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________________ CHU DUC TOAN STUDY ADAPTIVE CONTROL ALGORITHMS WITH REFERENCE FLOWS TO IMPROVE THE SPEED OF SPECISLIZED PARALLEL PROCESSING SYSTEMS Major: Control Engineering and Aut

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CHU DUC TOAN

STUDY ADAPTIVE CONTROL ALGORITHMS WITH REFERENCE FLOWS TO IMPROVE THE SPEED OF SPECISLIZED PARALLEL PROCESSING SYSTEMS

Major: Control Engineering and Automation

Code: 62.52.02.16

SUMMARY OF ENGINEERING THESIS

THAI NGUYEN - 2013

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Ass Prof Dr Nguyen Huu Cong

At hour, ….date month year

This thesis can be found in the library: Library of Industrial Engineering University - Thai Nguyen University; Learning materials Center of Thai Nguyen University, National Library of Vietnam

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SUMMARY OF THESIS

1 The necessary of the topic

Many new areas such as computer graphics, artificial intelligence, number analysis, parallel calculating in the petroleum industry, the unmanned equipment, equipment of identifying monitoring mobile targets , require to process very large volumes

of data with high speed Most of this problem, the sequential computer does not meet the actual requirements Research on parallel processing systems now focus two main researching directions are as follows:

The one is to study multi-processor systems as supercomputers (Suppercomputer) [45], [54], large computer (Mainframe), minicomputer (minicomputer) make versatile: the hardware structure and software function of the computer that must be multi-functional organized are complex Mathematical model is very complex, beyond ordinary calculating structure Therefore, when applied to specialized applications, their processing speed is often slower than the ability of the micro processing; real-time parameter is not controlled correctly Parallel multi-processing system has a big scale together with operating structural software is very complicated Therefore, the computer system has a very expensive price This is a difficult problem to solve specific problems required high speed, low cost consistent with economic conditions in Vietnam

The second is to study parallel multi-CPU processing system such as: parallel-specialized processing system for one or one class of specific math, the same function Therefore, manipulation methods,

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structure of data group need to be processed; the structure of resulting data are defined before, so it is more easy to decompose functions , easy to select data organization and appropriate processing methods with speed requirements With specific tasks and defined data structures, the optimal processing algorithm can be made, appropriate hardware structure, utilizing system resources reasonably Due to the function of parallel specialized processing systems is limited and explicit, the Monitor program is built in the most optimal, highly scalable and more importantly is to response fast requirements of operational processes in the system

Through the above analysis, the thesis selects the second direction that is parallel-specialized multi-CPU processing system In parallel specialized multi-CPU processing system, shared storage space (SSS) is very important: the storage of the database to be processed, the operating program When many reference flows accessed to shared memory at the same time that can lead to conflict, then the system may hang or low access speed, the performance of shared memory is reduced and does not meet the speed requirements

of this problem The importance of SSS is the control set of reference flow On that basis, the problem to be solved is to synthetic the structure of adaptive controlling of reference flow to SSS to minimize the probability of conflicts when accessing shared resources, improving computing speed is very important From the above analysis, the research poses the problem for parallel- specialized multi-CPU processing system met the fast and reliable processing speed, reasonable price is very necessary and as a basis to

form thesis’s topic: "Study adaptive control algorithms with

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reference flows to improve the speed of specialized parallel processing systems”

2 Object and scope of research

- Object of the thesis is SSS in parallel-specialized multi-CPU

processing system

- The researching scope of the thesis is the limitation in making the mathematical model in reference flow to SSS in parallel-specialized multi-CPU processing system; specify the binding conditions between these parameters and the changeable parameters to synthesize optimal controlling system (adaptation) in reference flow

to SSS to improve the efficiency and reduce the probability of conflicts when accessing shared resources

