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Citation - Scopus: 5
Nfa Based Regular Expression Matching on Fpga
(IEEE, 2021) Sert, Kamil; Bazlamaçcı, Cüneyt
String matching is about finding all occurrences of a string within a given text. String matching algorithms have important roles in various real world areas such as web and security applications. In this work, we are interested in solving regular expression matching hence a more general form of string matching problem targeting especially the field of network intrusion detection systems (NIDS). In our work, we enhance a non-deterministic finite automata (NFA) based method on FPGA considerably. We propose to use a matching structure that processes two consecutive characters instead of one in order to yield better memory utilization and provide a novel mapping of this new architecture onto FPGA. The amount of digital circuitry needed to represent the NFA is reduced due to having less number of states and less number of LUTs in the devised 2-character regex matching process. An evaluation study is performed using the well-known Snort rule set and a sizable performance improvement is demonstrated.
Citation - Scopus: 2
Workload Distribution on Heterogeneous Platforms
(IEEE, 2021) Alasmar, Mahmoud; Bazlamaçcı, Cüneyt
This paper targets the problem of finding an efficient distribution of a computational task on a heterogeneous computing platform. The heterogeneity of the processing elements arise due to differences in computation speed and memory capacity of the processors. We first consider using a discrete functional performance model that integrates processing speed and capacity of processing elements and then develop a mathematical model and propose a heuristic mapping algorithm for distributing a given total workload of size N on p processing elements such that the total computation time is minimized. Computational results show that the proposed method provides a significant improvement in reducing the computation time in comparison to equal distribution approach.
Citation - WoS: 1
Citation - Scopus: 1
Hybrid Probabilistic Timing Analysis With Extreme Value Theory and Copulas
(Elsevier, 2022) Bekdemir, Levent; Bazlamaçcı, Cüneyt F.
The primary challenge of time-critical systems is to guarantee that a task completes its execution before its deadline. In order to ensure compliance with timing requirements, it is necessary to analyze the timing behavior of the overall software. Worst-Case Execution Time (WCET) represents the maximum amount of time an individual software unit takes to execute and is used for scheduling analysis in safety-critical systems. Recent studies focus on statistical approaches, which augments measurement-based timing analysis with probabilistic confidence level by applying stochastic methods. Common approaches either utilize Extreme Value Theory (EVT) for end-to-end measurements or convolution techniques for a group of program units to derive probabilistic upper bounds for the program. The former method does not ensure path coverage while the latter suffers from ignoring possible extreme cases. Furthermore, current state-of-the-art convolution methods employed in a commercial WCET analysis tool overestimates the results because of using the assumption of worst-case dependence between basic blocks. In this paper, we propose a hybrid probabilistic timing analysis framework and modeling the program units with EVT to capture extreme cases and use Copulas to model the dependency between the units to derive tighter distributional bounds in order to mitigate the effects of co-monotonic assumptions.

Computer Engineering / Bilgisayar Mühendisliği

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