STM offers the promise of being less error-prone and more programmer friendly compared to traditional lock-based synchronization, it also needs to be competitive in performance in order for it to be adopted in mainstream software. A major source of performance overheads in STM is transactional aborts. Conflict resolution and aborting a transaction typically happens at the transaction level which has the advantage that it is automatic and application agnostic. However it has a substantial disadvantage in that STM declares the entire transaction as conflicting and hence aborts it and re-executes it fully, instead of partially re-executing only those part(s) of the transaction, which have been affected due to the conflict. This "Re-execute Everything" approach has a significant adverse impact on STM performance. In order to mitigate the abort overheads, we propose a compiler aided Selective Reconciliation STM (SR-STM) scheme, wherein certain transactional conflicts can be reconciled by performing partial re-execution of the transaction. Ours is a selective hybrid approach which uses compiler analysis to identify those data accesses which are legal and profitable candidates for reconciliation and applies partial re-execution only to these candidates selectively while other conflicting data accesses are handled by the default STM approach of abort and full re-execution. We describe the compiler analysis and code transformations required for supporting selective reconciliation. We find that SR-STM is effective in reducing the transactional abort overheads by improving the performance for a set of five STAMP benchmarks by 12.58% on an average and up to 22.34%.

Harmonic Analysis of DC-Link Capacitor Current in Sinusoidally Modulated Neutral-Point-Clamped Inverter

The voltage ripple and power loss in the DC-capacitor of a voltage source inverter depend on the harmonic currents flowing through the capacitor. This paper presents double Fourier series based harmonic analysis of DC capacitor current in a three-level neutral point clamped inverter, modulated with sine-triangle PWM. The analytical results are validated experimentally on a 5-kVA three-level inverter prototype. The results of the analysis are used for predicting the power loss in the DC capacitor.

Effect of Inlet Jet injection angle on a calandria based reactor-An investigation with numerical analysis of heat and mass transfer for an optimum reactor design

Heat and mass transfer studies in a calandria based reactor is quite complex both due to geometry and due to the complex mixing flow. It is challenging to devise optimum operating conditions with efficient but safe working range for such a complex configuration. Numerical study known to be very effective is taken up for investigation. In the present study a 3D RANS code with turbulence model has been used to compute the flow fields and to get the heat transfer characteristics to understand certain design parameters of engineering importance. The angle of injection and of the coolant liquid has a large effect on the heat transfer within the reactor.

CFD Analysis of two phase flow with a prediction of torque demand of a Bi-lobe rotor of a mixing chamber

An attempt to study the fluid dynamic behavior of two phase flow comprising of solid and liquid with nearly equal density in a geometrical case that has an industrial significance in theareas like processing of polymers, food, pharma ceutical, paints. In this work,crystalline silica is considered as the dispersed medium in glycerin. In the CFD analysis carried out,the two phase components are considered to be premixed homogeneously at the initial state. The flow in a cylinder that has an axially driven bi-lobe rotor, a typical blender used in polymer industry for mixing or kneading to render the multi-component mixture to homogeneous condition is considered. A viscous, incompressible, isothermal flow is considered with an assumption that the components do not undergo any physical change and the solids are rigid and mix in fully wetting conditions. Silica with a particle diameter of 0.4 mm is considered and flow is analyzed for different mixing fractions. An industry standard CFD code is used for solving 3D-RANS equations. As the outcome of the study the torque demand by the bi-lobe rotor for different mixture fractions which are estimated show a behavioral consistency to the expected physical phenomena occurring in the domain considered.

Prediction of the stiffness of nanoclay-polypropylene composites using a monte carlo finite element analysis approach

The present work deals with the prediction of stiffness of an Indian nanoclay-reinforced polypropylene composite (that can be termed as a nanocomposite) using a Monte Carlo finite element analysis (FEA) technique. Nanocomposite samples are at first prepared in the laboratory using a torque rheometer for achieving desirable dispersion of nanoclay during master batch preparation followed up with extrusion for the fabrication of tensile test dog-bone specimens. It has been observed through SEM (scanning electron microscopy) images of the prepared nanocomposite containing a given percentage (3–9% by weight) of the considered nanoclay that nanoclay platelets tend to remain in clusters. By ascertaining the average size of these nanoclay clusters from the images mentioned, a planar finite element model is created in which nanoclay groups and polymer matrix are modeled as separate entities assuming a given homogeneous distribution of the nanoclay clusters. Using a Monte Carlo simulation procedure, the distribution of nanoclay is varied randomly in an automated manner in a commercial FEA code, and virtual tensile tests are performed for computing the linear stiffness for each case. Values of computed stiffness modulus of highest frequency for nanocomposites with different nanoclay contents correspond well with the experimentally obtained measures of stiffness establishing the effectiveness of the present approach for further applications.