3 The researching method of the thesis

- Based on the classic theory as a queuing theory, probability theory namely Morkov process stops, distributes Poat-xông to build and calculate the performance for reference mathematical model to SSS

in parallel Multi-CPU processing system

- Describe mathematically model of shared memory in the parallel multi-CPU processing system

- Study to control the system by using emulation and practical technology that is FPGA modern technology

4 The scientific meaning and practice of the thesis

4.1 In the science

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The scientific meaning is to study and apply the optimal controller (adaption) in reference flow to SSS for parallel-specialized multi-CPU processing system to improve the performance, the speed, and minimize the probability of conflict when accessing shared resources

4.2 In the practice

The research result will be references for students and graduate students as well as researchers interested in research on multi-CPU parallel processing dedicated From the results of this research, topic

as the basis for many further studies aimed to apply widely the parallel-specialized multi-CPU processing system in the practice in Vietnam, especially the system has high requirement for speed

5 The structure of thesis

The thesis consists of three chapters namely explanation, conclusion and references

Chapter 1 Architecture of parallel multi-CPU processing

system

1.1 System Resources

1.1.1 Hardware Resources

1.1.2 Software Resources

1.2 The definition of parallel processing system

1.3 Classification of parallel processing system

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- Michel J.Flynn gave 4 architecture models of parallel processing system are: (i) SISD model, (ii) SIMD model, (iii) MISD model, (iv) MIMD model

- Handler classifies parallel processing system based on parallel level and processing level according to the pipeline mechanism of the hardware structure

1.4 Overall architecture of parallel multi-CPU processing system

1.4.1 Model

1.4.2 The issues related to performance

1.5 The architecture of parallel- specialized multi-CPU processing system

1.5.1 The characteristics of parallel- specialized multi-CPU

processing system

a Specialized function

Specialized function is also reflected in the data structure that the system must process This data structure is largely the vector data due to the similar structure of elements and they are arranged in the order (such as the structure: range-azimuth-height) that allows to vector easily the basis of this data The consequence is to perform data processing operations as the pipeline mechanism easily - a mechanism to improve the performance of processing system

b The structure of minimal hardware

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Due to parallel- specialized processing system performs a defined task and this task is established only in a math class so structural parameters must be determined quite accurately As a result, the hardware organization will ensure minimal with standard partitioning algorithm

c The high speed and performance

d The high reliability

This is a requirement, as well as a characteristic of the specialized processing system At first view, it seems to conflict to the requirement of high speed’s system However, unlike general-purpose computers, parallel-specialized processing system is largely the system which is difficult to maintenance, even impossible to maintenance (such as processing systems mounted on satellites, on the self-led missile, or in the early warning system under the sea )

parallel-so it must require high reliability

1.5.2 The architecture of parallel- specialized multi-CPU

processing system

a Model of parallel- specialized multi-CPU processing system

b These factors affect the performance of parallel- specialized multi-CPU processing system

c Branch instruction

1.6 Commentary, research-oriented of the topic

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Through the analysis and introduction about parallel multi-CPU processing system and parallel- specialized multi-CPU processing system in section (1.4) and (1.5)

With parallel - specialized multi-CPU processing system, the performance largely depends on the accessing speed into common resources, but the most importance is SSS because the highest possibility of conflict is here (because the frequency of using SSS is much higher than other resources such as I/O port, peripherals .) One of the tasks of the synthesis stage of the system is to minimize the possibility of conflict in reference to SSS of CPU unit that is a critical task For example, the monitoring system of aircrafts The aircrafts are such as: (i) at different distances (ii) the speed is also very different The parameters must be monitored for an aircraft: (i) distance (ii) azimuth and (iii) height, when the parameters are controlled, we are able to draw the flying orbits Then we can make other decisions (to kill, not to kill )

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- The situation of researching in the country: The researching of

"Solving level 1 problem for Radar intelligence information” scientific research at the level of Department of Defense, Dr Nguyen Van Lien (2008-2012)

