Serial Version Research Articles

Results of experimental studies of a tractor equipped with an elastic-damping mechanism when aggregated with a seeder

One of the significant factors influencing the operation of the tractor is the unsteady load that occurs when starting off, during the initial period of acceleration and deceleration. The elastic-damping mechanisms are used to reduce the negative consequences of such loads. Scientists still develop and study their application.
 In this article, the analysis of the cross correlation function and the analysis of the mutual spectral density of two processes were carried out. The analyzed processes were the engine crankshaft speed and the drive wheel speed. This analysis shows the change in the speed of the passing load frequencies along the shaft line of the traction class 1,4 wheeled tractor power transmission, where an elastic-damping mechanism is installed. The studies were carried out for the operating conditions of a tractor with a seeder. The purpose of the study was to determine the effect of the elastic-damping mechanism installed in the power transmission of a tractor on its operation with a trailed seeder.
 In the general case, the object of research is the functioning of a tractor of traction class 1,4 process, which is located in a unit with a seeder. Analysis of the mutual correlation function of the two processes showed a change in the speed of the passing load frequencies along the shaft line. The ratio of the propagation time of the disturbance signal in the experimental tractor in relation to the production version along the shaft line when aggregating the tractor with the seeder decreases by 40,1 %. The analysis of the mutual spectral density shows a shift in the frequency of disturbing influences in relation to the serial version and a decrease in their value when the tractor is aggregated with a seeder by 33,3 %. The value of the mutual spectral density is lower in the experimental version of the tractor, which may mean that the elastic-damping mechanism, as an element of the power transmission, absorbs part of the load fluctuations and reduces their propagation speed along the shaft line.

A particle packing parallel geometric method using GPU

The purpose of this paper is to present a methodology for obtaining granular models from a GPU parallel implementation of the geometric separation particle packing strategy. This methodology is suitable for the generation of large-scale granular models used in discontinuous media simulations. The proposed approach uses disk-shaped particles (two-dimensional approach) and parallelization mechanisms that consider different computational environments, with a focus on GPUs. The methodology is divided into three macro-steps: (a) definition of an input set of particles; (b) geometric separation; and (c) removal of spurious particles. The set of input particles uses data related to the particle size distribution and the domain filling rate, defining arbitrary positions for the particles. The other steps are used to eliminate overlaps between particles. Parallel computing is performed using the OpenCL programming API on compatible devices. Examples are presented to show the effectiveness of the proposed methodology. They show good time improvement and better memory efficiency in comparison with the original serial version of the strategy. The method is also validated by comparing the results with experimental and numerical data from the literature. The proposed methodology allows generating granular models with a parallel GPU particle packing method. It turns possible the achievement of bigger models in a smaller amount of time, without compromising the strategy efficiency and accuracy. It also presents mechanisms to avoid information exchange between GPU and CPU.

Serial and Parallel Iterative Splitting Methods: Algorithms and Applications to Fractional Convection-Diffusion Equations

The benefits and properties of iterative splitting methods, which are based on serial versions, have been studied in recent years, this work, we extend the iterative splitting methods to novel classes of parallel versions to solve nonlinear fractional convection-diffusion equations. For such interesting partial differential examples with higher dimensional, fractional, and nonlinear terms, we could apply the parallel iterative splitting methods, which allow for accelerating the solver methods and reduce the computational time. Here, we could apply the benefits of the higher accuracy of the iterative splitting methods. We present a novel parallel iterative splitting method, which is based on the multi-splitting methods, The flexibilisation with multisplitting methods allows for decomposing large scale operator equations. In combination with iterative splitting methods, which use characteristics of waveform-relaxation (WR) methods, we could embed the relaxation behavior and deal better with the nonlinearities of the operators. We consider the convergence results of the parallel iterative splitting methods, reformulating the underlying methods with a summation of the individual convergence results of the WR methods. We discuss the numerical convergence of the serial and parallel iterative splitting methods with respect to the synchronous and asynchronous treatments. Furthermore, we present different numerical applications of fluid and phase field problems in order to validate the benefit of the parallel versions.

