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Reiji Suda

Publications and source records attributed to Reiji Suda.

8 recordsLinked to original sources

Efficient Additions and Montgomery Reductions of Large Integers for SIMD

This paper presents efficient algorithms, designed to leverage SIMD for performing Montgomery reductions and additions on integers larger than 512 bits. The existing algorithms encounter inefficiencies when parallelized using SIMD due to extensive dependencies in both operations, particularly noticeable in costly operations like ARM's SVE. To mitigate this problem, a novel addition algorithm is introduced that simulates the addition of large integers using a smaller addition, quickly producing the same set of carries. These carries are then utilized to perform parallel additions on large integers. For Montgomery reductions, serial multiplications are replaced with precomputations that can be effectively calculated using SIMD extensions. Experimental evidence demonstrates that these proposed algorithms substantially enhance the performance of state-of-the-art implementations of several post-quantum cryptography algorithms. Notably, they deliver a 30% speed-up from the latest CTIDH implementation, an 11% speed-up from the latest CSIDH implementation in AVX-512 processors, and a 7% speed-up from Microsoft's standard PQCrypto-SIDH for SIKEp503 on A64FX.

cs.CR

Worst-Case Analysis of LPT Scheduling on Small Number of Non-Identical Processors

The approximation ratio of the longest processing time (LPT) scheduling algorithm has been studied in several papers. While the tight approximation ratio is known for the case when all processors are identical, the ratio is not yet known when the processors have different speeds. In this work, we give a tight approximation ratio for the case when the number of processors is 3,4, and 5. We show that the ratio for those cases are no more than the lower bound provided by Gonzalez, Ibarra, and Sahni (SIAM J. Computing 1977). They are approximately 1.38 for three processors, 1.43 for four processors, and 1.46 for five processors.

cs.DM

Train-by-Reconnect: Decoupling Locations of Weights from their Values

What makes untrained deep neural networks (DNNs) different from the trained performant ones? By zooming into the weights in well-trained DNNs, we found it is the location of weights that hold most of the information encoded by the training. Motivated by this observation, we hypothesize that weights in stochastic gradient-based method trained DNNs can be separated into two dimensions: the locations of weights and their exact values. To assess our hypothesis, we propose a novel method named Lookahead Permutation (LaPerm) to train DNNs by reconnecting the weights. We empirically demonstrate the versatility of LaPerm while producing extensive evidence to support our hypothesis: when the initial weights are random and dense, our method demonstrates speed and performance similar to or better than that of regular optimizers, e.g., Adam; when the initial weights are random and sparse (many zeros), our method changes the way neurons connect and reach accuracy comparable to that of a well-trained fully initialized network; when the initial weights share a single value, our method finds weight agnostic neural network with far better-than-chance accuracy.

cs.LG

Enumeration Based Search Algorithm For Finding A Regular Bi-partite Graph Of Maximum Attainable Girth For Specified Degree And Number Of Vertices

We introduce a search problem for finding a regular bi-partite graph of maximum attainable girth for specified degree and number of vertices, by restricting the search space using a series of mathematically rigourous arguments from [1] and [2]. The goal of this paper is to derive the enumeration search algorithm for finding a girth maximum (m, r) BTU, which is notation for regular partite graph that has been introduced in [1], using the optimal partition results from [2] as a starting point, and also understand the structure of the search space and the computational complexity of the algorithm.

cs.DM

Analysis Of The Girth For Regular Bi-partite Graphs With Degree 3

The goal of this paper is to derive the detailed description of the Enumeration Based Search Algorithm from the high level description provided in [16], analyze the experimental results from our implementation of the Enumeration Based Search Algorithm for finding a regular bi-partite graph of degree 3, and compare it with known results from the available literature. We show that the values of m for a given girth g for (m, 3) BTUs are within the known mathematical bounds for regular bi-partitite graphs from the available literature.

cs.DM

Partition Parameters for Girth Maximum (m, r) BTUs

This paper describes the calculation of the optimal partition parameters such that the girth maximum (m, r) Balanced Tanner Unit lies in family of BTUs specified by them using a series of proved results and thus creates a framework for specifying a search problem for finding the girth maximum (m, r) BTU. Several open questions for girth maximum (m, r) BTU have been raised.

cs.DM

A Mathematical Approach to Balanced Tanner Graph Enumeration

This paper summarizes our latest understanding and results about the application of the Mathematics Of Enumeration to Tanner Graphs that have a regular structure called Balanced Tanner Graphs. Some preliminaries of permutation groups have been presented followed by various enumeration theorems, and finally our approach for enumeration of Balanced Tanner Graphs has been explained, and several open questions have been raised.

cs.IT

Algorithms for Enumerating Balanced Tanner Graphs

This summarizes our latest understanding and results about the algorithms for enumerating Tanner Graphs that have a regular structure called Balanced Tanner Graphs. Enumeration algorithms for Balanced Tanner Graphs based upon Cyclic Permutation Groups have been developed in this paper. A constrained enumeration algorithm that enumerates Balanced Tanner Graphs that have a relatively larger length of minimum cycle has been described.

cs.IT