This paper proposes an algorithm to optimize the trade-off between space and time for a class of electronic structure calculations involving tensor contractions. The algorithm starts with an operation-based representation and applies transformations to minimize the total memory requirement by reducing the size of intermediate arrays through loop fusion techniques. This approach addresses the challenge of large temporary memory requirements for coupled cluster and other electronic structure models.
A Physical Approach to Moving Cast Shadow Detection (ICASSP 2009)Jia-Bin Huang
This document presents a physics-based approach for detecting moving cast shadows in video sequences. It develops a new physical model to characterize the variation in background appearance caused by cast shadows, without making assumptions about the spectral power distributions of light sources and ambient illumination. It uses a Gaussian mixture model to learn and update the shadow model parameters over time in an unsupervised manner. Experimental results on three challenging sequences demonstrate the effectiveness of the proposed method.
This document proposes using a hybrid model and structured sparsity for under-determined convolutive audio source separation. It presents a mathematical model that combines a convex cost function with sparse regularization terms. A hybrid model is introduced using a union of two Gabor frames, each adapted to a different "morphological layer" of the signal. Structured sparsity is incorporated using a windowed group lasso operator to better exploit time-frequency structure. Experiments on speech and music mixtures show improved source separation performance compared to baseline methods, confirming the benefits of the proposed hybrid and structured sparsity approaches.
- Compressive sensing (CS) theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use
- CS relies on two principle :
sparsity: which pertains to the signal of interest
In coherence : which pertains to the sensing modality
The document discusses convolution and its applications in digital signal processing. It begins with an introduction to convolution and its mathematical definitions for both continuous and discrete time signals. It then discusses various types of convolution including linear and circular convolution. The properties of convolution such as commutativity, associativity and distributivity are also covered. Applications of convolution in areas such as statistics, optics, acoustics, electrical engineering and digital signal processing are summarized. Finally, the document discusses symmetric convolution and its advantages over traditional convolution methods.
Ch7 noise variation of different modulation scheme pg 63Prateek Omer
This document summarizes the noise performance of various modulation schemes. It begins by introducing a receiver model and defining figures of merit used to evaluate performance. It then analyzes the noise performance of coherent demodulation for DSB-SC and SSB modulation. The following key points are made:
1) Coherent detection of DSB-SC signals results in signal and noise being additive at both the input and output of the detector. The detector completely rejects the quadrature noise component.
2) For DSB-SC, the output SNR and reference SNR are equal, resulting in a figure of merit of 1.
3) Analysis of SSB modulation shows it achieves a 3 dB improvement in output SNR over
2015_Reduced-Complexity Super-Resolution DOA Estimation with Unknown Number o...Mohamed Mubeen S
The document presents a novel technique for super-resolution direction-of-arrival (DOA) estimation when the number of sources is unknown. The technique formulates an optimization problem to minimize beamformer output power while constraining the weight vector norm, making it insensitive to the estimated number of sources. This provides resolution comparable to super-resolution techniques like MUSIC but with significantly lower computational cost, as it requires solving a generalized eigenvalue problem only once rather than for each scan direction. Analysis shows the technique works similarly to the minimum-norm algorithm while avoiding dependence on the estimated model order. Simulation results demonstrate it outperforms using model order estimation with subspace-based techniques.
The document describes fitting curves to data using R. It discusses intrinsically linear and linearizable relationships that can be fit with linear regression. For truly non-linear relationships, the nls method is used to fit functional forms such as power, exponential, and piecewise models. Examples are given fitting simulated data to a known cubic function using nls to estimate the power parameter, and comparing fits with and without an intercept term. Model quality is assessed using residual sum of squares.
Two novel transforms, related together and called Sine and Cosine Fresnel Transforms, as well as their optical implementation are presented. Each transform combines both backward and forward light propagation in the framework of the scalar diffraction approximation. It has been proven that the Fresnel transform is the optical version of the fractional Fourier transform. Therefore the former has the same properties as the latter. While showing properties similar to those of the Fresnel transform and therefore of the fractional Fourier transform, each of the Sine and Cosine Fresnel transforms provides a real result for a real input distribution. This enables saving half of the quantity of information in the complex plane. Because of parallelism, optics offers high speed processing of digital signals. Speech signals should be first represented by images through special light modulators for example. The Sine and Cosine Fresnel transforms may be regarded respectively as the fractional Sine and Cosine transforms which are more general than the Cosine transform used in information processing and compression.
A Physical Approach to Moving Cast Shadow Detection (ICASSP 2009)Jia-Bin Huang
This document presents a physics-based approach for detecting moving cast shadows in video sequences. It develops a new physical model to characterize the variation in background appearance caused by cast shadows, without making assumptions about the spectral power distributions of light sources and ambient illumination. It uses a Gaussian mixture model to learn and update the shadow model parameters over time in an unsupervised manner. Experimental results on three challenging sequences demonstrate the effectiveness of the proposed method.
This document proposes using a hybrid model and structured sparsity for under-determined convolutive audio source separation. It presents a mathematical model that combines a convex cost function with sparse regularization terms. A hybrid model is introduced using a union of two Gabor frames, each adapted to a different "morphological layer" of the signal. Structured sparsity is incorporated using a windowed group lasso operator to better exploit time-frequency structure. Experiments on speech and music mixtures show improved source separation performance compared to baseline methods, confirming the benefits of the proposed hybrid and structured sparsity approaches.
- Compressive sensing (CS) theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional methods use
- CS relies on two principle :
sparsity: which pertains to the signal of interest
In coherence : which pertains to the sensing modality
The document discusses convolution and its applications in digital signal processing. It begins with an introduction to convolution and its mathematical definitions for both continuous and discrete time signals. It then discusses various types of convolution including linear and circular convolution. The properties of convolution such as commutativity, associativity and distributivity are also covered. Applications of convolution in areas such as statistics, optics, acoustics, electrical engineering and digital signal processing are summarized. Finally, the document discusses symmetric convolution and its advantages over traditional convolution methods.
Ch7 noise variation of different modulation scheme pg 63Prateek Omer
This document summarizes the noise performance of various modulation schemes. It begins by introducing a receiver model and defining figures of merit used to evaluate performance. It then analyzes the noise performance of coherent demodulation for DSB-SC and SSB modulation. The following key points are made:
1) Coherent detection of DSB-SC signals results in signal and noise being additive at both the input and output of the detector. The detector completely rejects the quadrature noise component.
2) For DSB-SC, the output SNR and reference SNR are equal, resulting in a figure of merit of 1.