Analysis of the modulation process in advanced bus-clamping PWM techniques

Advanced bus-clamping pulse width modulation (ABCPWM) techniques are advantageous in terms of line current distortion and inverter switching loss in voltage source inverter-fed applications. However, the PWM waveforms corresponding to these techniques are not amenable to carrier-based generation. The modulation process in ABCPWM methods is analyzed here from a “per-phase” perspective. It is shown that three sets of descendant modulating functions (or modified modulating functions) can be generated from the three-phase sinusoidal signals. Each set of the modified modulating functions can be used to produce the PWM waveform of a given phase in a computationally efficient manner. Theoretical results and experimental investigations on a 5hp motor drive are presented

Selection and thermodynamic analysis of a turbocharger for a producer gas-fuelled multi-cylinder engine

The current work addresses the use of producer gas, a bio-derived gaseous alternative fuel, in engines designed for natural gas, derived from diesel engine frames. Impact of the use of producer gas on the general engine performance with specific focus on turbo-charging is addressed. The operation of a particular engine frame with diesel, natural gas and producer gas indicates that the peak load achieved is highest with diesel fuel (in compression ignition mode) followed by natural gas and producer gas (both in spark ignite mode). Detailed analysis of the engine power de-rating on fuelling with natural gas and producer gas indicates that the change in compression ratio (migration from compression to spark ignited mode), difference in mixture calorific value and turbocharger mismatch are the primary contributing factors. The largest de-rating occurs due to turbocharger mismatch. Turbocharger selection and optimization is identified as the strategy to recover the non-thermodynamic power loss, identified as the recovery potential (the loss due to mixture calorific value and turbocharger mismatch) on operating the engine with a fuel different from the base fuel. A turbocharged after-cooled six cylinder, 5.9 l, 90 kWe (diesel rating) engine (12.2 bar BMEP) is available commercially as a naturally aspirated natural gas engine delivering a peak load of 44.0 kWe (6.0 bar BMEP). The engine delivers a load of 27.3 kWe with producer gas under naturally aspirated mode. On charge boosting the engine with a turbocharger similar in configuration to the diesel engine turbocharger, the peak load delivered with producer gas is 36 kWe (4.8 bar BMEP) indicating a de-rating of about 60% over the baseline diesel mode. Estimation of knock limited peak load for producer gas-fuelled operation on the engine frame using a Wiebe function-based zero-dimensional code indicates a knock limited peak load of 76 kWe, indicating the potential to recover about 40 kWe. As a part of the recovery strategy, optimizing the ignition timing for maximum brake torque based on both spark sweep tests and established combustion descriptors and engine-turbocharger matching for producer gas-fuelled operation resulted in a knock limited peak load of 72.8 kWe (9.9 bar BMEP) at a compressor pressure ratio of 2.30. The de-rating of about 17.0 kWe compared to diesel rating is attributed to the reduction in compression ratio. With load recovery, the specific biomass consumption reduces from 1.2 kg/kWh to 1.0 kg/kWh, an improvement of over 16% while the engine thermal efficiency increases from 28% to 32%. The thermodynamic analysis of the compressor and the turbine indicates an isentropic efficiency of 74.5% and 73%, respectively.

