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Dual-step optimization for binary sequences with high merit factors

Digital Signal Processing: A Review Journal 2025年 165卷

作者： Pšeničnik, Blaž Mlinarič, Rene Brest, Janez Bošković, Borko Computer Architecture and Languages Laboratory Institute of Computer Science Faculty of Electrical Engineering and Computer Science University of Maribor Koroška c. 46 Maribor2000 Slovenia

The problem of finding aperiodic low auto-correlation binary sequences (LABS) presents a significant computational challenge, particularly as the sequence length increases. Such sequences have important applications in communication engineering, physics, chemistry, and cryptography. This paper introduces a dual-step algorithm for long binary sequences with high merit factors. The first step employs a parallel algorithm utilizing skew-symmetry and restriction classes to generate sequence candidates with merit factors above a predefined threshold. The second step uses a priority queue algorithm to refine these candidates further, searching the entire search space unrestrictedly. By combining GPU-based parallel computing and dual-step optimization, our approach has successfully identified best-known binary sequences for all lengths ranging from 450 to 527, with the exception of length 518, where the previous best-known merit factor value was matched with a different sequence. This hybrid method significantly outperforms traditional exhaustive and stochastic search methods, offering an efficient solution for finding long sequences with good merit factors. © 2025 The Author(s)

关键词： Digital arithmetic

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PARBLO:Page-Allocation-Based DRAM Row Buffer Locality Optimization

引用

Journal of computer Science & Technology 2009年第6期24卷 1086-1097页

作者：米伟冯晓兵贾耀仓陈莉薛京灵 Key Laboratory of Computer System and Architecture Institution of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences Programming Languages and Compilers Group School of Computer Science and Engineering University of New South Wales

DRAM row buffer conflicts can increase memory access latency significantly. This paper presents a new pageallocation-based optimization that works seamlessly together with some existing hardware and software optimizations to eliminate significantly more row buffer conflicts. Validation in simulation using a set of selected scientific and engineering benchmarks against a few representative memory controller optimizations shows that our method can reduce row buffer miss rates by up to 76% （with an average of 37.4%）. This reduction in row buffer miss rates will be translated into performance speedups by up to 15% （with an average of 5%）.

关键词： DRAM row buffer page allocation locality optimization

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Population Size in Differential Evolution 1

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7th International Conference on Swarm, Evolutionary, and Memetic Computing, SEMCCO 2019, and 5th International Conference on Fuzzy and Neural Computing, FANCCO 2019

作者： Alić, Amina Berkovič, Klemen Bošković, Borko Brest, Janez Faculty of Electrical Engineering and Computer Science Computer Architecture and Languages Laboratory Institute of Computer Science University of Maribor Maribor2000 Slovenia

ISBN: (数字)9783030378387

ISBN: (纸本)9783030378370

In this paper we examined how the population size affects the performance of the differential evolution algorithm. First, we tested the original differential evolution algorithm, and then the improved self-adaptive differential evolution algorithm, on ten benchmark functions, that have been proposed for the CEC 2019 competition. We used six different population sizes. Afterwards, we tested the newly created algorithm with population reinitialization. The results show that the population size affects the algorithm’s efficiency, and that we need to tune it to obtain the best results. In the paper, we demonstrate that the newly created algorithm with reinitialization gives better, or at least comparable, results than the two algorithms without reinitialization. © Springer Nature Switzerland AG 2020.

关键词： Population statistics

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A Hybrid Circular Queue Method for Iterative Stencil Computations on GPUs

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Journal of computer Science & Technology 2012年第1期27卷 57-74页

作者： Yang Yang Hui-Min Cui Xiao-Bing Feng Jing-Ling Xue State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China Graduate University of Chinese Academy of Sciences Beijing 100190China Programming Languages and Compilers Group School of Computer Science and Engineering University of New South WalesSydneyNSW 2052Australia

In this paper, we present a hybrid circular queue method that can significantly boost the performance of stencil computations on GPU by carefully balancing usage of registers and shared-memory. Unlike earlier methods that rely on circular queues predominantly implemented using indirectly addressable shared memory, our hybrid method exploits a new reuse pattern spanning across the multiple time steps in stencil computations so that circular queues can be implemented by both shared memory and registers effectively in a balanced manner. We describe a framework that automatically finds the best placement of data in registers and shared memory in order to maximize the performance of stencil computations. Validation using four different types of stencils on three different GPU platforms shows that our hybrid method achieves speedups up to 2.93X over methods that use circular queues implemented with shared-memory only.