Helmholtz solving and performance optimization in global/regional assimilation and prediction system

Despite efficient parallelism in the solution of physical parameterization in the Global/Regional Assimilation and Prediction System (GRAPES), the Helmholtz equation in the dynamic core, with the increase of resolution, can hardly achieve sufficient parallelism in the solving process due to a large amount of communication and irregular access. In this paper, optimizing the Helmholtz equation solution for better performance and higher efficiency has been an urgent task. An optimization scheme for the parallel solution of the Helmholtz equation is proposed in this paper. Specifically, the geometrical multigrid optimization strategy is designed by taking advantage of the data anisotropy of grid points near the pole and the isotropy of those near memory equator in the Helmholtz equation, and the Incomplete LU (ILU) decomposition preconditioner is adopted to speed up the convergence of the improved Generalized Conjugate Residual (GCR), which effectively reduces the number of iterations and the computation time. The overall solving performance of the Helmholtz equation is improved by thread-level parallelism, vectorization, and reuse of data in the cache. The experimental results show that the proposed optimization scheme can effectively eliminate the bottleneck of the Helmholtz equation as regards the solving speed. Considering the test results on a 10-node two-way server, the solution of the Helmholtz equation, compared with the original serial version, is accelerated by 100×, with one-third of iterations reduced.

Development of a Parallel 3D Navier–Stokes Solver for Sediment Transport Calculations in Channels

We propose a method to parallelize a 3D incompressible Navier–Stokes solver that uses a fully implicit fractional-step method to simulate sediment transport in prismatic channels. The governing equations are transformed into generalized curvilinear coordinates on a non-staggered grid. To develop a parallel version of the code that can run on various platforms, in particular on PC clusters, it was decided to parallelize the code using Message Passing Interface (MPI) which is one of the most flexible parallel programming libraries. Code parallelization is accomplished by “message passing” whereby the computer explicitly uses library calls to accomplish communication between the individual processors of the machine (e.g., PC cluster). As a part of the parallelization effort, besides the Navier–Stokes solver, the deformable bed module used in simulations with loose beds are also parallelized. The flow, sediment transport, and bathymetry at equilibrium conditions were computed with the parallel and serial versions of the code for the case of a 140-degree curved channel bend of rectangular section. The parallel simulation conducted on eight processors gives exactly the same results as the serial solver. The parallel version of the solver showed good scalability.

Parallel Extended Path Method for Solving Perfect Foresight Models

We parallelize the extended path method for solving rational expectations models, and apply it to compute perfect foresight competitive equilibrium for the global economy with multiple goods, regions, industries, and households. At each iteration, first intertemporal variables are updated, then equations for intra-temporal variables are solved in parallel. We compare serial, and parallel, versions of the extended path method in high-performance computing environments based on scenarios with long time horizons that include future populations, economic growth, energy use, and carbon dioxide emissions. Relative to the serial version, the speedup factor for the parallel extended path method grows almost linearly up to about 30 times with 18 cores, and computing times reduced from over 10 h for the serial version down to about 20 min for the parallel version.

REDUCTION OF THE TENSION OF MODIFIED TEETH OF NOVIKOV GEARING IN THE THREE-STEP GEARBOX Ц3НШ-450-40 DRIVE OF OIL PUMPING UNIT

The article is devoted to the actual topic – reduce the tension of the modified teeth of Novikov gearing drive gearbox of widely used oil pumping unit for oil production in order to increase the resource of their work and load-bearing capacity. As the object is considered a typical three-stage gearbox model Ц3НШ-450-40, produced by the plant “Izhneftemash” (Izhevsk). Gearbox is equipped with Novikov gearing with the basic rack profile according to GOST 15023–76. It is shown that the use of the proposed longitudinal modification of the working surfaces of the teeth in combination with an increase in gear module provides a very significant effect on reducing effective contact and bending stresses, on increase the load-bearing capacity and service life of the gearbox in comparison with the serial version currently produced by the domestic industry. The research is based on the results of solving the spatial contact problem of the stress-strain state of a tooth, as well as modeling the real multipoint engagement of Novikov gearing taking into account the technological errors of manufacture and assembly of gears. Recommendations on the implementation of the longitudinal modification of the teeth are given and it is shown that there are no technological difficulties. The effect achieved at different stages of the gearbox is: to reduce tooth stresses from 1.75 to 2.54 times, to increase the load-bearing capacity of the gearbox from 2.81 to 4.1 times, to increase the service life of the gearbox by an order of magnitude. In the future, the research outlined is supposed to spread to other models of gearboxes produced oil pumping units.