Effect of Input Source Energy on SASW Evaluation of Cement Concrete Pavement

A series of spectral analyses of surface waves (SASW) tests were conducted on a cement concrete pavement by dropping steel balls of four different values of diameter (D) varying between 25.4 and 76.2 mm. These tests were performed (1) by using different combinations of source to nearest receiver distance (S) and receiver spacing (X), and (2) for two different heights (H) of fall, namely, 0.25 and 0.50 m. The values of the maximum wavelength (lambda(max)) and minimum wavelength (lambda(min)) associated with the combined dispersion curve, corresponding to a particular combination of D and H, were noted to increase almost linearly with an increase in the magnitude of the input source energy (E). A continuous increase in strength and duration of the signals was noted to occur with an increase in the magnitude of D. Based on statistical analysis, two regression equations have been proposed to determine lambda(max) and lambda(min) for different values of source energy. It is concluded that the SASW technique is capable of producing nearly a unique dispersion curve irrespective of (1) diameters and heights of fall of the dropping masses used for producing the vibration, and (2) the spacing between different receivers. The results presented in this paper can be used to provide guidelines for deciding about the input source energy based on the required exploration zone of the pavement. (C) 2014 American Society of Civil Engineers.

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Programming for parallel architectures that do not have a shared address space is extremely difficult due to the need for explicit communication between memories of different compute devices. A heterogeneous system with CPUs and multiple GPUs, or a distributed-memory cluster are examples of such systems. Past works that try to automate data movement for distributed-memory architectures can lead to excessive redundant communication. In this paper, we propose an automatic data movement scheme that minimizes the volume of communication between compute devices in heterogeneous and distributed-memory systems. We show that by partitioning data dependences in a particular non-trivial way, one can generate data movement code that results in the minimum volume for a vast majority of cases. The techniques are applicable to any sequence of affine loop nests and works on top of any choice of loop transformations, parallelization, and computation placement. The data movement code generated minimizes the volume of communication for a particular configuration of these. We use a combination of powerful static analyses relying on the polyhedral compiler framework and lightweight runtime routines they generate, to build a source-to-source transformation tool that automatically generates communication code. We demonstrate that the tool is scalable and leads to substantial gains in efficiency. On a heterogeneous system, the communication volume is reduced by a factor of 11X to 83X over state-of-the-art, translating into a mean execution time speedup of 1.53X. On a distributed-memory cluster, our scheme reduces the communication volume by a factor of 1.4X to 63.5X over state-of-the-art, resulting in a mean speedup of 1.55X. In addition, our scheme yields a mean speedup of 2.19X over hand-optimized UPC codes.

Parallel Flow-Sensitive Pointer Analysis by Graph-Rewriting

Precise pointer analysis is a problem of interest to both the compiler and the program verification community. Flow-sensitivity is an important dimension of pointer analysis that affects the precision of the final result computed. Scaling flow-sensitive pointer analysis to millions of lines of code is a major challenge. Recently, staged flow-sensitive pointer analysis has been proposed, which exploits a sparse representation of program code created by staged analysis. In this paper we formulate the staged flow-sensitive pointer analysis as a graph-rewriting problem. Graph-rewriting has already been used for flow-insensitive analysis. However, formulating flow-sensitive pointer analysis as a graph-rewriting problem adds additional challenges due to the nature of flow-sensitivity. We implement our parallel algorithm using Intel Threading Building Blocks and demonstrate considerable scaling (upto 2.6x) for 8 threads on a set of 10 benchmarks. Compared to the sequential implementation of staged flow-sensitive analysis, a single threaded execution of our implementation performs better in 8 of the benchmarks.

Intense Acoustic Burst Ultrasound Modulated Optical Tomography for Elasticity Mapping of Soft Biological Tissue Mimicking Phantom: A Laser Speckle Contrast Analysis Study

This report addresses the assessment of variation in elastic property of soft biological tissues non-invasively using laser speckle contrast measurement. The experimental as well as the numerical (Monte-Carlo simulation) studies are carried out. In this an intense acoustic burst of ultrasound (an acoustic pulse with high power within standard safety limits), instead of continuous wave, is employed to induce large modulation of the tissue materials in the ultrasound insonified region of interest (ROI) and it results to enhance the strength of the ultrasound modulated optical signal in ultrasound modulated optical tomography (UMOT) system. The intensity fluctuation of speckle patterns formed by interference of light scattered (while traversing through tissue medium) is characterized by the motion of scattering sites. The displacement of scattering particles is inversely related to the elastic property of the tissue. We study the feasibility of laser speckle contrast analysis (LSCA) technique to reconstruct a map of the elastic property of a soft tissue-mimicking phantom. We employ source synchronized parallel speckle detection scheme to (experimentally) measure the speckle contrast from the light traversing through ultrasound (US) insonified tissue-mimicking phantom. The measured relative image contrast (the ratio of the difference of the maximum and the minimum values to the maximum value) for intense acoustic burst is 86.44 % in comparison to 67.28 % for continuous wave excitation of ultrasound. We also present 1-D and 2-D image of speckle contrast which is the representative of elastic property distribution.