Figure 1.14: Observation distance of

the system

Outermost range doughnut N1024

t

t

Range doughnut N1023

Range doughnut N1

Surge generator

375 Hz

Pulse reflection from the target on theother ranges other range

The cycle of pulse

U

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In which, this topic shows clearly that it must solve at the same time all the parameters such as, range, azimuth and height for 1024 range donuts However, the topic did not mention to SSS

- The situation of researching in the foreigner: The typical studies of

three authors from 2000 to now continue studying of parallel processing system The study was published in 2000 [5], Baghdadi A., Zergainoh N E in 2004 [13], Chou Y., Fahs B., AND Abraham

S, also in 2004 with the work of the author: Ken Mai, Ron Ho, Elad Alon, Dean Liu, Dinesh Patil, Mark Horowitz [39] However, these topics are applied for large multi-CPU system, supercomputers Therefore, these topics study un- limited number of CPU, maybe up

to thousands of CPU So many tight binding parameters are not specified, large survey graph drawing gets difficulties In term of the parallel- specialized multi-CPU processing system, the number of CPU is not too much, functional disintegrate is very good

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adaptive controlling of reference flow to SSS to minimize the probability of conflicts when accessing shared resources

On the basis of preliminary studies of parallel-specialized CPU processing system, in Chapter 2 the thesis will study farther, analysis, make mathematical model refer to SSS

multi-Chapter 2 Making mathematical models refer to common memory in parallel multi-CPU processing system

2.1 Theoretical Basic

To build the mathematical model for optimal controlling mechanism of reference flow in parallel-specialized multi-CPU processing system based on the requirements of the functional processing system described in chapter 1 that was done with SSS, the thesis need to use:

- Queuing theory is used to describe the n reference flow to SSS with queuing mechanism at the entrance / exit

- Probability theory, namely the Markov process is used to uniform referring mechanism of n reference flows to SSS with synchronization mechanism in the operation of the parallel- specialized multi-CPU processing system That means the state of the system established after clocking the system Moreover, there used stopping Markov process only to confirm that the future state of the system depends only on the current state of the system (which does not depend on the previous states)

- Use the distribution of the reference to SSS of the specialized multi-CPU processing system that is Poat-xong

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parallel-distribution: The parallel- specialized multi-CPU processing system has good disintegrate in functions so the time for reference is much less than the time for working in single-CPUs system of the system

2.2 Building mathematical model referenced the shared memory

in parallel multi-CPU processing system

2.2.1 The traditional reference model to the shared memory in parallel multi-CPU processing system

2.2.2 Building the improved reference model to the shared memory

in parallel multi-CPU processing system

To build a mathematical model, the thesis determined from the definitions of the performance E The E-assessing performance is defined here as the ratio of:

0/ acc

acc N N

E 

In which : Nacc - Total number of successful reference

MUX Control

Shared memory

+ Address channel + Controlling channel

Figure 2.1: Refering the shared memory in

parallel processing system

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Nacc0 - Total number of reference launched by the system If we call the probability of reference to SSS as E to ensure referring successfully, we need 1/ E test

Call P is the probability of the entrance reference registers is unoccupied (P is the conditional probability of entrance register is unoccupied), even when you are Q =1- P To refer successfully, we need 1/E1 test with a conditional probability P (E1 – the performance

of entrance reference register is unoccupied)

The probability of occupied entrance reference registers is 1 - P to ensure a successful reference, we need 1/Ep test (Ep – The performance of busy entrance reference register) So we turn to the problem of conditional probability, with a relationship:

E E

Q E

P

N

N

p l

p l

QE PE

E E E

This is a mathematical model to determine the performance of shared memory’s architecture with a buffering as role of queuing at the entrance and exit of the physical memory module To determine this model and appear controlling parameters, we need calculate three components: (i) P – the probability of unoccupied entrance reference register, (ii) Ep – The performance of occupied entrance reference register, (iii) El - The performance of unoccupied entrance reference register These quantities are complex and highly dependent on parameters related to the system’s structure

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