Construction and use of linear regression models for processor performance analysis

Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate Processor performance to micro-architecture parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike's information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques.

High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Performance

Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space-time block codes (STBC) from Cyclic Division Algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32x32 STBC from CDA, which employs 32 transmit antennas and sends 32(2) = 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16x16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

Use of L matrix to obtain reliable ab initio force constants of polyatomic molecules: ethylene as a test system

Direct use of experimental eigenvalues of the vibrational secular equation on to the ab initio predicted eigenvector space is suggested as a means of obtaining a reliable set of intramolecular force constants. This method which we have termed RECOVES (recovery in the eigenvector space) is computationally simple and free from arbitrariness. The RECOVES force constants, by definition, reproduce the experimental vibrational frequencies of the parent molecule exactly. The ab initio calculations were carried out for ethylene as a test molecule and the force constants obtained by the present procedure also correctly predict the vibrational frequencies of the deuterated species. The RECOVES force constants for ethylene are compared with those obtained by using the SQM procedure.

Single real-symbol decodable, high-rate, distributed space-time block codes

A scheme to apply the rate-1 real orthogonal designs (RODs) in relay networks with single real-symbol decodability of the symbols at the destination for any arbitrary number of relays is proposed. In the case where the relays do not have any information about the channel gains from the source to themselves, the best known distributed space time block codes (DSTBCs) for k relays with single real-symbol decodability offer an overall rate of complex symbols per channel use. The scheme proposed in this paper offers an overall rate of 2/2+k complex symbol per channel use, which is independent of the number of relays. Furthermore, in the scenario where the relays have partial channel information in the form of channel phase knowledge, the best known DSTBCs with single real-symbol decodability offer an overall rate of 1/3 complex symbols per channel use. In this paper, making use of RODs, a scheme which achieves the same overall rate of 1/3 complex symbols per channel use but with a decoding delay that is 50 percent of that of the best known DSTBCs, is presented. Simulation results of the symbol error rate performance for 10 relays, which show the superiority of the proposed scheme over the best known DSTBC for 10 relays with single real-symbol decodability, are provided.

Exploring use of climate information for optimal design of water resources infrastructure

We conducted surveys of fire and fuels managers at local, regional, and national levels to gain insights into decision processes and information flows in wildfire management. Survey results in the form of fire managers’ decision calendars show how climate information needs vary seasonally, over space, and through the organizational network, and help determine optimal points for introducing climate information and forecasts into decision processes. We identified opportunities to use climate information in fire management, including seasonal to interannual climate forecasts at all organizational levels, to improve the targeting of fuels treatments and prescribed burns, the positioning and movement of initial attack resources, and staffing and budgeting decisions. Longer-term (5–10 years) outlooks also could be useful at the national level in setting budget and research priorities. We discuss these opportunities and examine the kinds of organizational changes that could facilitate effective use of existing climate information and climate forecast capabilities.

Novel Switching Sequences for a Space-Vector-Modulated Three-Level Inverter

A three-level inverter produces six active vectors, each of normalized magnitudes 1, 0.866, and 0.5, besides a zero vector. The vectors of relative length 0.5 are termed pivot vectors.The three nearest voltage vectors are usually used to synthesize the reference vector. In most continuous pulsewidth-modulation(PWM) schemes, the switching sequence begins from a pivot vector and ends with the same pivot vector. Thus, the pivot vector is applied twice in a subcycle or half-carrier cycle. This paper proposes and investigates alternative switching sequences, which use the pivot vector only once but employ one of the other two vectors twice within the subcycle. The total harmonic distortion(THD) in the fundamental line current pertaining to these novel sequences is studied theoretically as well as experimentally over the whole range of modulation. Compared with centered space vector PWM, two of the proposed sequences lead to reduced THD at high modulation indices at a given average switching frequency.

Specification Based Regression Testing Using Explicit State Space Enumeration

This paper presents a method of partial automation of specification based regression testing, which we call ESSE (Explicit State Space Enumeration). The first step in ESSE method is the extraction of a finite state model of the system making use of an already tested version of the system under test (SUT). Thereafter, the finite state model thus obtained is used to compute good test sequences that can be used to regression test subsequent versions of the system. We present two new algorithms for test sequence computation - both based on our finite state model generated by the above method. We also provide the details and results of the experimental evaluation of ESSE method. Comparison with a practically used random-testing algorithm has shown substantial improvements.

A general construction of space-time trellis codes for PSK signal sets

The diversity order and coding gain are crucial for the performance of a multiple antenna communication system. It is known that space-time trellis codes (STTC) can be used to achieve these objectives. In particular, we can use STTCs to obtain large coding gains. Many attempts have been made to construct STTCs which achieve full-diversity and good coding gains, though a general method of construction does not exist. Delay diversity code (rate-1) is known to achieve full-diversity, for any number of transmit antennas and any signal set, but does not give a good coding gain. A product distance code based delay diversity scheme (Tarokh, V. et al., IEEE Trans. Inform. Theory, vol.44, p.744-65, 1998) enables one to improve the coding gain and construct STTCs for any given number of states using coding in conjunction with delay diversity; it was stated as an open problem. We achieve such a construction. We assume a shift register based model to construct an STTC for any state complexity. We derive a sufficient condition for this STTC to achieve full-diversity, based on the delay diversity scheme. This condition provides a framework to do coding in conjunction with delay diversity for any signal constellation. Using this condition, we provide a formal rate-1 STTC construction scheme for PSK signal sets, for any number of transmit antennas and any given number of states, which achieves full-diversity and gives a good coding gain.