3) Analysis of SSB modulation shows it achieves a 3 dB improvement in output SNR over
2015_Reduced-Complexity Super-Resolution DOA Estimation with Unknown Number o...Mohamed Mubeen S
The document presents a novel technique for super-resolution direction-of-arrival (DOA) estimation when the number of sources is unknown. The technique formulates an optimization problem to minimize beamformer output power while constraining the weight vector norm, making it insensitive to the estimated number of sources. This provides resolution comparable to super-resolution techniques like MUSIC but with significantly lower computational cost, as it requires solving a generalized eigenvalue problem only once rather than for each scan direction. Analysis shows the technique works similarly to the minimum-norm algorithm while avoiding dependence on the estimated model order. Simulation results demonstrate it outperforms using model order estimation with subspace-based techniques.
The document describes fitting curves to data using R. It discusses intrinsically linear and linearizable relationships that can be fit with linear regression. For truly non-linear relationships, the nls method is used to fit functional forms such as power, exponential, and piecewise models. Examples are given fitting simulated data to a known cubic function using nls to estimate the power parameter, and comparing fits with and without an intercept term. Model quality is assessed using residual sum of squares.
Two novel transforms, related together and called Sine and Cosine Fresnel Transforms, as well as their optical implementation are presented. Each transform combines both backward and forward light propagation in the framework of the scalar diffraction approximation. It has been proven that the Fresnel transform is the optical version of the fractional Fourier transform. Therefore the former has the same properties as the latter. While showing properties similar to those of the Fresnel transform and therefore of the fractional Fourier transform, each of the Sine and Cosine Fresnel transforms provides a real result for a real input distribution. This enables saving half of the quantity of information in the complex plane. Because of parallelism, optics offers high speed processing of digital signals. Speech signals should be first represented by images through special light modulators for example. The Sine and Cosine Fresnel transforms may be regarded respectively as the fractional Sine and Cosine transforms which are more general than the Cosine transform used in information processing and compression.
In this paper, we provide the average bit error probabilities of MQAM and MPSK in the presence of log normal shadowing using Maximal Ratio Combining technique for L diversity branches. We have derived probability of density function (PDF) of received signal to noise ratio (SNR) for L diversity branches in Log Normal fadingfor Maximal Ratio Combining (MRC). We have used Fenton-Wilkinson method to estimate the parameters for a single log-normal distribution that approximates the sum of log-normal random variables (RVs). The results that we provide in this paper are an important tool for measuring the performance ofcommunication links in a log-normal shadowing.
Analysis of Peak to Average Power Ratio Reduction Techniques in Sfbc Ofdm SystemIOSR Journals
This document summarizes techniques to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It analyzes applying selected mapping (SLM) and clipping with differential scaling techniques to space frequency block coded (SFBC) OFDM systems. SLM generates alternative representations of OFDM symbols by rotating frames with different phase sequences and selects the one with minimum PAPR. Clipping clips signal amplitudes above a threshold and differential scaling scales different amplitude ranges differently to reduce PAPR without degrading bit error rate. Simulation results show SLM and clipping with scaling effectively reduce PAPR.
11.[23 36]quadrature radon transform for smoother tomographic reconstructionAlexander Decker
This document discusses a technique called quadrature Radon transform for tomographic reconstruction. The quadrature Radon transform uses projections from two angles (θ and θ+π/2) rather than just one angle as in conventional Radon transform. This provides additional information that can yield smoother reconstructions. Two approaches are proposed: 1) treating the two sets of projections as real and imaginary parts of a complex number, or 2) averaging the individual back projections. Experimental results show the quadrature Radon transform produces numerically and visually better reconstructions compared to using a single set of projections.
11.quadrature radon transform for smoother tomographic reconstructionAlexander Decker
This document discusses a technique called quadrature Radon transform for tomographic reconstruction. The quadrature Radon transform uses projections from two angles (θ and θ+π/2) rather than just one angle as in conventional Radon transform. This provides additional information that can yield smoother reconstructions. Two approaches are proposed - treating the two sets of projections as real and imaginary parts of a complex number, or averaging the individual back projections. Experimental results show the quadrature Radon transform produces numerically and visually better reconstructions compared to using projections from a single angle.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This document describes a MATLAB simulation project investigating digital modulation, sampling receivers, the Nyquist criterion, intersymbol interference, and pulse shaping. The project involves building a basic digital modulator and sampling receiver in Simulink. Experiments are conducted introducing intersymbol interference by overlapping pulses and using different pulse shapes, including a Nyquist pulse. The results demonstrate how intersymbol interference affects the signal and how satisfying the Nyquist criterion can prevent interference during sampling.
This document discusses the effect of multipath on covariance-based beamforming in MIMO radar.
It begins with an introduction to MIMO radar and covariance-based beamforming methods. It then presents a signal model that incorporates multipath effects, showing how the beam pattern expression is modified.
Simulations are shown analyzing how multipath can change the beam pattern peak direction, increase sidelobe levels, and produce false peaks, depending on the random amplitudes and phases of the multipath signals. Increasing the number of multipath paths or their phase variance generally leads to greater errors in the desired beam pattern.
DUNE on current and next generation HPC PlatformsMarkus Blatt
In this talk we present the Distributed and Unified Numerics
Environment (DUNE). It is a software framework for the parallel
numerical solution of partial differential equations with grid-based
methods. Using generic programming techniques it strives for both:
high flexibility (efficiency of the programmer) and high performance
(efficiency of the program).
We present parallel applications realized with DUNE and
show their scalability on current HPC platforms such as the Blue
Gene/P system in Jülich.
Finally we will take a closer look on hardware attributes that
influence the scalability of DUNE and software solving partial
differential equations in general. We investigate how DUNE will
perform on future hardware like Blue Gene/Q.
Special emphasis will be put on the performance of parallel
iterative solvers both in general and in DUNE.
This document discusses performance of matching algorithms for signal approximation. It begins by introducing matching pursuit algorithms like Orthogonal Matching Pursuit (OMP) and Stagewise Orthogonal Matching Pursuit (StOMP) which are greedy algorithms that approximate sparse signals. It then describes the Non-Negative Least Squares algorithm which solves non-negative least squares problems. Finally, it discusses Extranious Equivalent Detection (EED), a modification of OED that incorporates non-negativity of representations by using a non-negative optimization technique instead of orthogonal projection.