An efficient automated incremental density-based algorithm for clustering and classification

Data clustering divides the datasets into different groups. Incremental Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a famous density-based clustering technique able to find the clusters of variable sizes and shapes. The quality of incremental DBSCAN results has been influenced by two input parameters: MinPts (Minimum Points) and Eps (Epsilon). Therefore, the parameter setting is one of the major problems of incremental DBSCAN. In the present article, an improved incremental DBSCAN accorded to Non-dominated Sorting Genetic Algorithm II (NSGA-II) has been presented to address the issue. The proposed algorithm adjusts the two parameters (MinPts and Eps) of the incremental DBSCAN via the iteration and the fitness functions to enhance the clustering precision. Moreover, our proposed method introduces suitable fitness functions for both labeled and unlabeled datasets. We have also improved the efficiency of the proposed hybrid algorithm by parallelization of the optimization process. The evaluation of the introduced method has been done through some textual and numerical datasets with different shapes, sizes, and dimensions. According to the experimental results, the proposed algorithm provides better results than Multi-Objective Particle Swarm Optimization (MOPSO) based incremental DBSCAN and a few well-known techniques, particularly regarding the shape and balanced datasets. Also, good speed-up can be reached with a parallel model compared with the serial version of the algorithm.

FPGA implementations of Grain v1, Mickey 2.0, Trivium, Lizard and Plantlet

In this paper, three eSTREAM Portfolio 2 ciphers: Grain v1, Mickey 2.0 and Trivium, and two Grain-like stream ciphers: Lizard and Plantlet are implemented in three versions aimed at different hardware application purposes. The hardware platform adopts Xilinx’s Spartan7 serial, and the simulations, syntheses and implementations are conducted in Vivado using the Verilog hardware design language. These implementations are compared with each other and those presented in existing literature in terms of performance metrics including: throughput, area consumption and throughput-area ratio. The basic version of Trivium achieves the highest frequency reaching a maximum of 416 Mbps and the serial version consumes the smallest area of 13 slices. In the parallel version, the maximum throughput-area ratio is 165.5 Mbps/Slice achieved by Trivium. At the same time, the basic version of the Mickey 2.0 algorithm achieved the second highest frequency of 384 Mbps, and the serial version of the Grain v1 algorithm achieved the second smallest area with 26 slices.

Application of Graphics Processing Units for Self-Consistent Modelling of Shallow Water Dynamics and Sediment Transport

In this paper, we describe a numerical algorithm for the self-consistent simulations of surface water and sediment dynamics. The method is based on the original Lagrangian-Eulerian CSPH-TVD approach for solving the Saint-Venant and Exner equations, taking into account the physical factors essential for the understanding of the shallow water and surface soil layer motions, including complex terrain structure and its evolution due to sediment transport. Additional Exner equation for sediment transport has been used for the numerical CSPH-TVD scheme stability criteria definition. By using OpenMP-CUDA and GPUDirect technologies for hybrid computing systems (supercomputers) with several graphic coprocessors (GPUs) interacting with each other via the PCI-E / NVLINK interface we also develop a parallel numerical algorithm for the CSPH-TVD method. The developed parallel version of the algorithm demonstrates high efficiency for various configurations of Nvidia Tesla CPU + GPU computing systems. In particular, maximal speed up is 1800 for a system with four C2070 GPUs compare to the serial version for the CPU. The calculation time on the GPU V100~(Volta architecture) is reduced by 95 times compared to the GPU C2070~(Fermi architecture).

Fast, good, and repeatable: Summations, vectorization, and reproducibility

Enhanced-precision global sums are key to reproducibility in exascale applications. We examine two classic summation algorithms and show that vectorized versions are fast, good and reproducible at exascale. Both 256-bit and 512-bit implementations speed up the operation by almost a factor of four over the serial version. They thus demonstrate improved performance on global summations while retaining the numerical reproducibility of these methods.

