• Journal of KIISE
• /
• v.42 no.4
• /
• pp.522-529
• /
• 2015

Ever since the R-tree was proposed to index multi-dimensional data, many efforts have been made to improve its query performances. One common trend to improve query performance is to parallelize query processing with the use of multi-core architectures. To this end, a GPU-base R-tree has been recently proposed. However, even though a GPU-based R-tree can exhibit an improvement in query performance, it is limited in its ability to handle large volumes of data because GPUs have limited physical memory. To address this problem, we propose MGR-tree (Multi-GPU R-tree), which can manage large volumes of data by dividing nodes into multiple GPUs. Our experiments show that MGR-tree is up to 9.1 times faster than a sequential search on a GPU and up to 1.6 times faster than a conventional GPU-based R-tree.

• Smart Media Journal
• /
• v.5 no.4
• /
• pp.69-74
• /
• 2016

Recently, parallel computing using GPGPU(General-Purpose computing on Graphics Processing Units) according to the development of the graphics processing unit is expanding. This can be achieved through the processing speeds faster than traditional computing environments across many fields, including science, medicine, engineering, and analysis. However, in using the GPU technology to implement the a parallel program there are many constraints. In this paper, we port a CPU-based program(Video Quality Measurement Program) to use technology. The program ported to GPU-based show about 1.83 times the execution speed than CPU-based program. We study on the acceleration of the GPU-based program. Also we discuss the technical constraints and problems that occur when you modify the CPU to the GPU-based programs.

• Spatial Information Research
• /
• v.17 no.3
• /
• pp.371-379
• /
• 2009

Recently, GPU (Graphics Processing Unit) has been improved rapidly on the need of speed for gaming. As a result, GPU contains multiple ALU (Arithmetic Logic Unit) for parallel processing of a lot of graphics data, such as transform, ray tracing, etc. Therefore, this paper proposed a technique for parallel processing of spatial data using GPU. Spatial data consists of multiple coordinates, and each coordinate contains value of x and y axis. To display spatial data graphics operations have to be processed to large amount of coordinates. Because the graphics operation is identical and coordinates are multiple data, SIMD (Single Instruction Multiple Data) parallel processing of GPU can be used for processing of spatial data to improve performance. This paper implemented SIMD parallel processing of spatial data using two kinds of SDK (Software Development Kit). CUDA and ATI Stream are used for NVIDIA and ATI GPU respectively. Experiments that measure time of calculation for graphics operations are carried out to observe enhancement of performance. Experimental result is reported that proposed method can enhance performance up to 1,162% for graphics operations. The proposed method that uses parallel processing with GPU for spatial data can be generally used to enhance performance for applications which deal with large amount of spatial data.

• Journal of Digital Contents Society
• /
• v.16 no.5
• /
• pp.805-813
• /
• 2015

Many researchers expect the compressive sensing and sparse recovery problem can overcome the limitation of conventional digital techniques. However, these new approaches require to solve the l1 norm optimization problems when it comes to signal reconstruction. In the signal reconstruction process, the transform computation by multiplication of a random matrix and a vector consumes considerable computing power. To address this issue, parallel processing is applied to the optimization problems. In particular, due to huge size of original signal, it is hard to store the random matrix directly in memory, which makes one need to design a procedural approach in handling the random matrix. This paper presents a new parallel algorithm to calculate random partial Haar wavelet transform based on Single Instruction Multiple Threads (SIMT) platform.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.6
• /
• pp.955-961
• /
• 2017