A novel particle swarm optimization for papr reduction of ofdm systemsaliasghar1989
This document summarizes a research paper that proposes a new particle swarm optimization (PPSO) technique to reduce the computational complexity of the original PSO (OPSO) method for phase optimization in partial transmit sequence (PTS) peak-to-average power ratio (PAPR) reduction schemes for orthogonal frequency division multiplexing (OFDM) systems. Simulation results show that PPSO achieves nearly the same PAPR performance as OPSO but with lower complexity, as it removes the need for random variables and exhaustive searching in phase factor selection for PTS. The complexity is reduced further as the number of particle generations and sub-blocks increases.
Design and Fabrication of a Two Axis Parabolic Solar Dish CollectorIJERA Editor
The work consists of the design of the chain drive system and the fabrication of the two axis parabolic solar dish.
It is a model study of the two axis parabolic dish which worked by the automatic circuit that was developed. Ready
made parabolic solar dish is taken and fabricated. The circular iron ring provides the two axis motion of the dish.
A compound chain drive system was developed for the smooth movement of the dish. An electromechanical
system which tracks the sun on both axes and which is controlled via a programmable logic control (PLC) was
designed and implemented. In this a theoretical study was done. A C program was made which gave the required
result for the graphical representation of the recorded radiation. Programmable Logic Controls (PLC) was used
instead of photo sensors, which are widely used for tracking the sun. The azimuthal angle of the sun from sunrise
to sunset times was calculated for each day of the year at 23.59 Lat & 72.38Longitude in the Northern hemisphere,
the location of the city Mehsana. According to this azimuth angle, the required analog signal was taken from the
PLC analog module and sent to the power window motor, which controlled the position of the panel to ensure that
the rays fall vertically on the panel. After the mechanical control of the system was started, the performance
measurements of the solar panel were carried out. The values obtained from the measurements were compared and
the necessary evaluations were conducted.
New Bounds on the Size of Optimal MeshesDon Sheehy
The document discusses mesh generation, which involves decomposing a domain into simple elements like triangles or tetrahedra. An optimal mesh has good element quality, conforms to the input domain, and uses the minimum number of points needed to make all Voronoi cells sufficiently "fat" or well-shaped according to metrics like radius-edge ratios. The talk presents analysis showing that the optimal mesh size is determined by the "feature size measure" of the input points, which involves the distance to each point's second nearest neighbor.
The document proposes a time-frequency domain approach for pitch estimation of noisy speech that uses an inverse circular average magnitude difference function to weight the autocorrelation function of pre-filtered noisy speech. It estimates the dominant pitch harmonic in the frequency domain using a cosine model of autocorrelation function before optimally fitting a variable period impulse train to the weighted autocorrelation function for pitch estimation. Simulation results using the Keele speech database show the proposed method achieves better pitch estimation accuracy than conventional autocorrelation-based methods, even at low signal-to-noise ratios down to -10 dB.
Blind Estimation of Carrier Frequency Offset in Multicarrier Communication Sy...IDES Editor
Orthogonal Frequency Division Multiplexing
(OFDM) systems are very sensitive to carrier frequency offset
(CFO), caused by either frequency differences between
transmitter and receiver local oscillators or by frequency
selective channels. The CFO disturbs the orthogonality among
subcarriers of OFDM system and results intercarrier
interference (ICI), which degrades the bit error rate (BER)
performance of the system. This paper presents a new blind
CFO estimation scheme for single-input single-output (SISO)
OFDM systems. The presented scheme is based on the
assumption that the channel frequency response changes
slowly in frequency domain. In this scheme an excellent tradeoff
between complexity and performance, as compared to
existing estimation schemes, is obtained. The improved
performance of the present scheme is confirmed through
extensive simulations.
The document proposes a successive overrelaxation (SOR)-based linear precoding scheme to reduce the complexity of matrix inversion required for regularized zero-forcing (RZF) precoding in massive MIMO systems. The SOR-based precoding approximates the matrix inversion using an iterative SOR method, which can reduce complexity by about one order of magnitude compared to RZF precoding. It is also shown to converge within a few iterations and achieve performance close to RZF precoding. An empirical formula is provided to choose the optimal relaxation parameter for the SOR method in practical massive MIMO configurations.
This document proposes methods to make relational data clustering algorithms more robust against noise and outliers. It applies the concept of noise clustering, originally developed for object data clustering, to several relational data clustering algorithms. Specifically, it extends the Roubens algorithm, the RFCM algorithm of Hathaway et al., and proposes a new Fuzzy Relational Data Clustering (FRC) algorithm based on generalization of the FANNY algorithm. The extensions introduce a separate noise class and define the noise distance to make the algorithms less sensitive to noise in the relational data. The document demonstrates the robustness of the new algorithms through examples.
This document presents a new approach to modeling speech spectra and pitch for text-independent speaker identification using Gaussian mixture models based on multi-space probability distribution (MSD-GMM). The MSD-GMM allows modeling of continuous pitch values for voiced frames and discrete symbols representing unvoiced frames in a unified framework. Spectral and pitch features are jointly modeled by a two-stream MSD-GMM. Maximum likelihood estimation formulae are derived for the MSD-GMM parameters. Experimental results show the MSD-GMM can efficiently model spectral and pitch features of each speaker and outperforms conventional speaker models.
The document proposes a GreenMST solution that uses the minimum spanning tree (MST) algorithm to calculate a loop-free topology for OpenFlow networks using the learning switch module. This prevents broadcast storms while enabling failover capabilities. The MST is recomputed dynamically in response to topology changes to open and close ports. An implementation was created using Open vSwitch and the Beacon controller that demonstrated the ability of GreenMST to efficiently compute the MST and update port statuses with changes to links or switches. Future work is proposed to integrate dynamic link costs and alternative path memorization.
In this paper, we provide the average bit error probabilities of MQAM and MPSK in the presence of log normal shadowing using Maximal Ratio Combining technique for L diversity branches. We have derived probability of density function (PDF) of received signal to noise ratio (SNR) for L diversity branches in Log Normal fadingfor Maximal Ratio Combining (MRC). We have used Fenton-Wilkinson method to estimate the parameters for a single log-normal distribution that approximates the sum of log-normal random variables (RVs). The results that we provide in this paper are an important tool for measuring the performance ofcommunication links in a log-normal shadowing.
Analysis of Peak to Average Power Ratio Reduction Techniques in Sfbc Ofdm SystemIOSR Journals
This document summarizes techniques to reduce peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing (OFDM) systems. It analyzes applying selected mapping (SLM) and clipping with differential scaling techniques to space frequency block coded (SFBC) OFDM systems. SLM generates alternative representations of OFDM symbols by rotating frames with different phase sequences and selects the one with minimum PAPR. Clipping clips signal amplitudes above a threshold and differential scaling scales different amplitude ranges differently to reduce PAPR without degrading bit error rate. Simulation results show SLM and clipping with scaling effectively reduce PAPR.
