• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.9-26
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• 2005

In the pursuit of ever higher levels of performance, recent computer systems have made use of deep pipeline, dynamic scheduling and multi-issue superscalar processor technologies. In this situations, branch prediction schemes are an essential part of modem microarchitectures because the penalty for a branch misprediction increases as pipelines deepen and the number of instructions issued per cycle increases. In this paper, we propose a novel branch prediction scheme, direction-gshare(d-gshare), to improve the prediction accuracy. At first, we model a neural network with the components that possibly affect the branch prediction accuracy, and analyze the variation of their weights based on the neural network information. Then, we newly add the component that has a high weight value to an original gshare scheme. We simulate our branch prediction scheme using Simple Scalar, a powerful event-driven simulator, and analyze the simulation results. Our results show that, compared to bimodal, two-level adaptive and gshare predictor, direction-gshare predictor(d-gshare. 3) outperforms, without additional hardware costs, by up to 4.1% and 1.5% in average for the default mont of embedded direction, and 11.8% in maximum and 3.7% in average for the optimal one.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.116-126
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• 2011

In this paper, we present a multi-media processor which can decode multiple-format video standards. The designed processor is evaluated with optimized MPEG-2, MPEG-4, and AVS (Audio video standard). There are two approaches for developing of real-time video decoders. First, hardware-based system is much superior to a processor-based one in execution time. However, it takes long time to implement and modify hardware systems. On the contrary, the software-based video codecs can be easily implemented and flexible, however, their performance is not so good for real-time applications. In this paper, in order to exploit benefits related to two approaches, we designed a processor called ASIP(Application specific instruction-set processor) for video decoding. In our work, we extracted eight common modules from various video decoders, and added several multimedia instructions to the processor. The developed processor for video decoders is evaluated with the Synopsys platform simulator and a FPGA board. In our experiment, we can achieve about 37% time saving in total decoding time.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.8
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• pp.171-180
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• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.289-298
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• 2014

Recently, the traditional paradigm in railroad technology is changing as more efficient and cost-effective electric vehicle (EV) technologies have emerged. The original concept of PRT (Personal Rapid Transit) proposed in the past has come to be regarded as unrealistic, but its feasibility is improving through the utilization of an EV platform. In particular, battery-powered vehicles pose difficult technical challenges in attempts to achieve reliable and efficient operation. However, based on the inductive power transfer (IPT) technology, the fast charging of supercapacitors with high energy density can contribute to overcoming this technical challenge and promote the transition to electric-powered ground transportation by improving the appearance of cities. This study discusses the development process of a power supply system for PRT, including concept design, numerical analysis, and device manufacturing, along with performance predictions and evaluations. In terms of results, the system was found to meet the performance requirements for power supply modules on a test-bed.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.813-823
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• 2020

Purpose: In order to maximize the stability and productivity of the work through simulation prior to high-risk facilities and high-cost work such as dismantling the facilities inside the reactor, we intend to use digital twin technology that can be closely controlled by simulating the specifications of the actual control equipment. Motion control errors, which can be caused by the time gap between precision control equipment and simulation in applying digital twin technology, can cause hazards such as collisions between hazardous facilities and control equipment. In order to eliminate and control these situations, prior research is needed. Method: Unity 3D is currently the most popular engine used to develop simulations. However, there are control errors that can be caused by time correction within Unity 3D engines. The error is expected in many environments and may vary depending on the development environment, such as system specifications. To demonstrate this, we develop crash simulations using Unity 3D engines, which conduct collision experiments under various conditions, organize and analyze the resulting results, and derive tolerances for precision control equipment based on them. Result: In experiments with collision experiment simulation, the time correction in 1/1000 seconds of an engine internal function call results in a unit-hour distance error in the movement control of the collision objects and the distance error is proportional to the velocity of the collision. Conclusion: Remote decomposition simulators using digital twin technology are considered to require limitations of the speed of movement according to the required precision of the precision control devices in the hardware and software environment and manual control. In addition, the size of modeling data such as system development environment, hardware specifications and simulations imitated control equipment and facilities must also be taken into account, available and acceptable errors of operational control equipment and the speed required of work.