High-level synthesis optimization for blocked floating-point matrix multiplication

In the last decade floating-point matrix multiplication on FPGAs has been studied extensively and efficient architectures as well as detailed performance models have been developed. By design these IP cores take a fixed footprint which not necessarily optimizes the use of all available resources. Moreover, the low-level architectures are not easily amenable to a parameterized synthesis. In this paper high-level synthesis is used to fine-tune the configuration parameters in order to achieve the highest performance with maximal resource utilization. An\ exploration strategy is presented to optimize the use of critical resources (DSPs, memory) for any given FPGA. To account for the limited memory size on the FPGA, a block-oriented matrix multiplication is organized such that the block summation is done on the CPU while the block multiplication occurs on the logic fabric simultaneously. The communication overhead between the CPU and the FPGA is minimized by streaming the blocks in a Gray code ordering scheme which maximizes the data reuse for consecutive block matrix product calculations. Using high-level synthesis optimization, the programmable logic operates at 93% of the theoretical peak performance and the combined CPU-FPGA design achieves 76% of the available hardware processing speed for the floating-point multiplication of 2K by 2K matrices

Efficiency Evaluation Of Implementation Of Optimization Methods Of Operation Modes Of The "Plast - Gas Pipeline" System By The Methods Of Mathematical Modeling

To date, Ukraine's mature gas fields, which are being developed in the gas regime, are at the final stage of development, which is characterized by a significant depletion of reservoir energy. The final stage of development requires solving complex problems related to watering wells, destruction of the reservoir, removal of formation water and mechanical impurities, increasing back pressure in the system, as well as the moral and physical wear and tear of industrial equipment. In the conditions of falling gas production, a significant part of the operating well stock is unstable, in the mode of unauthorized stops due to the accumulation of liquid at the bottom and insufficient gas velocities for removal to the surface, and also the accumulation of the liquid phase in the lowered places of the gas gathering system.Within the framework of the conducted studies, the gas dynamic models of the operation of the gas collection system of 3 oil/gas-condensate fields (OGCF) are created. A single model of the gas production system "reservoir - well - gas gathering system - inter-field gas pipeline - main facilities" is built. The current efficiency of the gas production, collection and transportation system is assessed. On the basis of model calculations, the current production capabilities of the wells are defined, as well as the "narrow" places of the system.It is established that the introduction of modern technologies for the operation of watered wells without optimizing the operation of the entire gas production system is irrational, since the liquid that is carried out from the wellbore will accumulate in the plumes and increase the back pressure level in the ground part. In conditions of increasing gas sampling, liquid flowlines can be taken out of the loops and deactivated the separation equipment.The feasibility of introducing methods for optimizing the operation modes of the gas production - gathering and transportation system is estimated, which allows choosing the optimal method for increasing the efficiency and reliability of its operation.For the first time in the Ukrainian gas industry, an integrated model of the field is created as a single chain of extraction, collection, preparation and transportation of natural gas, which can be adapted for the development and arrangement of both new and mature deposits.The main advantage of the application for the hydrocarbon production sector is the simulation of the processes, which makes it possible to evaluate the operating mode of the well in the safe zone while reducing the working pressure and introducing various intensification methods, and also to estimate the increase in hydrocarbon production. For the equipment of the ground infrastructure – "midstream" – the main advantage is a reduction in the time required to perform design calculations for gas pipelines, trains and pipelines for transporting multiphase media using public models.The creation and use of integrated models of gas fields gives an understanding of the integral picture of available resources and ensures an increase in the efficiency of field development management.The results of the calculation are clearly correlated with the actual data, which makes it possible to use the models constructed to obtain numerical results

Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation

Rapid Serial Visual Presentation (RSVP) is a paradigm that supports the application of cortically coupled computer vision to rapid image search. In RSVP, images are presented to participants in a rapid serial sequence which can evoke Event-related Potentials (ERPs) detectable in their Electroencephalogram (EEG). The contemporary approach to this problem involves supervised spatial filtering techniques which are applied for the purposes of enhancing the discriminative information in the EEG data. In this paper we make two primary contributions to that field: 1) We propose a novel spatial filtering method which we call the Multiple Time Window LDA Beamformer (MTWLB) method; 2) we provide a comprehensive comparison of nine spatial filtering pipelines using three spatial filtering schemes namely, MTWLB, xDAWN, Common Spatial Pattern (CSP) and three linear classification methods Linear Discriminant Analysis (LDA), Bayesian Linear Regression (BLR) and Logistic Regression (LR). Three pipelines without spatial filtering are used as baseline comparison. The Area Under Curve (AUC) is used as an evaluation metric in this paper. The results reveal that MTWLB and xDAWN spatial filtering techniques enhance the classification performance of the pipeline but CSP does not. The results also support the conclusion that LR can be effective for RSVP based BCI if discriminative features are available