11.[23 36]quadrature radon transform for smoother tomographic reconstructionAlexander Decker
This document discusses a technique called quadrature Radon transform for tomographic reconstruction. The quadrature Radon transform uses projections from two angles (θ and θ+π/2) rather than just one angle as in conventional Radon transform. This provides additional information that can yield smoother reconstructions. Two approaches are proposed: 1) treating the two sets of projections as real and imaginary parts of a complex number, or 2) averaging the individual back projections. Experimental results show the quadrature Radon transform produces numerically and visually better reconstructions compared to using a single set of projections.
11.quadrature radon transform for smoother tomographic reconstructionAlexander Decker
This document discusses a technique called quadrature Radon transform for tomographic reconstruction. The quadrature Radon transform uses projections from two angles (θ and θ+π/2) rather than just one angle as in conventional Radon transform. This provides additional information that can yield smoother reconstructions. Two approaches are proposed - treating the two sets of projections as real and imaginary parts of a complex number, or averaging the individual back projections. Experimental results show the quadrature Radon transform produces numerically and visually better reconstructions compared to using projections from a single angle.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
This document describes a MATLAB simulation project investigating digital modulation, sampling receivers, the Nyquist criterion, intersymbol interference, and pulse shaping. The project involves building a basic digital modulator and sampling receiver in Simulink. Experiments are conducted introducing intersymbol interference by overlapping pulses and using different pulse shapes, including a Nyquist pulse. The results demonstrate how intersymbol interference affects the signal and how satisfying the Nyquist criterion can prevent interference during sampling.
This document discusses the effect of multipath on covariance-based beamforming in MIMO radar.
It begins with an introduction to MIMO radar and covariance-based beamforming methods. It then presents a signal model that incorporates multipath effects, showing how the beam pattern expression is modified.
Simulations are shown analyzing how multipath can change the beam pattern peak direction, increase sidelobe levels, and produce false peaks, depending on the random amplitudes and phases of the multipath signals. Increasing the number of multipath paths or their phase variance generally leads to greater errors in the desired beam pattern.
DUNE on current and next generation HPC PlatformsMarkus Blatt
In this talk we present the Distributed and Unified Numerics
Environment (DUNE). It is a software framework for the parallel
numerical solution of partial differential equations with grid-based
methods. Using generic programming techniques it strives for both:
high flexibility (efficiency of the programmer) and high performance
(efficiency of the program).
We present parallel applications realized with DUNE and
show their scalability on current HPC platforms such as the Blue
Gene/P system in Jülich.
Finally we will take a closer look on hardware attributes that
influence the scalability of DUNE and software solving partial
differential equations in general. We investigate how DUNE will
perform on future hardware like Blue Gene/Q.
Special emphasis will be put on the performance of parallel
iterative solvers both in general and in DUNE.
This document discusses performance of matching algorithms for signal approximation. It begins by introducing matching pursuit algorithms like Orthogonal Matching Pursuit (OMP) and Stagewise Orthogonal Matching Pursuit (StOMP) which are greedy algorithms that approximate sparse signals. It then describes the Non-Negative Least Squares algorithm which solves non-negative least squares problems. Finally, it discusses Extranious Equivalent Detection (EED), a modification of OED that incorporates non-negativity of representations by using a non-negative optimization technique instead of orthogonal projection.
A novel particle swarm optimization for papr reduction of ofdm systemsaliasghar1989
This document summarizes a research paper that proposes a new particle swarm optimization (PPSO) technique to reduce the computational complexity of the original PSO (OPSO) method for phase optimization in partial transmit sequence (PTS) peak-to-average power ratio (PAPR) reduction schemes for orthogonal frequency division multiplexing (OFDM) systems. Simulation results show that PPSO achieves nearly the same PAPR performance as OPSO but with lower complexity, as it removes the need for random variables and exhaustive searching in phase factor selection for PTS. The complexity is reduced further as the number of particle generations and sub-blocks increases.
Design and Fabrication of a Two Axis Parabolic Solar Dish CollectorIJERA Editor
The work consists of the design of the chain drive system and the fabrication of the two axis parabolic solar dish.
It is a model study of the two axis parabolic dish which worked by the automatic circuit that was developed. Ready
made parabolic solar dish is taken and fabricated. The circular iron ring provides the two axis motion of the dish.
A compound chain drive system was developed for the smooth movement of the dish. An electromechanical
system which tracks the sun on both axes and which is controlled via a programmable logic control (PLC) was
designed and implemented. In this a theoretical study was done. A C program was made which gave the required
result for the graphical representation of the recorded radiation. Programmable Logic Controls (PLC) was used
instead of photo sensors, which are widely used for tracking the sun. The azimuthal angle of the sun from sunrise
to sunset times was calculated for each day of the year at 23.59 Lat & 72.38Longitude in the Northern hemisphere,
the location of the city Mehsana. According to this azimuth angle, the required analog signal was taken from the
PLC analog module and sent to the power window motor, which controlled the position of the panel to ensure that
the rays fall vertically on the panel. After the mechanical control of the system was started, the performance
measurements of the solar panel were carried out. The values obtained from the measurements were compared and
the necessary evaluations were conducted.
New Bounds on the Size of Optimal MeshesDon Sheehy
The document discusses mesh generation, which involves decomposing a domain into simple elements like triangles or tetrahedra. An optimal mesh has good element quality, conforms to the input domain, and uses the minimum number of points needed to make all Voronoi cells sufficiently "fat" or well-shaped according to metrics like radius-edge ratios. The talk presents analysis showing that the optimal mesh size is determined by the "feature size measure" of the input points, which involves the distance to each point's second nearest neighbor.
The document proposes a time-frequency domain approach for pitch estimation of noisy speech that uses an inverse circular average magnitude difference function to weight the autocorrelation function of pre-filtered noisy speech. It estimates the dominant pitch harmonic in the frequency domain using a cosine model of autocorrelation function before optimally fitting a variable period impulse train to the weighted autocorrelation function for pitch estimation. Simulation results using the Keele speech database show the proposed method achieves better pitch estimation accuracy than conventional autocorrelation-based methods, even at low signal-to-noise ratios down to -10 dB.
