In the conditions of industrial production many processes of polymerisation are nonstationary. By processes optimization with the regard for such features as basic data it is necessary to use adaptive algorithms of id...
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In the conditions of industrial production many processes of polymerisation are nonstationary. By processes optimization with the regard for such features as basic data it is necessary to use adaptive algorithms of identification, allowing mathematical model of process continuously to be adapted for changing conditions of operation. Use of such algorithms for process optimization demands periodic recalculation of optimum technological modes of process. Polymer reaction engineering is a discipline that deals with various problems concerning the fundamental nature of chemical and physical phenomena in polymerization processes. Mathematical modeling is a powerful tool for the development of process understanding and advanced reactor technology in the polymer industry.
This paper demonstrates model-based dynamic optimization through the coupling of two open source tools: OpenModelica, which is a Modelica-based modeling and simulation platform, and CasADi, a framework for numerical o...
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ISBN:
(纸本)9783902823434
This paper demonstrates model-based dynamic optimization through the coupling of two open source tools: OpenModelica, which is a Modelica-based modeling and simulation platform, and CasADi, a framework for numerical optimization. The coupling uses a standardized XML format for exchange of differential-algebraic equations (DAE) models. OpenModelica supports export of models written in Modelica and the optimization language extension using this XML format, while CasADi supports import of models represented in this format. This allows users to define optimal control problems (OCP) using Modelica and optimization language specification, and solve the underlying model formulation using a range of optimization methods, including direct collocation and direct multiple shooting. The proposed solution has been tested on several industrially relevant optimal control problems, including a dieselelectric power train.
GPGPUs are increasingly being used to as performance accelerators for HPC (High Performance Computing) applications in CPU/GPU heterogeneous computing systems, including TianHe-1A, the world's fastest supercomputer...
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GPGPUs are increasingly being used to as performance accelerators for HPC (High Performance Computing) applications in CPU/GPU heterogeneous computing systems, including TianHe-1A, the world's fastest supercomputer in the TOP500 list, built at NUDT (National University of Defense Technology) last year. However, despite their performance advantages, GPGPUs do not provide built-in fault-tolerant mechanisms to offer reliability guarantees required by many HPC applications. By analyzing the SIMT (single-instruction, multiple-thread) characteristics of programs running on GPGPUs, we have developed PartialRC, a new checkpoint-based compiler-directed partial recomputing method, for achieving efficient fault recovery by leveraging the phenomenal computing power of GPGPUs. In this paper, we introduce our PartialRC method that recovers from errors detected in a code region by partially re-computing the region, describe a checkpoint-based faulttolerance framework developed on PartialRC, and discuss an implementation on the CUDA platform. Validation using a range of representative CUDA programs on NVIDIA GPGPUs against FullRC (a traditional full-recomputing Checkpoint-Rollback-Restart fault recovery method for CPUs) shows that PartialRC reduces significantly the fault recovery overheads incurred by FullRC, by 73.5% when errors occur earlier during execution and 74.6% when errors occur later on average. In addition, PartialRC also reduces error detection overheads incurred by FullRC during fault recovery while incurring negligible performance overheads when no fault happens.
We introduce a static detector, Saber, for detecting memory leaks in C programs. Leveraging recent advances on sparse pointer analysis, Saber is the first to use a full-sparse value-flow analysis for leak detection. S...
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This paper demonstrates model-based dynamic optimization through the coupling of two open source tools: OpenModelica, which is a Modelica-based modeling and simulation platform, and CasADi, a framework for numerical o...
详细信息
This paper demonstrates model-based dynamic optimization through the coupling of two open source tools: OpenModelica, which is a Modelica-based modeling and simulation platform, and CasADi, a framework for numerical optimization. The coupling uses a standardized XML format for exchange of differential-algebraic equations (DAE) models. OpenModelica supports export of models written in Modelica and the optimization language extension using this XML format, while CasADi supports import of models represented in this format. This allows users to define optimal control problems (OCP) using Modelica and optimization language specification, and solve the underlying model formulation using a range of optimization methods, including direct collocation and direct multiple shooting. The proposed solution has been tested on several industrially relevant optimal control problems, including a diesel-electric power train.
The multilevel inverters (MLIs) are classified into three topologies such as Diode Clamped, Flying Capacitor and Cascade Multilevel Inverter (CMLI). CMLI topologies include two kind of structure that is named symmetri...
