{"citation":{"short":"K.-H. Chen, C. Su, C. Hakert, S. Buschjäger, C.-L. Lee, J.-K. Lee, K. Morik, J.-J. Chen, ACM Transactions on Embedded Computing Systems 21 (2022) 1–26.","chicago":"Chen, Kuan-Hsun, Chiahui Su, Christian Hakert, Sebastian Buschjäger, Chao-Lin Lee, Jenq-Kuen Lee, Katharina Morik, and Jian-Jia Chen. “Efficient Realization of Decision Trees for Real-Time Inference.” <i>ACM Transactions on Embedded Computing Systems</i> 21, no. 6 (2022): 1–26. <a href=\"https://doi.org/10.1145/3508019\">https://doi.org/10.1145/3508019</a>.","apa":"Chen, K.-H., Su, C., Hakert, C., Buschjäger, S., Lee, C.-L., Lee, J.-K., Morik, K., &#38; Chen, J.-J. (2022). Efficient Realization of Decision Trees for Real-Time Inference. <i>ACM Transactions on Embedded Computing Systems</i>, <i>21</i>(6), 1–26. <a href=\"https://doi.org/10.1145/3508019\">https://doi.org/10.1145/3508019</a>","ieee":"K.-H. Chen <i>et al.</i>, “Efficient Realization of Decision Trees for Real-Time Inference,” <i>ACM Transactions on Embedded Computing Systems</i>, vol. 21, no. 6, pp. 1–26, 2022, doi: <a href=\"https://doi.org/10.1145/3508019\">10.1145/3508019</a>.","ama":"Chen K-H, Su C, Hakert C, et al. Efficient Realization of Decision Trees for Real-Time Inference. <i>ACM Transactions on Embedded Computing Systems</i>. 2022;21(6):1-26. doi:<a href=\"https://doi.org/10.1145/3508019\">10.1145/3508019</a>","bibtex":"@article{Chen_Su_Hakert_Buschjäger_Lee_Lee_Morik_Chen_2022, title={Efficient Realization of Decision Trees for Real-Time Inference}, volume={21}, DOI={<a href=\"https://doi.org/10.1145/3508019\">10.1145/3508019</a>}, number={6}, journal={ACM Transactions on Embedded Computing Systems}, publisher={Association for Computing Machinery (ACM)}, author={Chen, Kuan-Hsun and Su, Chiahui and Hakert, Christian and Buschjäger, Sebastian and Lee, Chao-Lin and Lee, Jenq-Kuen and Morik, Katharina and Chen, Jian-Jia}, year={2022}, pages={1–26} }","mla":"Chen, Kuan-Hsun, et al. “Efficient Realization of Decision Trees for Real-Time Inference.” <i>ACM Transactions on Embedded Computing Systems</i>, vol. 21, no. 6, Association for Computing Machinery (ACM), 2022, pp. 1–26, doi:<a href=\"https://doi.org/10.1145/3508019\">10.1145/3508019</a>."},"publisher":"Association for Computing Machinery (ACM)","_id":"66209","page":"1-26","volume":21,"user_id":"128464","status":"public","date_created":"2026-07-03T21:18:32Z","type":"journal_article","publication":"ACM Transactions on Embedded Computing Systems","issue":"6","abstract":[{"lang":"eng","text":"<jats:p>For timing-sensitive edge applications, the demand for efficient lightweight machine learning solutions has increased recently. Tree ensembles are among the state-of-the-art in many machine learning applications. While single decision trees are comparably small, an ensemble of trees can have a significant memory footprint leading to cache locality issues, which are crucial to performance in terms of execution time. In this work, we analyze memory-locality issues of the two most common realizations of decision trees, i.e., native and if-else trees. We highlight that both realizations demand a more careful memory layout to improve caching behavior and maximize performance. We adopt a probabilistic model of decision tree inference to find the best memory layout for each tree at the application layer. Further, we present an efficient heuristic to take architecture-dependent information into account thereby optimizing the given ensemble for a target computer architecture. Our code-generation framework, which is freely available on an open-source repository, produces optimized code sessions while preserving the structure and accuracy of the trees. With several real-world data sets, we evaluate the elapsed time of various tree realizations on server hardware as well as embedded systems for Intel and ARM processors. Our optimized memory layout achieves a reduction in execution time up to 75 % execution for server-class systems, and up to 70 % for embedded systems, respectively.</jats:p>"}],"language":[{"iso":"eng"}],"doi":"10.1145/3508019","author":[{"first_name":"Kuan-Hsun","last_name":"Chen","full_name":"Chen, Kuan-Hsun"},{"first_name":"Chiahui","last_name":"Su","full_name":"Su, Chiahui"},{"first_name":"Christian","last_name":"Hakert","full_name":"Hakert, Christian"},{"first_name":"Sebastian","last_name":"Buschjäger","full_name":"Buschjäger, Sebastian"},{"full_name":"Lee, Chao-Lin","last_name":"Lee","first_name":"Chao-Lin"},{"full_name":"Lee, Jenq-Kuen","last_name":"Lee","first_name":"Jenq-Kuen"},{"last_name":"Morik","first_name":"Katharina","full_name":"Morik, Katharina"},{"last_name":"Chen","first_name":"Jian-Jia","full_name":"Chen, Jian-Jia"}],"publication_identifier":{"issn":["1539-9087","1558-3465"]},"year":"2022","title":"Efficient Realization of Decision Trees for Real-Time Inference","intvolume":"        21","publication_status":"published","date_updated":"2026-07-05T14:45:55Z"}