Blind Estimation of Carrier Frequency Offset in Multicarrier Communication Sy...IDES Editor
Orthogonal Frequency Division Multiplexing
(OFDM) systems are very sensitive to carrier frequency offset
(CFO), caused by either frequency differences between
transmitter and receiver local oscillators or by frequency
selective channels. The CFO disturbs the orthogonality among
subcarriers of OFDM system and results intercarrier
interference (ICI), which degrades the bit error rate (BER)
performance of the system. This paper presents a new blind
CFO estimation scheme for single-input single-output (SISO)
OFDM systems. The presented scheme is based on the
assumption that the channel frequency response changes
slowly in frequency domain. In this scheme an excellent tradeoff
between complexity and performance, as compared to
existing estimation schemes, is obtained. The improved
performance of the present scheme is confirmed through
extensive simulations.
The document proposes a successive overrelaxation (SOR)-based linear precoding scheme to reduce the complexity of matrix inversion required for regularized zero-forcing (RZF) precoding in massive MIMO systems. The SOR-based precoding approximates the matrix inversion using an iterative SOR method, which can reduce complexity by about one order of magnitude compared to RZF precoding. It is also shown to converge within a few iterations and achieve performance close to RZF precoding. An empirical formula is provided to choose the optimal relaxation parameter for the SOR method in practical massive MIMO configurations.
This document proposes methods to make relational data clustering algorithms more robust against noise and outliers. It applies the concept of noise clustering, originally developed for object data clustering, to several relational data clustering algorithms. Specifically, it extends the Roubens algorithm, the RFCM algorithm of Hathaway et al., and proposes a new Fuzzy Relational Data Clustering (FRC) algorithm based on generalization of the FANNY algorithm. The extensions introduce a separate noise class and define the noise distance to make the algorithms less sensitive to noise in the relational data. The document demonstrates the robustness of the new algorithms through examples.
This document presents a new approach to modeling speech spectra and pitch for text-independent speaker identification using Gaussian mixture models based on multi-space probability distribution (MSD-GMM). The MSD-GMM allows modeling of continuous pitch values for voiced frames and discrete symbols representing unvoiced frames in a unified framework. Spectral and pitch features are jointly modeled by a two-stream MSD-GMM. Maximum likelihood estimation formulae are derived for the MSD-GMM parameters. Experimental results show the MSD-GMM can efficiently model spectral and pitch features of each speaker and outperforms conventional speaker models.
The document proposes a GreenMST solution that uses the minimum spanning tree (MST) algorithm to calculate a loop-free topology for OpenFlow networks using the learning switch module. This prevents broadcast storms while enabling failover capabilities. The MST is recomputed dynamically in response to topology changes to open and close ports. An implementation was created using Open vSwitch and the Beacon controller that demonstrated the ability of GreenMST to efficiently compute the MST and update port statuses with changes to links or switches. Future work is proposed to integrate dynamic link costs and alternative path memorization.
This document discusses the design of a pipelined architecture for sparse matrix-vector multiplication on an FPGA. It begins with introductions to matrices, linear algebra, and matrix multiplication. It then describes the objective of building a hardware processor to perform multiple arithmetic operations in parallel through pipelining. The document reviews literature on pipelined floating point units. It provides details on the proposed pipelined design for sparse matrix-vector multiplication, including storing vector values in on-chip memory and using multiple pipelines to complete results in parallel. Simulation results showing reduced power and execution time are presented before concluding the design can improve performance for scientific applications.
This document provides the solutions to selected problems from the textbook "Introduction to Parallel Computing". The solutions are supplemented with figures where needed. Figure and equation numbers are represented in roman numerals to differentiate them from the textbook. The document contains solutions to problems from 13 chapters of the textbook covering topics in parallel computing models, algorithms, and applications.
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...Pooyan Jamshidi
https://arxiv.org/abs/1606.06543
Finding optimal configurations for Stream Processing Systems (SPS) is a challenging problem due to the large number of parameters that can influence their performance and the lack of analytical models to anticipate the effect of a change. To tackle this issue, we consider tuning methods where an experimenter is given a limited budget of experiments and needs to carefully allocate this budget to find optimal configurations. We propose in this setting Bayesian Optimization for Configuration Optimization (BO4CO), an auto-tuning algorithm that leverages Gaussian Processes (GPs) to iteratively capture posterior distributions of the configuration spaces and sequentially drive the experimentation. Validation based on Apache Storm demonstrates that our approach locates optimal configurations within a limited experimental budget, with an improvement of SPS performance typically of at least an order of magnitude compared to existing configuration algorithms.
Continuous Architecting of Stream-Based SystemsCHOOSE
Pooyan Jamshidi CHOOSE Talk 2016-11-01
Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors making it a difficult task for software architects to refactor the initial designs. As an aid to designers and developers, we developed OSTIA (On-the-fly Static Topology Inference Analysis) that allows: (a) visualizing big data architectures for the purpose of design-time refactoring while maintaining constraints that would only be evaluated at later stages such as deployment and run-time; (b) detecting the occurrence of common anti-patterns across big data architectures; (c) exploiting software verification techniques on the elicited architectural models. In the lecture, OSTIA will be shown on three industrial-scale case studies.
See: http://www.choose.s-i.ch/events/jamshidi-2016/
An Area Efficient Vedic-Wallace based Variable Precision Hardware Multiplier ...IDES Editor
The complete architecture with the necessary blocks
and their internal structures are proposed in this paper. In
this algorithm the complete variable precision format is
utilized for the multiplication of the two numbers with a size
of nxn bits. The internal multiplier is choosen for m bit size
and is implemented using vedic-wallace structure for high
speed implementation. The architecture includes the
calculation of all the fields in the format for complete output.
The exponent of the final result is obtained by using carry
save adder for fast computations with less area utilization.
This multiplier uses the concept of MAC unit, giving rise to
more accurate results having a bits size of the final result will
be 2n2.
Approaches to online quantile estimationData Con LA
Data Con LA 2020
Description
This talk will explore and compare several compact data structures for estimation of quantiles on streams, including a discussion of how they balance accuracy against computational resource efficiency. A new approach providing more flexibility in specifying how computational resources should be expended across the distribution will also be explained. Quantiles (e.g., median, 99th percentile) are fundamental summary statistics of one-dimensional distributions. They are particularly important for SLA-type calculations and characterizing latency distributions, but unlike their simpler counterparts such as the mean and standard deviation, their computation is somewhat more expensive. The increasing importance of stream processing (in observability and other domains) and the impossibility of exact online quantile calculation together motivate the construction of compact data structures for estimation of quantiles on streams. In this talk we will explore and compare several such data structures (e.g., moment-based, KLL sketch, t-digest) with an eye towards how they balance accuracy against resource efficiency, theoretical guarantees, and desirable properties such as mergeability. We will also discuss a recent variation of the t-digest which provides more flexibility in specifying how computational resources should be expended across the distribution. No prior knowledge of the subject is assumed. Some familiarity with the general problem area would be helpful but is not required.