On the solution of bivariate population balance equations for aggregation: X-discretization of space for expansion and contraction of computational domain

A new structured discretization of 2D space, named X-discretization, is proposed to solve bivariate population balance equations using the framework of minimal internal consistency of discretization of Chakraborty and Kumar [2007, A new framework for solution of multidimensional population balance equations. Chem. Eng. Sci. 62, 4112-4125] for breakup and aggregation of particles. The 2D space of particle constituents (internal attributes) is discretized into bins by using arbitrarily spaced constant composition radial lines and constant mass lines of slope -1. The quadrilaterals are triangulated by using straight lines pointing towards the mean composition line. The monotonicity of the new discretization makes is quite easy to implement, like a rectangular grid but with significantly reduced numerical dispersion. We use the new discretization of space to automate the expansion and contraction of the computational domain for the aggregation process, corresponding to the formation of larger particles and the disappearance of smaller particles by adding and removing the constant mass lines at the boundaries. The results show that the predictions of particle size distribution on fixed X-grid are in better agreement with the analytical solution than those obtained with the earlier techniques. The simulations carried out with expansion and/or contraction of the computational domain as population evolves show that the proposed strategy of evolving the computational domain with the aggregation process brings down the computational effort quite substantially; larger the extent of evolution, greater is the reduction in computational effort. (C) 2011 Elsevier Ltd. All rights reserved.

Model projections for household energy use in India

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO(2) emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO(2) emissions via increased electricity use. (C) 2011 Elsevier Ltd. All rights reserved.

Space vector based bus clamped PWM algorithms for three level inverters: implementation, performance analysis and application considerations

This paper describes the different types of space vector based bus clamped PWM algorithms for three level inverters. A novel bus clamp PWM algorithm for low modulation indices region is also presented. The principles and switching sequences of all the types of bus clamped algorithms for high switching frequency are presented. Synchronized version of the PWM sequences for high power applications where switching frequency is low is also presented. The implementation details on DSP based digital controller and experimental results are presented. The THD of the output waveforms is studied for the entire operating region and is compared with the conventional space vector PWM technique. The bus clamped techniques can be used to reduce the switching losses or to improve the output voltage quality or both.. Different issues dominate depending on the type of application and power rating of the inverters. The results presented in this paper can be used for judicious use of the PWM techniques, which result in improved system efficiency and performance.

Image Encryption with Space-filling Curves

Conventional encryption techniques are usually applicable for text data and often unsuited for encrypting multimedia objects for two reasons. Firstly, the huge sizes associated with multimedia objects make conventional encryption computationally costly. Secondly, multimedia objects come with massive redundancies which are useful in avoiding encryption of the objects in their entirety. Hence a class of encryption techniques devoted to encrypting multimedia objects like images have been developed. These techniques make use of the fact that the data comprising multimedia objects like images could in general be seggregated into two disjoint components, namely salient and non-salient. While the former component contributes to the perceptual quality of the object, the latter only adds minor details to it. In the context of images, the salient component is often much smaller in size than the non-salient component. Encryption effort is considerably reduced if only the salient component is encrypted while leaving the other component unencrypted. A key challenge is to find means to achieve a desirable seggregation so that the unencrypted component does not reveal any information about the object itself. In this study, an image encryption approach that uses fractal structures known as space-filling curves- in order to reduce the encryption overload is presented. In addition, the approach also enables a high quality lossy compression of images.

On Selection of Search Space Dimension in Compressive Sampling Matching Pursuit

Compressive Sampling Matching Pursuit (CoSaMP) is one of the popular greedy methods in the emerging field of Compressed Sensing (CS). In addition to the appealing empirical performance, CoSaMP has also splendid theoretical guarantees for convergence. In this paper, we propose a modification in CoSaMP to adaptively choose the dimension of search space in each iteration, using a threshold based approach. Using Monte Carlo simulations, we show that this modification improves the reconstruction capability of the CoSaMP algorithm in clean as well as noisy measurement cases. From empirical observations, we also propose an optimum value for the threshold to use in applications.

Fiber Bragg Grating Sensor Instrumentation for Parking Space Occupancy Management

This work aims at providing an effective parking management system by reducing the drivers' searching time for vacant car-parking space, in turn improving the traffic flow in the car park areas. This is achieved by the use of Fiber Bragg Grating Sensor (FBG) sensor instrumentation in vehicle parking management system. Present work involves embedding an array of FBG sensors underground in the parking space, then determining the strain changes on the FBG sensor due to load applied by the vehicle parked in the parking space, occupancy of the parking space is determined. To validate the FBG sensor parking management system, three most common cases have been considered. This closed loop FBG parking management system can give real-time feed-back to space-guidance display board helping the driver in maneuvering the vehicle to the appropriate parking space. The proposed technique offers optimized usage of parking space for the various segments of cars and also facilitates in a conjoined automated billing system, as compared to conventional method of parking systems.