In this paper, we implement the SIFT(Scale-Invariant Feature Transform) algorithm for feature point extraction using a many-core processor, and analyze the performance, area efficiency, and system area efficiency of the many-core processor. In addition, we demonstrate the potential of the proposed many-core processor by comparing the performance of the many-core processor with that of high-performance CPU and GPU(Graphics Processing Unit). Experimental results indicate that the accuracy result of the SIFT algorithm using the many-core processor was same as that of OpenCV. In addition, the many-core processor outperforms CPU and GPU in terms of execution time. Moreover, this paper proposed an optimal model of the SIFT algorithm on the many-core

The article describes the algorithm for seismic imaging data processing that enables detecting and evaluating geological anomalies based on the system of specific criteria. Employing the algorithm we can complete the process of profile record, amplitude and velocity spectra computation, filtering and imaging of T-X curves. Subsequently computation and statistical processing of kinematic and dynamic parameters are made in the selected velocity windows. The main procedures for the algorithm include tomographic recovery of wavefield parameters in the plane of extraction panel, detection and interpretation of anomalous zones based on the prediction criteria to determine type of the discontinuity. There is a good reason that tomography in the plane of extraction panel shall be made in velocity windows of the dedicated wavetrains step by step for the main informative parameters. Analysis of the velocity distribution for the amplitude module maximum provides high accuracy when it comes to detect anomalous zones. This parameter is marked by relative independence on chance factors. Analysis of typical wavetrain frequency shift is determining factor indicative not only of the discontinuity but also of its type. Recording of wavetrain amplitude distribution is characterized by high accuracy in terms of anomalous zone detection. However, recording is complicated by dependence on a host of chance factors. The other parameters have much lesser quality and can be used as auxiliary. The algorithm is implemented into software capable to computerize most time-consuming operations. Use of this algorithm is illustrated as a case study for the results of data analysis and interpretation for seismic exploration at 37К10-В longwall panel section in Kuzembaev Mine (Kazakhstan).

: In this paper, we implement and evaluate the performance of a vector-based rasterization algorithm for 3D graphics by using a SIMD (single instruction multiple data) many-core processor architecture. In addition, we evaluate the impact of a data-per-processing elements (DPE) ratio that is defined as the amount of data directly mapped to each processing element (PE) within many-core in terms of performance, energy efficiency, and area efficiency. For the experiment, we utilize seven different PE configurations by varying the DPE ratio (or the number PEs), which are implemented in the same 130 nm CMOS technology with a 500 MHz clock frequency. Experimental results indicate that the optimal PE configuration is achieved as the DPE ratio is in the range from 16,384 to 256 (or the number of PEs is in the range from 16 and 1,024), which meets the requirements of mobile devices in terms of the optimal performance and efficiency.