Speaker
Joe Ross, Splunk, Principal Data Scientist
Development of Multi-level Reduced Order MOdeling MethodologyMohammad
This document summarizes the development of a new multi-level reduced order modeling (MLROM) methodology. MLROM allows extracting the effective dimensionality of a high-fidelity nuclear reactor model by executing the model in a small sub-domain, like a pin cell, rather than the entire domain. This significantly reduces computational cost compared to previous ROM methods. The document describes the mathematical framework of MLROM and presents initial numerical tests of the method using a benchmark boiling water reactor lattice model. Results suggest MLROM can accurately represent the full model while requiring far fewer executions of the high-fidelity code.
This document summarizes the development of a multi-level reduced order modeling (MLROM) methodology. MLROM uses a physics-informed approach to extract an active subspace by executing a high-fidelity model on sub-domains, like a pin cell, rather than the full domain like the whole core. This reduces computational cost. Error bounds for the reduced model are established using the pin-cell determined active subspace and verified against full-order lattice simulations. Future work will apply MLROM to core-wide calculations using representative lattices to capture the core-wide active subspace.
Fuzzy Logic And Application Jntu Model Paper{Www.Studentyogi.Com}guest3f9c6b
This document contains an exam for a course on Fuzzy Logic and Applications. It includes 8 questions covering topics such as operations on crisp and fuzzy sets using Venn diagrams, fuzzy relations, membership functions, fuzzy logic connectives, defuzzification methods, and decision making under fuzzy conditions. Students are instructed to answer any 5 of the 8 questions.
Exact network reconstruction from consensus signals and one eigen valueIJCNCJournal
The basic inverse problem in spectral graph theory consists in determining the graph given its eigenvalue
spectrum. In this paper, we are interested in a network of technological agents whose graph is unknown,
communicating by means of a consensus protocol. Recently, the use of artificial noise added to consensus
signals has been proposed to reconstruct the unknown graph, although errors are possible. On the other
hand, some methodologies have been devised to estimate the eigenvalue spectrum, but noise could interfere
with the elaborations. We combine these two techniques in order to simplify calculations and avoid
topological reconstruction errors, using only one eigenvalue. Moreover, we use an high frequency noise to
reconstruct the network, thus it is easy to filter the control signals after the graph identification. Numerical
simulations of several topologies show an exact and robust reconstruction of the graphs.
A study of localized algorithm for self organized wireless sensor network and...eSAT Journals
1. The document discusses localized algorithms for self-organized wireless sensor networks and analyzes the Algorithm for Cluster Establishment (ACE). ACE is an emergent algorithm that allows nodes to assess their potential as cluster heads and step down if another node is better.
2. ACE works through iterations of spawning new clusters and migration of existing ones. Migration selects the best candidate cluster head based on number of followers. Parameters like the spawning threshold function are also discussed.
3. The performance of ACE is evaluated through simulations comparing average cluster size and standard deviation for different parameters and iterations. Figures and tables show the clustering process and outputs of sensor nodes for different data sets.
A study of localized algorithm for self organized wireless sensor network and...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The mean shift procedure is a general nonparametric technique for analyzing complex multimodal feature spaces and delineating arbitrarily shaped clusters. It works by recursively finding the nearest stationary point of the underlying density function, which corresponds to the mode of the density. The mean shift procedure relates to kernel density estimation and robust M-estimators of location. It provides a versatile tool for feature space analysis that can solve many low-level computer vision tasks with few parameters.
Event driven, mobile artificial intelligence algorithmsDinesh More
This document summarizes a paper presented at the 2010 Second International Conference on Computer Modeling and Simulation. The paper proposes a novel methodology called BoilingJulus for deploying object-oriented languages. BoilingJulus is built on the principles of hardware and architecture and is based on improving public-private key pairs. The paper describes the implementation of BoilingJulus and analyzes its performance through various experiments and comparisons to other methodologies.
The large-scale cyberinformatics method to replication is defined not only by the analysis of local-area networks, but also by the structured need for the Internet. Here, we confirm the refinement of superpages, which embodies the unfortunate principles of operating systems. SHODE, our new methodology for secure methodologies, is the solution to all of these obstacles.
The document describes the Pochoir stencil compiler, which allows programmers to write specifications for stencil computations in a domain-specific language embedded in C++. The Pochoir compiler then translates these specifications into high-performance parallel Cilk code using an efficient cache-oblivious algorithm called TRAP. Benchmark results show that the Pochoir-generated code runs 2-10 times faster than standard parallel loop implementations for a variety of stencil computations.
This document discusses the use of linear algebra in various domains such as graphs and networks, chemistry, mechanics, quantum computing, chaos theory, coding and error correction, data compression, solving systems of equations, games, statistics, game theory, neural networks, Markov chains, splines, symbolic dynamics, inverse problems, and a "Will Hunting" problem posed in the movie Good Will Hunting. Linear algebra provides useful tools and representations for understanding concepts in these diverse areas. The document aims to illustrate the wide applicability and relevance of learning linear algebra.
Linear algebra has many applications including understanding networks and graphs, modeling complex systems like bridges and molecules, quantum computing, chaos theory, coding and error correction, data compression, and solving systems of equations. It can be used to analyze vibrations, study dynamical systems, and efficiently solve Lagrange multiplier systems.
An Algorithm For Vector Quantizer DesignAngie Miller
The document presents an algorithm for designing vector quantizers. The algorithm is efficient, intuitive, and can be used for quantizers with general distortion measures and large block lengths. It is based on Lloyd's approach but does not require differentiation, making it applicable even when the data distribution has discrete components. The algorithm finds quantizers that meet necessary optimality conditions. Examples show it converges well and finds near-optimal quantizers for memoryless Gaussian sources. It is also used successfully to quantize LPC speech parameters with a complicated distortion measure.
1) The document describes a modification to the Huffman coding used in JPEG image compression. It proposes pairing each non-zero DCT coefficient with the run-length of subsequent (rather than preceding) zero coefficients.
2) This allows using separate optimized Huffman code tables for each DCT coefficient position, improving compression by 10-15% over standard JPEG coding.