PSTGF: Time-independent R-matrix atomic electron-impact code

stgf is a community code employed for outer-region R-matrix calculations, describing electron-impact collisional processes. It is widely recognised that the original version of stgf was written by M.J. Seaton in 1983, but through constant refinement over the next decades by worldwide contributors has evolved into its current form that more reflects modern coding practice and current computer architectures. Despite its current wide acceptance, it was never formally published.Therefore, we present an updated high-performance parallel version of pstgf, that balances the requirements of small university clusters, yet can exploit the computational power of cutting edge supercomputers. There are many improvements over the original stgf, but most noticeably, the full introduction of MQDT options that provide subsequent integration with ICFT (Intermediate Coupling Frame Transformation) codes, and for either Breit–Pauli/DARC (Dirac Atomic R-matrix Codes), better load balancing, high levels of vectorisation and simplified output. Semantically, the program is full Fortran 90 in conjunction with MPI (Message Passing Interface) though has CUDA Fortran options for the most numerically intensive code sections. Program summaryProgram Title: RMATRX-PSTGFCPC Library link to program files:http://dx.doi.org/10.17632/3j55fmr86g.1Licensing provisions: GNU Lesser General Public License v2.1Programming language: Fortran 90Nature of problem: The R-matrix outer region code, pstgf directly calculates various electron-impact driven processes such as excitation and ionisation, or provides K-matrices for input for subsequent ICFT, differential or magnetic sub-level codes. As the problem size increases, there is an associated increase in the input/output, the numerical computation and unbalanced workload, especially for electron-impact energies where the number of open-channels is of a similar size to the number of closed. The code has been significantly modified to address these issues.pstgf interfaces the R-matrix inner region with the outer region, with the R-matrix acting as intermediary between the two regions. The outer region expresses an electron moving in the multi-pole expansion of the target and predominantly employs Coulomb functions, perturbed or otherwise to achieve this. This is a computationally expensive task, as the R-matrix must be formed for every energy point of every partial wave.Solution method: An approach that permutes both the partial wave and energy of the incident electron has been implemented. In this version, each processor does not calculate the same incident energy point for each partial wave, but rather distributes all energy points across all processors. This achieves better load-balancing of the work between cores and avoids the case where an overloaded single processor has to always calculate in the energy range where there are approximately the same number of half-open or half-closed channels, which is numerically intensive.Additional comments including restrictions and unusual features: Dimension parameters used to define arrays and matrices within pstgf (PARAM file) have been removed, all array dimensions are dynamically allocatable based upon the H.DAT file and set to the exact dimension. A CUDA subroutine for matrix multiplications using GPUs has been included, it can be activated or deactivated commenting this module in the source. Users of serial version stgf or older parallel versions of pstgf can move to current version without any modification in the input files.[1] M.J. Seaton, Coulomb functions for attractive and repulsive potentials and for positive and negative energies, Comp. Phys. Comm. 146 (2) (2002) 225–249. doi:https://doi.org/10.1016/S0010-4655(02)00275-8.[2] M.J. Seaton, Quantum defect theory, Rep. Prog. Phys. 46 (2) (1983) 167.doi:https://doi.org/10.1088/0034-4885/46/2/002.

Accelerated molecular dynamics simulation of Silicon Crystals on TaihuLight using OpenACC

The Sunway TaihuLight with the theoretical peak performance of 125PFlop/s is now ranked third in the TOP500 list. It provides a high-level programming model named OpenACC, which extends the OpenACC 2.0 standard with some customized extensions. We assess the performance of the extended programming model and the SW26010 heterogeneous many-core processor for running molecular dynamics (MD) simulation of solid covalent crystals using many-body potentials, such as the Tersoff potentials. Considering the special architecture of the SW26010 processor, we implement the porting of the MD simulation of silicon crystals using the Sunway OpenACC under the guidance of the extended Amdahl’s law. Since the Sunway OpenACC compiler cannot deal with the performance bottleneck of the MD simulation of silicon crystals, we implement two primary optimizations including designing the software cache and minimizing the access frequency of the main memory on an intermediate version of the code generated by the compiler. Experimental results indicate that a single-process many-core speedup of 12.89x can be achieved by using manual optimization strategies. Compared with the execution time of the serial version on Intel (R) Xeon (R) CPU E5-2620 v4 processor, 8.7x speedup can be achieved.

Longitudinal Effects of Left Ventricular Assist Device Implantation on Global and Domain-Specific Cognitive Function.