In this paper, we propose a parallel approximate string matching algorithm with k-mismatches for multiple fixed-length patterns (PMASM) in DNA sequences. PMASM is developed from parallel single pattern approximate string matching algorithms to effectively calculate the Hamming distances for multiple patterns with a fixed-length. In the preprocessing phase of PMASM, all target patterns are binary encoded and stored into a look-up memory. With each input character from the input string, the Hamming distances between a substring and all patterns can be updated at the same time based on the binary encoding information in the look-up memory. Moreover, PMASM adopts graphics processing units (GPUs) to process the data computations in parallel. This paper presents three kinds of PMASM implementation methods in GPUs: thread PMASM, block-thread PMASM, and shared-mem PMASM methods. The shared-mem PMASM method gives an example to effectively make use of the GPU parallel capacity. Moreover, it also exploits special features of the CUDA (Compute Unified Device Architecture) memory structure to optimize the performance. In the experiments with DNA sequences, the proposed PMASM on GPU is 385, 77, and 64 times faster than the traditional naive algorithm, the shift-add algorithm and the single thread PMASM implementation on CPU. With the same NVIDIA GPU model, the performance of the proposed approach is enhanced up to 44% and 21%, compared with the naive, and the shift-add algorithms.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.8
• /
• pp.1-8
• /
• 2013

This paper proposes an effective parallel implementation of a physical modeling synthesis of guitar on the GPU environment. We used appropriate filter coefficients and adjusted the length of delay line for each open string to generate 44,100 six-polyphonic guitar sounds (E2, A2, D3, G4, B3, E4) by using physical modeling synthesis. In addition, we analyzed the physical modeling synthesis algorithm and observed that we can exploit parallelism inherent in the length of delay line. Thus, we assigned CUDA cores as many as the length of delay line and effectively implemented the physical modeling synthesis using GPU to achieve the highest performance. Experimental results indicated that synthetic guitar sounds using GPU were very similar to the original sounds when we compared their spectra. In addition, GPU achieved 68x and 3x better performance than high-performance TI DSP and CPU, respectively. Furthermore, this paper implemented and evaluated the performance of multi-GPU systems for the physical modeling algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.3
• /
• pp.477-489
• /
• 2019

In this paper, we experimentally verify the expected differential probability under the markov cipher assumption and the distribution of the differential probability. Firstly, we validate the expected differential probability of 6round-PRESENT of the lightweight block cipher under the markov cipher assumption by analyzing the empirical differential probability. Secondly, we demonstrate that even though the expected differential probability under the markov cipher assumption seems valid, the empirical distribution does not follow the well-known distribution of the differential probability. The results was deduced from the 4round-GIFT. Finally, in order to analyze whether the key-schedule affects the mis-matching phenomenon, we collect the results while changing the XOR positions of round keys on GIFT. The results show that the key-schedule is not the only factor to affect the mis-matching phenomenon. Leveraging on GPGPU technology, the data collection process can be performed about 157 times faster than using CPU only.

• Journal of Broadcast Engineering
• /
• v.23 no.6
• /
• pp.876-885
• /
• 2018

Although e-sports broadcasting market based on VR(Virtual Reality) is growing in these days, technology development for securing market competitiveness is quite inadequate in Korea. Global companies such as SLIVER and Facebook already developed and are trying to commercialize 360 VR broadcasting technology which is able to broadcast e-sports in 4K 30FPS VR video. However, 2D video is too poor to use for 360 VR video in that it brings less immersive experience and dizziness and has low resolution in the scene. this paper, we not only proposed and implemented virtual camera technology which is able to capture in-game space as 360 video with 4K 3D by 60FPS for e-sports VR broadcasting but also verified feasibleness of obtaining stereo 360 video up to 4K/60FPS by conducting experiment after setting up virtual camera in sample games from game engine and commercial games.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.31 no.3
• /
• pp.481-496
• /
• 2021

It is imperative to migrate the current public key cryptosystem to a quantum-resistance system ahead of the realization of large-scale quantum computing technology. The National Institute of Standards and Technology, NIST, is promoting a public standardization project for Post-Quantum Cryptography(PQC) and also many research efforts have been conducted to apply PQC to TLS(Transport Layer Security) protocols, which are used for Internet communication security. In this paper, we propose a scenario in which a server and multi-clients share session keys on TLS by using the parallelized NTRU which is PQC in the key exchange process. In addition, we propose a method of accelerating NTRU using GPU and analyze its efficiency in an environment where a server needs to process large-scale data simultaneously.

• Journal of Positioning, Navigation, and Timing
• /
• v.10 no.4
• /
• pp.315-333
• /
• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.