3) The decoding procedure is not changed and no end-of-block marker is needed, providing advantages with no increase in complexity.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
OpenID AuthZEN Interop Read Out - AuthorizationDavid Brossard
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
WeTestAthens: Postman's AI & Automation Techniques
Space time
1. CITED BY 9
Space-Time Trade-Off Optimization for a Class of
Electronic Structure Calculations
Daniel Cociorva Gerald Baumgartner Chi-Chung Lam P. Sadayappan
J. Ramanujam Marcel Nooijen David E. Bernholdt Robert Harrison
Dept. of Computer and Information Science Department of Chemistry
The Ohio State University Princeton University
cociorva,gb,clam,saday Nooijen@Princeton.edu
@cis.ohio-state.edu Oak Ridge National Laboratory
bernholdtde@ornl.gov
Dept. of Electrical and Computer Engineering
Louisiana State University Pacific Northwest National Laboratory
jxr@ece.lsu.edu Robert.Harrison@pnl.gov
ABSTRACT : 1. INTRODUCTION
The development of high-performance parallel programs for sci-
The accurate modeling of the electronic structure of atoms and
molecules is very computationally intensive. Many models of elec- entific applications is usually very time consuming. The time to de-
tronic structure, such as the Coupled Cluster approach, involve col- velop an efficient parallel program for a computational model can
lections of tensor contractions. There are usually a large number be a primary limiting factor in the rate of progress of the science.
of alternative ways of implementing the tensor contractions, rep- Our long term goal is to develop a program synthesis system to fa-
resenting different trade-offs between the space required for tem- cilitate the development of high-performance parallel programs for
porary intermediates and the total number of arithmetic operations. a class of scientific computations encountered in quantum chem-
In this paper, we present an algorithm that starts with an operation- istry. The domain of our focus is electronic structure calculations,
3. n the class ofrequired. Consider the following expression: be
operations computations considered, the final result to ing to the fused loop to be eliminate
puted can be expressed in terms of tensor contractions, essen- quirement for the computation is to view
a smaller intermediate array and thu
y a collection of multi-dimensional summations of the product loop fusions. Loop fusion merges loop ne
ments. For the example considered
everal input arrays. Due to commutativity, associativity, and loops illustrated in Fig. 1(c). By use loop
into larger imperfectly nested of lo
ributivity, expressionmany different ways to compute the finalnested produces an intermediate array actually be
If this there are is directly translated to code (with ten can be seen that can which is co
in the number arithmetic operations nest, fusing the two loop nests allows the
lt,loops, for could differ widely total number ofof floating point
and they indices ), the
a 2-dimensional array, without chan
rations required. be Consider theif the range of each index
following expression: ing to operations.
the fused loop to be eliminated in t
required will is . a smallerFor a computation comprising of a
intermediate array and thus reduc
Instead, the same expression can be rewritten by use of associative ments.will generally be a number of fusio
For the example considered, the
and distributive laws as the following: illustrated incompatible.By useis because
tually Fig. 1(c). This of loop fus
can berequire different loops to bebe reduc
seen that can actually made th
his expression is directly translated to code (with ten nested a 2-dimensional the problem ofchanging t
ps, for indices ), the total number of arithmetic operations addressed array, without finding the
operations.
operator tree that minimized the tota
uired will be if the range of each index is . For after fusion [14, 16, 15]. of a numb
a computation comprising
ead, the same expression can be rewritten by use of associative will generally be a for manyof fusion choi
However, number of the compu
distributive laws as the the formula sequence shown in Fig. 1(a) and tually compatible. This is because differe
This corresponds to following:
can be directly translated into code as shown in Fig. 1(b). This require different loopscomponent of the NW
coupled cluster
form only requires instances where to be made the outer
operations. However, additional space addressed the problem thefinding the choic minimal memo
and . S=0 fusion is still tooof
S = 0
is required to store temporary arrays T1=0; T2=0;Often, the space operator tree that minimized theIn such sit large.
for b, c
for b, c, d, e, f, l executable implementation, it isspac
requirements for the temporary arrays poses a serious problem. For after fusion [14,0; T2f = 0 T1f =
total ess
T1bcdf += Bbefl Dcdel by for d, 16, 15].
f
only storing lower dimensional s
this example, abstracted from a quantum chemistry model, the ar- However, for e, l of the computation
for b, c, d, f, j, k for many
s corresponds to the indices sequence the largest, while the dfjk
ray extents along formula shown in += T1bcdf and
T2bcjk Fig. 1(a) C extents
are for a, b, c, i, j, k recomputing the befl Dcdel
T1f += B slices as needed. Th
into code as shown in Fig. 1(b). of tempo- coupled clusterwe address in this paper. We
be directly translatedare the smallest. Therefore, the sizeThis
along indices problem component of the NWChem
for j, k
Sabij += T2bcjk Aacik instances whereconceptT1f aCfusion graph
T2f the minimal dfjk
m only requires would dominate theHowever, additional space
rary array operations. total memory requirement. proposed jk += k of memory req
quired to store temporary arrays and (b) Direct implementation
. Often, the space fusion isfor a, i, j, In such situation
still too large.
Sabij += T2fjk A
(a) Formula sequence (unfused code)
uirements for the temporary arrays poses a serious problem. For executable implementation, acik essential
it is
(c) Memory-reduced implementation (fused)
example, abstracted from a quantum chemistry model, thefusion for memory reduction. lower dimensional slices o
Figure 1: Example illustrating use of loop ar- by only storing
extents along indices are the largest, while the extents recomputing the slices as needed. This is th
178
g indices are the smallest. Therefore, the size of tempo- problem we address in this paper. We exten
ussian, NWChem, PSI, and MOLPRO. In particular, they com- The operationproposed concept of a fusion here is a and de
minimization problem encountered graph gen-
array
se the bulk of the computation with thetotal memoryapproach
would dominate the coupled cluster requirement. eralization of the well known matrix-chain multiplication problem,
5. Fusion Graph
can be used to facilitate enumeration of all possible compatible fusion configurations
for a given computation tree.