Left ventricular assist devices (LVADs) are a common treatment of advanced heart failure, but cognitive dysfunction, which is common in heart failure, could limit the ability to perform postimplantation LVAD care. Implantation of an LVAD has been associated with improved cerebral perfusion and may improve cognitive function post implantation. The aim of this study was to quantify longitudinal change in cognitive function after LVAD implantation. A secondary analysis of data on 101 adults was completed to evaluate cognitive function before implantation and again at 1, 3, and 6 months post implantation of an LVAD. Latent growth curve modeling was conducted to characterize change over time. Serial versions of the Montreal Cognitive Assessment were used to measure overall (total) cognitive function and function in 6 cognitive domains. There was moderate, nonlinear improvement from preimplantation to 6 months post implantation in Montreal Cognitive Assessment total score (Hedges' g = 0.50) and in short-term memory (Hedges' g = 0.64). There also were small, nonlinear improvements in visuospatial ability, executive function, and attention from preimplantation to 6 months post implantation (Hedges' g = 0.20-0.28). The greatest improvements were observed in the first 3 months after implantation and were followed by smaller, sustained improvements or no additional significant change. Implantation of an LVAD is associated with significant, nonlinear improvement in short-term memory and global cognitive function, with the most significant improvements occurring in the first 3 months after implantation. Clinicians should anticipate improvements in cognitive function after LVAD implantation and modify postimplantation education to maximize effectiveness of LVAD self-care.

Comparative investigation of GPU-accelerated triangle-triangle intersection algorithms for collision detection

Efficient collision detection is critical in 3D geometric modeling. In this paper, we first implement three parallel triangle-triangle intersection algorithms on a GPU and then compare the computational efficiency of these three GPU-accelerated parallel triangle-triangle intersection algorithms in an application that detects collisions between triangulated models. The presented GPU-based parallel collision detection method for triangulated models has two stages: first, we propose a straightforward and efficient parallel approach to reduce the number of potentially intersecting triangle pairs based on AABBs, and second, we conduct intersection tests with the remaining triangle pairs in parallel based on three triangle-triangle intersection algorithms, i.e., the Moller’s algorithm, Devillers’ and Guigue’s algorithm, and Shen’s algorithm. To evaluate the performance of the presented GPU-based parallel collision detection method for triangulated models, we conduct four groups of benchmarks. The experimental results show the following: (1) the time required to detect collisions for the triangulated model consisting of approximately 1.5 billion triangle pairs is less than 0.5 s; (2) the GPU-based parallel collision detection method speedup over the corresponding serial version is 50x - 60x, and (3) Devillers’ and Guigue’s algorithm is comparatively and comprehensively the best of the three GPU-based parallel triangle-triangle intersection algorithms. The presented GPU-accelerated method is capable of efficiently detecting the potential collisions of triangulated models. Overall, the GPU-accelerated parallel Devillers’ and Guigue’s triangle-triangle intersection algorithm is recommended when performing practical collision detections between large triangulated models.

Investigating the efficiency of multithreading application programming interfaces for parallel packet classification in wireless sensor networks

This paper investigates the most appropriate application programming interface API that best accelerates the flow-based applications on the wireless sensor networks WSNs . Each WSN include many sensor nodes which have limited resources. These sensor nodes are connected together using base stations. The base stations are commonly network systems with conventional processors which are responsible for handling a large amount of communicated data in flows of network packets. For this purpose, classification of the communicated packets is considered the primary process in such systems. With the advent of high-performance multicore processors, developers in the network industry have considered these processors as a striking choice for implementing a wide range of flow-based wireless sensor networking applications. The main challenge in this field is choosing and exploiting an API which best allows multithreading; i.e. one which maximally hides the latency of performing complex operations by threads and increases the overall efficiency of the cores. This paper assesses the efficiency of Thread, Open Multiprocessing, and Threading Building Blocks TBB libraries in multithread implementation of set-pruning and grid-of-tries packet classification algorithms on dual-core and quad-core processors. In all cases, the speed and throughput of all parallel versions of the classification algorithms are much more than the corresponding serial versions. Moreover, for parallel classification of a sufficiently large number of packets by both classification algorithms, TBB library results in higher throughput and performance than the other libraries due to its automatic scheduling and internal task stealing mechanism.

