7 resultados para Symbolic Execution
em Martin Luther Universitat Halle Wittenberg, Germany
Resumo:
Magdeburg, Univ., Fak. für Naturwiss., Diss., 2014
Resumo:
Monitoring, object-orientation, real-time, execution-time, scheduling
Resumo:
Object-oriented simulation, mechatronic systems, non-iterative algorithm, electric components, piezo-actuator, symbolic computation, Maple, Sparse-Tableau, Library of components
Resumo:
An appropriate assessment of end-to-end network performance presumes highly efficient time tracking and measurement with precise time control of the stopping and resuming of program operation. In this paper, a novel approach to solving the problems of highly efficient and precise time measurements on PC-platforms and on ARM-architectures is proposed. A new unified High Performance Timer and a corresponding software library offer a unified interface to the known time counters and automatically identify the fastest and most reliable time source, available in the user space of a computing system. The research is focused on developing an approach of unified time acquisition from the PC hardware and accordingly substituting the common way of getting the time value through Linux system calls. The presented approach provides a much faster means of obtaining the time values with a nanosecond precision than by using conventional means. Moreover, it is capable of handling the sequential time value, precise sleep functions and process resuming. This ability means the reduction of wasting computer resources during the execution of a sleeping process from 100% (busy-wait) to 1-1.5%, whereas the benefits of very accurate process resuming times on long waits are maintained.
Resumo:
In this paper we investigate various algorithms for performing Fast Fourier Transformation (FFT)/Inverse Fast Fourier Transformation (IFFT), and proper techniques for maximizing the FFT/IFFT execution speed, such as pipelining or parallel processing, and use of memory structures with pre-computed values (look up tables -LUT) or other dedicated hardware components (usually multipliers). Furthermore, we discuss the optimal hardware architectures that best apply to various FFT/IFFT algorithms, along with their abilities to exploit parallel processing with minimal data dependences of the FFT/IFFT calculations. An interesting approach that is also considered in this paper is the application of the integrated processing-in-memory Intelligent RAM (IRAM) chip to high speed FFT/IFFT computing. The results of the assessment study emphasize that the execution speed of the FFT/IFFT algorithms is tightly connected to the capabilities of the FFT/IFFT hardware to support the provided parallelism of the given algorithm. Therefore, we suggest that the basic Discrete Fourier Transform (DFT)/Inverse Discrete Fourier Transform (IDFT) can also provide high performances, by utilizing a specialized FFT/IFFT hardware architecture that can exploit the provided parallelism of the DFT/IDF operations. The proposed improvements include simplified multiplications over symbols given in polar coordinate system, using sinе and cosine look up tables, and an approach for performing parallel addition of N input symbols.
Resumo:
In this paper we investigate various algorithms for performing Fast Fourier Transformation (FFT)/Inverse Fast Fourier Transformation (IFFT), and proper techniquesfor maximizing the FFT/IFFT execution speed, such as pipelining or parallel processing, and use of memory structures with pre-computed values (look up tables -LUT) or other dedicated hardware components (usually multipliers). Furthermore, we discuss the optimal hardware architectures that best apply to various FFT/IFFT algorithms, along with their abilities to exploit parallel processing with minimal data dependences of the FFT/IFFT calculations. An interesting approach that is also considered in this paper is the application of the integrated processing-in-memory Intelligent RAM (IRAM) chip to high speed FFT/IFFT computing. The results of the assessment study emphasize that the execution speed of the FFT/IFFT algorithms is tightly connected to the capabilities of the FFT/IFFT hardware to support the provided parallelism of the given algorithm. Therefore, we suggest that the basic Discrete Fourier Transform (DFT)/Inverse Discrete Fourier Transform (IDFT) can also provide high performances, by utilizing a specialized FFT/IFFT hardware architecture that can exploit the provided parallelism of the DFT/IDF operations. The proposed improvements include simplified multiplications over symbols given in polar coordinate system, using sinе and cosine look up tables,and an approach for performing parallel addition of N input symbols.
Resumo:
The modern computer systems that are in use nowadays are mostly processor-dominant, which means that their memory is treated as a slave element that has one major task – to serve execution units data requirements. This organization is based on the classical Von Neumann's computer model, proposed seven decades ago in the 1950ties. This model suffers from a substantial processor-memory bottleneck, because of the huge disparity between the processor and memory working speeds. In order to solve this problem, in this paper we propose a novel architecture and organization of processors and computers that attempts to provide stronger match between the processing and memory elements in the system. The proposed model utilizes a memory-centric architecture, wherein the execution hardware is added to the memory code blocks, allowing them to perform instructions scheduling and execution, management of data requests and responses, and direct communication with the data memory blocks without using registers. This organization allows concurrent execution of all threads, processes or program segments that fit in the memory at a given time. Therefore, in this paper we describe several possibilities for organizing the proposed memory-centric system with multiple data and logicmemory merged blocks, by utilizing a high-speed interconnection switching network.