The potential for fusion of a common loop among a producer-consumer pair of loop
nests is indicated in the fusion graph through a dashed edge connecting
the corresponding vertices.
ceaf Althoug
E +ceaf number of
theory gro
bk number of
X +ij Y +bk and there
size of the
The fus
T T T1 T2 problem, w
aei j cf i j
the fusion
gorithm w
f1 f2 and find th
cebk af bk
and and
the size of
Figure 5: Fusion graph for unfused operation-minimal form of unable to r
loop in Figure 2. arrays wo
6. Example (1)
for a, e, c, f for a, e, c, f A desirable solution would be somewhere in bet
for i, j for i, j
X += Tijae Tijcf fused structure of Fig. 2 (with maximal memory req
Xaecf += Tijae Tijcf maximal reuse) and the fully fused structure of Fig.
for a, f for b, k
T1 = f (c,e,b,k) imal memory requirement and minimal reuse). Thi
for c, e, b, k
T1cebk = f (c,e,b,k) T2 = f (a,f,b,k) Fig. 4, where tiling and partial fusion of the loops
Y += T1 T2 The loops with indices are tiled by splitting
for c, e
for a, f, b, k E += X Y indices into a pair of indices. The indices with a super
T2afbk = f (a,f,b,k) sent the tiling loops and the unsuperscripted indices
array space time
for c, e, a, f
X 1
intra-tile loops with a range of , the block size used
for b, k each tile , blocks of and of size
T1 1
Yceaf += T1cebk T2afbk puted and used to form product contributions to th
T2 1
for c, e, a, f ceaf
components of , which are stored in an array of siz
Y 1
E += Xaecf Yceaf E +ceaf As the tile size is increased, the cost of function
E 1
for decreases by factor , due to the reuse e
Figure 3: Use of redundant computation to allow full fusion. ever, the size of the neededb ktemporary array for in
X +ij (the space needed for can actually be reduced back
Y +bk
for a , e , c , f fusing its producer loop with the loop producing E,
for a, e, c, f requirement cannot be decreased). When becom
for i, j the size of physical memory, expensive paging in an
Xaecf += Tijae Tijcf T T T
array space time will be required for T1 Further, there are diminishi
. T2
for b, k aei j c freuse of
i j e
for c, e X and after becomes comparable
T1ce = f (c,e,b,k) T1 the loop producing now becomes the dominant on
for a, f T2 expect that as f1 increased, performance will imp
is f2
T2af = f (a,f,b,k) Y level off and then deteriorate. The optimum value of
cebk af bk
for c, e, a, f E 1
(a) Fully fused computation from Fig. 3. at the various levels o
depend on the cost of access
Yceaf += T1ce T2af hierarchy.
for c, e, a, f The computation consideredgraphs just one com
E += Xaecf Yceaf Figure 6: Fusion here is showing re
7. T2 1
for c, e, a, f components of , which are stored in
Y 1
E += Xaecf Yceaf
Example (2)
E 1 As the tile size is increased, the
for decreases by factor , du
Figure 3: Use of redundant computation to allow full fusion. ever, the size of the needed temporar
(the space needed for can actually
for a , e , c , f fusing its producer loop with the loo
for a, e, c, f requirement cannot be decreased). W
for i, j the size of physical memory, expens
Xaecf += Tijae Tijcf
array space time will be required for . Further, the
for b, k
for c, e X reuse of and after becom
T1ce = f (c,e,b,k) T1 the loop producing now becomes
for a, f T2 expect that as is increased, perfor
T2af = f (a,f,b,k) Y level off and then deteriorate. The op
for c, e, a, f E 1
depend on the cost of access at the
Yceaf += T1ce T2af hierarchy.
for c, e, a, f ct et at f t c e a f
E +ceaf The computation considered here
E += Xaecf Yceaf
term, which in turn is only one
bk be computed. Although developers
Figure 4: Use of tiling and partial fusion to reduce recomputa- bk
naturally recognize and+bk
Y perform some
tion cost. Y +bk X +ij
lective analysis of all these computati
implementation is beyond the scope o
developments in optimizing compiler
reuse of the stored T2
T1 integrals T
in and (each element of
T and T1 T2
et at a e i j ct f t f i j
nificant strides in data locality optimi
is used times). However, it is impractical cdue to the
existing work that addresses the kind
huge memory requirement. With and , the size
mization required in the context we c
f1 of , is f2 bytes and the size of , is bytes. f1 f2
k By fusing together pairs of producer-consumer loops in the compu- t et c e b k
af bk c at f t a f b k
tation, reductions in the needed array sizes may Partially fused computation from Fig. 4.
n from Fig. 3. (b) be sought, since the
fusion of a loop with common index in the pair of loops allows the
4. SOLUTION APPROA
elimination of that dimension of the intermediate array. It can be
ure 6: Fusion graphs showing redundant compution and tiling. GRAPH
8. so be made fu-
lem discussed in the previous sub-section, requiring that selective
ng fusion edges
Space-Time Tradeoff Exploration
search strategies be developed.
ully fused with
In this paper, we develop a two-step search strategy for explo-
oducer loop for
ration of the space-time trade-off:
n edge (say for
hains for and Search among all possible ways of introducing redundant
loop indices in the fusion graph to reduce memory require-
sented graphi- ments, and determine the optimal set of lower dimensional
ve been added intermediate arrays for various total memory limits. In this
es correspond- step, the use of tiling for partial reduction of array extents is
omplete fusion not considered. However, among all possible combinations
n the scopes of of lower dimensional arrays for intermediates, the combina-
that in fact the tion that minimizes recomputation cost is determined, for a
of or to specified memory limit. The range from zero to the actual
the additional memory limit is split into subranges within which the op-
partial-overlap timal combination of lower dimensional arrays remains the
same.
hm [16, 14] to
s the total stor- Because the first step only considers complete fusion of loops,
s. A bottom-up each array dimension is either fully eliminated or left intact,
intains a set of i.e. partial reduction of array extents is not performed. The
merging solu- objective of the second step is to allow for such arrays. Start-
onfigurations at ing from each of the optimal combinations of lower dimen-
y required un- sional intermediate arrays derived in the first step, possible
s imposed by a ways of using tiling to partially expand arrays along previ-
uration is infe- ously compressed dimensions are explored. The goal is to
g” with respect further reduce recomputation cost by partially expanding ar-
memory. At the rays to fully utilize the available memory
ry requirement
9. Space-Time optimization
Dimension Reduction for Intermediate Arrays
search among all possible combination
memory and recomputation costs
Partial Expansion of Reduced Intermediates
resort to array expansion
for determining the best choice for array
expansion costs
10. Result
15 over
10
clus
1 the d
Memory limit
L
sion
Memory usage (words)
10
10
2 and
anis
3 repe
fusi
10
5
4
at m
5 tion
and
refe
0 6
10 0 5 10 15 20 25 T
10 10 10 10 10 10
Recomputation cost (floating point operations) ory
alig
by f