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Developing Models for the Runtime of Programs With Exponential Runtime Behavior

Burger, Michael ; Nguyen, Giang Nam ; Bischof, Christian (2020)
Developing Models for the Runtime of Programs With Exponential Runtime Behavior.
2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS). virtual Conference (12.11.2020-12.11.2020)
doi: 10.1109/PMBS51919.2020.00015
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

In this paper, we present a new approach to generate runtime models for programs whose runtime grows exponentially with the value of one input parameter. Such programs are, e.g., of high interest for cryptanalysis to analyze practical security of traditional and post-quantum secure schemes. The model generation approach on the base of profiled training runs is built on ideas realized in the open source tool Extra-P, extended with a new class of model functions and a shared-memory parallel simulated annealing approach to heuristically determine coefficients for the model functions. Our approach is implemented in the open source software SimAnMo (Simulated Annealing Modeler). We demonstrate on various theoretical and synthetic, practical test cases that our approach delivers very accurate models and reliable predictions, compared to standard approaches on x86 and ARM architectures. SimAnMo is also employed to generate models of four codes which are employed to solve the so-called shortest vector problem. This is an important problem from the field of lattice-based cryptography. We demonstrate the quality of our models with measurements for higher lattice dimensions, as far as it is feasible. Additionally, we highlight inherent problems with models for algorithms with exponential runtime.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2020
Autor(en): Burger, Michael ; Nguyen, Giang Nam ; Bischof, Christian
Art des Eintrags: Bibliographie
Titel: Developing Models for the Runtime of Programs With Exponential Runtime Behavior
Sprache: Englisch
Publikationsjahr: 12 November 2020
Verlag: IEEE
Buchtitel: Proceedings of PMBS 2020: Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems
Veranstaltungstitel: 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)
Veranstaltungsort: virtual Conference
Veranstaltungsdatum: 12.11.2020-12.11.2020
DOI: 10.1109/PMBS51919.2020.00015
URL / URN: https://ieeexplore.ieee.org/document/9307859
Kurzbeschreibung (Abstract):

In this paper, we present a new approach to generate runtime models for programs whose runtime grows exponentially with the value of one input parameter. Such programs are, e.g., of high interest for cryptanalysis to analyze practical security of traditional and post-quantum secure schemes. The model generation approach on the base of profiled training runs is built on ideas realized in the open source tool Extra-P, extended with a new class of model functions and a shared-memory parallel simulated annealing approach to heuristically determine coefficients for the model functions. Our approach is implemented in the open source software SimAnMo (Simulated Annealing Modeler). We demonstrate on various theoretical and synthetic, practical test cases that our approach delivers very accurate models and reliable predictions, compared to standard approaches on x86 and ARM architectures. SimAnMo is also employed to generate models of four codes which are employed to solve the so-called shortest vector problem. This is an important problem from the field of lattice-based cryptography. We demonstrate the quality of our models with measurements for higher lattice dimensions, as far as it is feasible. Additionally, we highlight inherent problems with models for algorithms with exponential runtime.

Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Scientific Computing
DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1119: CROSSING – Kryptographiebasierte Sicherheitslösungen als Grundlage für Vertrauen in heutigen und zukünftigen IT-Systemen
Hinterlegungsdatum: 18 Jul 2022 08:56
Letzte Änderung: 18 Jul 2022 08:56
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