关键词： stencil computation circular queue GPU occupancy register

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DUAL-STEP OPTIMIZATION FOR BINARY SEQUENCES WITH HIGH MERIT FACTORS

arXiv

引用

arXiv 2024年

作者： Pšeničnik, Blaž Mlinarič, Rene Brest, Janez Bošković, Borko Computer Architecture and Languages Laboratory Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia

MSC Codes 68T20The problem of finding aperiodic low auto-correlation binary sequences (LABS) presents a significant computational challenge, particularly as the sequence length increases. Such sequences have important applications in communication engineering, physics, chemistry, and cryptography. This paper introduces a novel dual-step algorithm for long binary sequences with high merit factors. The first step employs a parallel algorithm utilizing skew-symmetry and restriction classes to generate sequence candidates with merit factors above a predefined threshold. The second step uses a priority queue algorithm to refine these candidates further, searching the entire search space unrestrictedly. By combining GPU-based parallel computing and dual-step optimization, our approach has successfully identified new best-known binary sequences for all lengths ranging from 450 to 527, with the exception of length 518, where the previous best-known value was matched with a different sequence. This hybrid method significantly outperforms traditional exhaustive and stochastic search methods, offering an efficient solution for finding long sequences with good merit factors. © 2024, CC BY.

关键词： Stochastic systems

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Hy perflow 3

Hy perflow

引用

3rd Conference on Hypercube Concurrent computers and Applications, C3P 1988

作者： DeForest, D. Faustini, A. Lee, R. Declarative Languages and Advanced Architecture Group Department of Computer Science Arizona State University TempeAZ85287 United States Hypercube Group Jet Propulsion Laboratory PasadenaCA91109 United States

In this paper we show how a model of parallel computation called Eduction (tagged demand-driven dataflow) can be implemented on a hypercube. The resulting implementation is called Hyperflow. In addition we will deal w... 详细信息

ISBN: (纸本)0897912780

关键词： Data flow analysis

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Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization

Differential Evolution with Self-adaptation and Local Search...

引用

Congress on Evolutionary Computation

作者： Ales Zamuda Janez Brest Borko Boskovic Viljem Zumer Computer Architecture and Languages Laboratory Institute of Computer Science Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

This paper presents differential evolution with self-adaptation and local search for constrained multiobjective optimization algorithm (DECMOSA-SQP), which uses the self-adaptation mechanism from DEMOwSA algorithm presented at CEC 2007 and a SQP local search. The constrained handling mechanism is also incorporated in the new algorithm. Assessment of the algorithm using CEC 2009 special session and competition on constrained multiobjective optimization test functions is presented. The functions are composed of unconstrained and constrained problems. Their results are assessed using the IGD metric. Based on this metric, algorithm strengths and weaknesses are discussed.

关键词： Constraint optimization Testing Evolutionary computation computer science Quadratic programming Simulated annealing Computational modeling Guidelines computer architecture Search methods

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Differential evolution for multiobjective optimization with self adaptation

Differential evolution for multiobjective optimization with ...

引用

Congress on Evolutionary Computation

This paper presents performance assessment of differential evolution for multiobjective optimization with self adaptation algorithm, which uses the self adaptation mechanism from evolution strategies to adapt F and CR parameters of the candidate creation in DE. Results for several runs on CEC2007 special session test functions are presented and assessed with different performance metrics. Based on these metrics, algorithm strengths and weaknesses are discussed.

关键词： Chromium Measurement Evolutionary computation Genetic mutations computer science Automatic testing Simulated annealing Performance evaluation computer architecture Ground penetrating radar

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