Engineering topics

Su, Chun-Yi

Publications and source records attributed to Su, Chun-Yi.

5 records

DOE OSTI2020

A signal compensation based cascaded PI control for an industrial heat exchange system

Since the characteristics of the industrial heat exchange system (HES) are drastically affected by variations of the steam pressure, ambient temperature and water quality, it is difficult for the classical cascade PI control system to meet the desirable control objectives. Therefore, in this paper, a deterministic linear model with unmodeled dynamics is used to describe the dynamic characteristics of the HES. It should be noted that the unmodeled dynamics at the previously sampled instant can be calculated using actual measurements and that the tracking error, which includes effects of the rate of changes of unmodeled dynamics on the controlled model, can be accurately determined. An additional compensating signal is obtained with the feedforward control together with a one-step optimal control law. Consequently, the cascade PI control strategy with the signal compensation is established. Furthermore, the simulation and industrial application show that the proposed method can effectively improve the performance of the cascade PI control system, especially when the unmodeled dynamics is subjected to unknown variations.

42 ENGINEERING↗

DOE OSTI2017

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperature are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.

Adaptive signal approacg↗

DOE OSTI2014

Energy-aware Thread and Data Management in Heterogeneous Multi-core, Multi-memory Systems

By 2004, microprocessor design focused on multicore scaling—increasing the number of cores per die in each generation—as the primary strategy for improving performance. These multicore processors typically equip multiple memory subsystems to improve data throughput. In addition, these systems employ heterogeneous processors such as GPUs and heterogeneous memories like non-volatile memory to improve performance, capacity, and energy efficiency. With the increasing volume of hardware resources and system complexity caused by heterogeneity, future systems will require intelligent ways to manage hardware resources. Early research to improve performance and energy efficiency on heterogeneous, multi-core, multi-memory systems focused on tuning a single primitive or at best a few primitives in the systems. The key limitation of past efforts is their lack of a holistic approach to resource management that balances the tradeoff between performance and energy consumption. In addition, the shift from simple, homogeneous systems to these heterogeneous, multicore, multi-memory systems requires in-depth understanding of efficient resource management for scalable execution, including new models that capture the interchange between performance and energy, smarter resource management strategies, and novel low-level performance/energy tuning primitives and runtime systems. Tuning an application to control available resources efficiently has become a daunting challenge; managing resources in automation is still a dark art since the tradeoffs among programming, energy, and performance remain insufficiently understood. In this dissertation, I have developed theories, models, and resource management techniques to enable energy-efficient execution of parallel applications through thread and data management in these heterogeneous multi-core, multi-memory systems. I study the effect of dynamic concurrent throttling on the performance and energy of multi-core, non-uniform memory access (NUMA) systems. I use critical path analysis to quantify memory contention in the NUMA memory system and determine thread mappings. In addition, I implement a runtime system that combines concurrent throttling and a novel thread mapping algorithm to manage thread resources and improve energy efficient execution in multi-core, NUMA systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

The Power-Performance Tradeoffs of the Intel Xeon Phi on HPC Applications

Accelerators are used in about 13% of the current Top500 List. Supercomputers leveraging accelerators grew by a factor of 2.2x in 2012 and are expected to completely dominate the Top500 by 2015. Though most of these deployments use NVIDIA GPGPU accelerators, Intel’s Xeon Phi architecture will likely grow in popularity in the coming years. Unfortunately, there are few studies analyzing the performance and energy efficiency of systems leveraging the Intel Xeon Phi. We extend our systemic measurement methodology to isolate system power by component including accelerators. We use this methodology to present a detailed study of the performance-energy tradeoffs of the Xeon Phi architecture.

Li, Bo↗

DOE OSTI2012

MODA A Framework for Memory Centric Performance Characterization

In the age of massive parallelism, the focus of performance analysis has switched from the processor and related structures to the memory and I/O resources. Adapting to this new reality, a performance analysis tool has to provide a way to analyze resource usage to pinpoint existing and potential problems in a given application. This paper provides an overview of the Memory Observant Data Analysis (MODA) tool, a memory-centric tool first implemented on the Cray XMT supercomputer. Throughout the paper, MODA's capabilities have been showcased with experiments done on matrix multiply and Graph-500 application codes.

Shrestha, Sunil↗