РАСПАРАЛЛЕЛИВАНИЕ РАСЧЁТНОГО КОДА ODETTA ДЛЯ РЕШЕНИЯ ЗАДАЧ ПЕРЕНОСА НЕЙТРОНОВ И ГАММА-КВАНТОВ

The ODETTA calculation code and a comparative analysis of the program simulation with using of MPI principles as well as the possibility of applying MPI technology to speed up the calculation code are considered. The development of the ODETTA program algorithmic part with MPI using is described. Features and specifics of this program parallelizing are presented. The modification of the calculation code is given. The corresponding software algorithms are considered. The structure of ODETTA program modules with MPI using is displayed. The results of ODETTA serial and parallel versions in OS Linux with MPI using on the HPC cluster of National Research Nuclear University MEPhI are presented. In addition, the comparative analysis of two program implementations in terms of speed and accuracy of results by using of two different clusters and a different number of nodes on them is given.

A Parallel Grid Optimization of SVM Hyperparameter for Big Data Classification using Spark Radoop

The big data phenomenon is currently a challenge to the process of relevant knowledge extraction using classical machine learning technique. This is due to the need for efficient data reduction and new fast-distributed machine learning algorithms for such process on big data. The extensive application of SVM demands efficient methods of constructing the classifier to be suitable for big data and high classification capability. In reality, the efficiency of SVM relies on the efficient derivation of the optimal feature subset and the algorithmic parameters. The grid search optimization method usually presents global optima and high learning accuracy compared to PSO and GA, but its larger computation takes much time. The grid search is more attractive because it can simultaneously take part in the learning of every SVM since they do not rely on each other. A novel parallel implementation of grid optimization using Spark Radoop is proposed in this paper to minimize the great computation load and make it suitable for big data processing issues. A major contribution of this study is a significant reduction in the algorithmic computational time when compared to the serial version of gridSVM, as well as the high classification accuracy compared to the other parallel optimization techniques.

JuSFEM: A Julia-based open-source package of parallel Smoothed Finite Element Method (S-FEM) for elastic problems

The Smoothed Finite Element Method (S-FEM) proposed by Liu G.R. can achieve more accurate results than the conventional FEM. Currently, much commercial software and many open-source packages have been developed to analyze various science and engineering problems using the FEM. However, there is little work focusing on designing and developing software or packages for the S-FEM. In this paper, we design and implement an open-source package of the parallel S-FEM for elastic problems by utilizing the Julia language on multi-core CPU. The Julia language is a fast, easy-to-use, and open-source programming language that was originally designed for high-performance computing. We term our package as juSFEM. To the best of the authors’ knowledge, juSFEM is the first package of parallel S-FEM developed with the Julia language. To verify the correctness and evaluate the efficiency of juSFEM, two groups of benchmark tests are conducted. The benchmark results show that (1) juSFEM can achieve accurate results when compared to commercial FEM software ABAQUS, and (2) juSFEM only requires 543 s to calculate the displacements of a 3D elastic cantilever beam model which is composed of approximately 2 million tetrahedral elements, while in contrast the commercial FEM software needs 930 s for the same calculation model; (3) the parallel juSFEM executed on the 24-core CPU is approximately 20× faster than the corresponding serial version. Moreover, the structure and function of juSFEM are easily modularized, and the code in juSFEM is clear and readable, which is convenient for further development.

Impaired Fixation-Related Theta Modulation Predicts Reduced Visual Span and Guided Search Deficits in Schizophrenia.

During normal visual behavior, individuals scan the environment through a series of saccades and fixations. At each fixation, the phase of ongoing rhythmic neural oscillations is reset, thereby increasing efficiency of subsequent visual processing. This phase-reset is reflected in the generation of a fixation-related potential (FRP). Here, we evaluate the integrity of theta phase-reset/FRP generation and Guided Visual Search task in schizophrenia. Subjects performed serial and parallel versions of the task. An initial study (15 healthy controls (HC)/15 schizophrenia patients (SCZ)) investigated behavioral performance parametrically across stimulus features and set-sizes. A subsequent study (25-HC/25-SCZ) evaluated integrity of search-related FRP generation relative to search performance and evaluated visual span size as an index of parafoveal processing. Search times were significantly increased for patients versus controls across all conditions. Furthermore, significantly, deficits were observed for fixation-related theta phase-reset across conditions, that fully predicted impaired reduced visual span and search performance and correlated with impaired visual components of neurocognitive processing. By contrast, overall search strategy was similar between groups. Deficits in theta phase-reset mechanisms are increasingly documented across sensory modalities in schizophrenia. Here, we demonstrate that deficits in fixation-related theta phase-reset during naturalistic visual processing underlie impaired efficiency of early visual function in schizophrenia.