• Journal of Elementary Mathematics Education in Korea
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• v.22 no.4
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• pp.369-384
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• 2018

Multiplication is able to be described by using repeated addition, a Cartesian product, a scalar operation, rectangular array and area in many various context. Multiplication in various problem situations is learned by various of the teaching method and the order of teaching more than any other mathematical concepts and operations in elementary school. Nevertheless, the context of multiplication leaves further room for improvement. The purpose of this study is to examine the similarities and differences between the conceptual aspects of multiplication through the literature and to analyze the appropriateness of the teaching method and the order of teaching through textbook analysis. As a result of the study, it was found that multiplication of a scalar operation was introduced too early and did not properly reflect of meaning of multiplication as a scalar operation. There is also a need to use the concept of the rectangular array or area as a meaning of multiplication two quantities.

• Journal of Applied and Pure Mathematics
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• v.6 no.3_4
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• pp.167-176
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• 2024

This study is about division and right multiplication in matrices. The discussion of the properties of multiplication and division is examined. Some results between multiplication based on the row-column relationship and division based on the same relationship are discussed. The commonalities of these results between the processes are emphasized. Examples of unrealized properties are given. The algebraic properties of the newly defined right product and division are clarified in matrices. The properties of the known multiplication operation and new situations between right multiplication and division are investigated. Some results are declared between the transpositions of matrices and the obtained rules of operations. New results are discussed belong the equations ${\underleftarrow{XA}}=B$ and ${\underleftarrow{AX}}=B$. New ideas are proposed for solving these equations. The contribution The contribution is explained the equation $AB={\underleftarrow{BA}}$ to division operation. Many new properties, lemmas and theorems are presented on this subject.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.223-225
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• 2021

Modular multiplication is a key operation for point scalar multiplication of ECC, and is the most important factor affecting the performance of ECC processor. This paper describes a design of a 256-bit modular multiplier that adopts 3-way Toom-Cook multiplication algorithm and modified fast reduction algorithm. One 90-bit multiplier and three 264-bit adders were used to optimize the hardware size and the number of clock cycles required. The modular multiplier was verified by implementing it using Zynq UltraScale+ MPSoC device and the modular multiplication operation takes 15 clock cycles.

• MALSORI
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• no.47
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• pp.85-96
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• 2003

It is difficult to implement sound field effect on real time using linear convolution in time domain because linear convolution needs much multiply operations. In this paper three ways is introduced to reduce multiplication operations. Firstly, linear convolution in time domain is replaced with circular convolution in frequency domain. It means that it operates multiplication in place of convolution. Secondly, one frame will be divided into several frames. It will reduce the multiplication operation in processing that transforms time domain into frequency domain. Finally, QFT will be used in place of FFT. Three ways result much reduction in multiplication operations. The reduction of the multiplication operation makes the real time implementation possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.738-756
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• 2020

The modular multiplication is the key module of public-key cryptosystems such as RSA (Rivest-Shamir-Adleman) and ECC (Elliptic Curve Cryptography). However, the efficiency of the modular multiplication, especially the modular square, is very low. In order to reduce their operation cycles and power consumption, and improve the efficiency of the public-key cryptosystems, a dual-field efficient FIPS (Finely Integrated Product Scanning) modular multiplication algorithm is proposed. The algorithm makes a full use of the correlation of the data in the case of equal operands so as to avoid some redundant operations. The experimental results show that the operation speed of the modular square is increased by 23.8% compared to the traditional algorithm after the multiplication and addition operations are reduced about (s² - s) / 2, and the read operations are reduced about s² - s, where s = n / 32 for n-bit operands. In addition, since the algorithm supports the length scalable and dual-field modular multiplication, distinct applications focused on performance or cost could be satisfied by adjusting the relevant parameters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1257-1263
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• 2018

Secure authentication technology is a fundamental building block for secure services for Internet of Things devices. Particularly, the multiplication operation is a core operation of public key cryptography, such as RSA, ECC, and SIDH. However, modern low-power processor, namely ARM Cortex-M3 processor, is not secure enough for practical usages, since it executes the multiplication operation in variable-time depending on the input length. When the execution is performed in variable-time, the attacker can extract the password from the measured timing. In order to resolve this issue, recent work presented constant-time solution for multiplication operation. However, the implementation still missed various speed-optimization techniques. In this paper, we analyze previous multiplication methods over ARM Cortex-M3 and provide optimized implementations to accelerate the speed-performance further. The proposed method successfully accelerates the execution-time by up-to 25.7% than previous works.

• Journal of information and communication convergence engineering
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• v.13 no.1
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• pp.27-35
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• 2015

Multiprecision multiplication is the most expensive operation in public key-based cryptography. Therefore, many multiplication methods have been studied intensively for several decades. In Workshop on Cryptographic Hardware and Embedded Systems 2011 (CHES2011), a novel multiplication method called 'operand caching' was proposed. This method reduces the number of required load instructions by caching the operands. However, it does not provide full operand caching when changing the row of partial products. To overcome this problem, a novel method, that is, 'consecutive operand caching' was proposed in Workshop on Information Security Applications 2012 (WISA2012). It divides a multiplication structure into partial products and reconstructs them to share common operands between previous and next partial products. However, there is still room for improvement; therefore, we propose a finely designed operand-caching mode to minimize useless memory accesses when the first row is changed. Finally, we reduce the number of memory access instructions and boost the speed of the overall multiprecision multiplication for public key cryptography.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.367-374
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• 2022

The acceleration of neural networks has become an important topic in the field of computer vision. An accelerator is absolutely necessary for accelerating the lightweight model. Most accelerator-supported operators focused on direct convolution operations. If the accelerator does not provide GEMM operation, it is mostly replaced by CPU operation. In this paper, we proposed an optimization technique for 2-stage tiling-based GEMM routines on VTA. We improved performance of the matrix multiplication routine by maximizing the reusability of the input matrix and optimizing the operation pipelining. In addition, we applied the proposed technique to the DarkNet framework to check the performance improvement of the matrix multiplication routine. The proposed GEMM method showed a performance improvement of more than 2.4 times compared to the non-optimized GEMM method. The inference performance of our DarkNet framework has also improved by at least 2.3 times.

• Journal of IKEEE
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• v.24 no.4
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• pp.961-968
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• 2020

This paper describes a design of high performance modular multiplier that is essentially used for elliptic curve cryptography. Our modular multiplier supports modular multiplications for five field sizes over GF(p), including 192, 224, 256, 384 and 521 bits as defined in NIST FIPS 186-2, and it calculates modular multiplication in two steps with integer multiplication and reduction. The Karatsuba-Ofman multiplication algorithm was used for fast integer multiplication, and the Lazy reduction algorithm was adopted for reduction operation. In addition, the Nikhilam division algorithm was used for the division operation included in the Lazy reduction. The division operation is performed only once for a given modulo value, and it was designed to skip division operation when continuous modular multiplications with the same modulo value are calculated. It was estimated that our modular multiplier can perform 6.4 million modular multiplications per second when operating at a clock frequency of 32 MHz. It occupied 456,400 gate equivalents (GEs), and the estimated clock frequency was 67 MHz when synthesized with a 180-nm CMOS cell library.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1359-1371
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• 2020

In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.