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ISBN:
(纸本)9781467363914
The multilevel inverters (MLIs) are classified into three topologies such as Diode Clamped, Flying Capacitor and Cascade Multilevel Inverter (CMLI). CMLI topologies include two kind of structure that is named symmetric and asymmetric topologies. Asymmetric Cascade MLI (ACMLI) topologies consist of unequal DC sources. Many modulation techniques have been used in ACMLI topology such as Multi-Carrier PWM (MC-PWM), Space Vector PWM and Selective Harmonic PWM. The MC-PWM technique is achieved by four different types. In this study, MC-PWM techniques which are named Phase Disposition PWM, Phase Opposition Disposition PWM, Alternate Phase Opposition Disposition PWM and Phase Shifted PWM have been compared. It is uncovered that Phase Opposition Disposition PWM technique is more convenient in terms of Total Harmonic Distortion of output voltage and current signals and in terms of the quality of power factor in ACMLI which is performed in this study.
Let there be given a safety related electronic system suffering from random failures or errors. The standard IEC 61508 contains simplified equations for the probability of failure on demand PFDavg for special system a...
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ISBN:
(纸本)9781622764365
Let there be given a safety related electronic system suffering from random failures or errors. The standard IEC 61508 contains simplified equations for the probability of failure on demand PFDavg for special system architectures, mostly without proof. In various publications PFDavg is defined by several different equations, e.g. as a Laplacian probability, as an integral mean, or by means of the average failure rate of the system. The aim of the paper is to determine PFDavgby stochastic methods and to bring together the different definitions. A formula for PFDavg is given that is valid for most universal electronic systems. The equivalence of 2 different definitions of PFDavgis shown. The special case of a koon-System is investigated, and the resulting equations improve those known so far. The basic idea is to randomize the time to failure, the down time of the system, as well as the repair time, and then, by means of the Stieltjes-Integral, determine the mean or average time as the expectation of the respective random variable.
Software composed of artifacts written in multiple (programming) languages is pervasive in today's enterprise, desktop, and mobile applications. Since they form one system, artifacts from different languages refer...
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In this paper, we present a hybrid circular queue method that can significantly boost the performance of stencil computations on GPU by carefully balancing usage of registers and shared-memory. Unlike earlier methods ...
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In this paper, we present a hybrid circular queue method that can significantly boost the performance of stencil computations on GPU by carefully balancing usage of registers and shared-memory. Unlike earlier methods that rely on circular queues predominantly implemented using indirectly addressable shared memory, our hybrid method exploits a new reuse pattern spanning across the multiple time steps in stencil computations so that circular queues can be implemented by both shared memory and registers effectively in a balanced manner. We describe a framework that automatically finds the best placement of data in registers and shared memory in order to maximize the performance of stencil computations. Validation using four different types of stencils on three different GPU platforms shows that our hybrid method achieves speedups up to 2.93X over methods that use circular queues implemented with shared-memory only.
In this paper, we propose SnuCL, an OpenCL framework for heterogeneous CPU/GPU clusters. We show that the original OpenCL semantics naturally fits to the heterogeneous cluster programming environment, and the framewor...
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ISBN:
(纸本)9781450313162
In this paper, we propose SnuCL, an OpenCL framework for heterogeneous CPU/GPU clusters. We show that the original OpenCL semantics naturally fits to the heterogeneous cluster programming environment, and the framework achieves high performance and ease of programming. The target cluster architecture consists of a designated, single host node and many compute nodes. They are connected by an interconnection network, such as Gigabit Ethernet and InfiniBand switches. Each compute node is equipped with multicore CPUs and multiple GPUs. A set of CPU cores or each GPU becomes an OpenCL compute device. The host node executes the host program in an OpenCL application. SnuCL provides a system image running a single operating system instance for heterogeneous CPU/GPU clusters to the user. It allows the application to utilize compute devices in a compute node as if they were in the host node. No communication API, such as the MPI library, is required in the application source. SnuCL also provides collective communication extensions to OpenCL to facilitate manipulating memory objects. With SnuCL, an OpenCL application becomes portable not only between heterogeneous devices in a single node, but also between compute devices in the cluster environment. We implement SnuCL and evaluate its performance using eleven OpenCL benchmark applications. Copyright 2012 ACM.
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