A shortest path tree based algorithm for relay placement in a wireless sensor network and its performance analysis

In this paper, we study a problem of designing a multi-hop wireless network for interconnecting sensors (hereafter called source nodes) to a Base Station (BS), by deploying a minimum number of relay nodes at a subset of given potential locations, while meeting a quality of service (QoS) objective specified as a hop count bound for paths from the sources to the BS. The hop count bound suffices to ensure a certain probability of the data being delivered to the BS within a given maximum delay under a light traffic model. We observe that the problem is NP-Hard. For this problem, we propose a polynomial time approximation algorithm based on iteratively constructing shortest path trees and heuristically pruning away the relay nodes used until the hop count bound is violated. Results show that the algorithm performs efficiently in various randomly generated network scenarios; in over 90% of the tested scenarios, it gave solutions that were either optimal or were worse than optimal by just one relay. We then use random graph techniques to obtain, under a certain stochastic setting, an upper bound on the average case approximation ratio of a class of algorithms (including the proposed algorithm) for this problem as a function of the number of source nodes, and the hop count bound. To the best of our knowledge, the average case analysis is the first of its kind in the relay placement literature. Since the design is based on a light traffic model, we also provide simulation results (using models for the IEEE 802.15.4 physical layer and medium access control) to assess the traffic levels up to which the QoS objectives continue to be met. (C) 2014 Elsevier B.V. All rights reserved.

Biodegradation of acrylamide by acrylamidase from Stenotrophomonas acidaminiphila MSU12 and analysis of degradation products by MALDI-TOF and HPLC

The present study examines an improved detoxification and rapid biological degradation of toxic pollutant acrylamide using a bacterium. The acrylamide degrading bacterium was isolated from the soil followed by its screening to know the acrylamide degrading capability. The minimal medium containing acrylamide (30 mM) served as a sole source of carbon and nitrogen for their active growth. The optimization of three different factors was analyzed by using Response Surface Methodology (RSM). The bacteria actively degraded the acrylamide at a temperature of 32 degrees C, with a maximum growth at 30 mM substrate (acrylamide) concentration at a pH of 7.2. The acrylamidase activity and degradation of acrylamide was determined by High Performance Liquid Chromatography (HPLC) and Matrix Assisted Laser Desorption and Ionization Time of Flight mass spectrometer (MALDI-TOF). Based on 168 rRNA analysis the selected strain was identified as Gram negative bacilli Stenotrophomonas acidaminiphila MSU12. The acrylamidase was isolated from bacterial extract and was purified by HPLC, whose mass spectrum showed a molecular mass of 38 kDa. (C) 2014 Elsevier Ltd. All rights reserved.

Influence of source concentration on structural and optical properties of SnO2 nanoparticles prepared by chemical precipitation method

In present work, a systematic study has been carried out to understand the influence of source concentration on structural and optical properties of the SnO2 nanoparticles. SnO2 nanoparticles have been prepared by using chemical precipitation method at room temperature with aqueous ammonia as a stabilizing agent. X-ray diffraction analysis reveals that SnO2 nanoparticles exhibit tetragonal structure and the particle size is in range of 4.9-7.6 nm. High resolution transmission electron microscopic image shows that all the particles are nearly spherical in nature and particle size lies in range of 4.6-7 nm. Compositional analysis indicates the presence of Sn and O in samples. Blue shift has been observed in optical absorption spectra due to quantum confinement and the bandgap is in range of 4-4.16 eV. The origin of photoluminescence in SnO2 is found to be due to recombination of electrons in singly occupied oxygen vacancies with photo-excited holes in valance band.