[{"language":[{"iso":"eng"}],"user_id":"64665","department":[{"_id":"78"}],"_id":"54468","status":"public","type":"conference","publication":"To apear in IEEE ISVLSI 2024","conference":{"location":"Knoxville, Tennessee, USA","end_date":"2024-07-03","start_date":"2024-07-01","name":"IEEE Computer Society Annual Symposium on VLSI"},"title":"DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing","author":[{"id":"64665","full_name":"Awais, Muhammad","orcid":"https://orcid.org/0000-0003-4148-2969","last_name":"Awais","first_name":"Muhammad"},{"first_name":"Hassan","id":"61186","full_name":"Ghasemzadeh Mohammadi, Hassan","last_name":"Ghasemzadeh Mohammadi"},{"first_name":"Marco","id":"398","full_name":"Platzner, Marco","last_name":"Platzner"}],"date_created":"2024-05-28T08:14:43Z","date_updated":"2024-05-29T08:26:29Z","citation":{"apa":"Awais, M., Ghasemzadeh Mohammadi, H., &#38; Platzner, M. (2024). DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing. <i>To Apear in IEEE ISVLSI 2024</i>. IEEE Computer Society Annual Symposium on VLSI, Knoxville, Tennessee, USA.","short":"M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: To Apear in IEEE ISVLSI 2024, 2024.","mla":"Awais, Muhammad, et al. “DeepApprox: Rapid Deep Learning Based Design Space Exploration of Approximate Circuits via Check-Pointing.” <i>To Apear in IEEE ISVLSI 2024</i>, 2024.","bibtex":"@inproceedings{Awais_Ghasemzadeh Mohammadi_Platzner_2024, title={DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing}, booktitle={To apear in IEEE ISVLSI 2024}, author={Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}, year={2024} }","ieee":"M. Awais, H. Ghasemzadeh Mohammadi, and M. Platzner, “DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing,” presented at the IEEE Computer Society Annual Symposium on VLSI, Knoxville, Tennessee, USA, 2024.","chicago":"Awais, Muhammad, Hassan Ghasemzadeh Mohammadi, and Marco Platzner. “DeepApprox: Rapid Deep Learning Based Design Space Exploration of Approximate Circuits via Check-Pointing.” In <i>To Apear in IEEE ISVLSI 2024</i>, 2024.","ama":"Awais M, Ghasemzadeh Mohammadi H, Platzner M. DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing. In: <i>To Apear in IEEE ISVLSI 2024</i>. ; 2024."},"year":"2024"},{"publication_status":"published","year":"2021","page":"27-32","citation":{"bibtex":"@inproceedings{Awais_Ghasemzadeh Mohammadi_Platzner_2021, title={LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis}, DOI={<a href=\"https://doi.org/10.1145/3453688.3461506\">https://doi.org/10.1145/3453688.3461506</a>}, booktitle={Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021}, publisher={ACM}, author={Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}, year={2021}, pages={27–32} }","short":"M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021, ACM, 2021, pp. 27–32.","mla":"Awais, Muhammad, et al. “LDAX: A Learning-Based Fast Design Space Exploration Framework for Approximate Circuit Synthesis.” <i>Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021</i>, ACM, 2021, pp. 27–32, doi:<a href=\"https://doi.org/10.1145/3453688.3461506\">https://doi.org/10.1145/3453688.3461506</a>.","apa":"Awais, M., Ghasemzadeh Mohammadi, H., &#38; Platzner, M. (2021). LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. In <i>Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021</i> (pp. 27–32). Virtual: ACM. <a href=\"https://doi.org/10.1145/3453688.3461506\">https://doi.org/10.1145/3453688.3461506</a>","ieee":"M. Awais, H. Ghasemzadeh Mohammadi, and M. Platzner, “LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis,” in <i>Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021</i>, Virtual, 2021, pp. 27–32.","chicago":"Awais, Muhammad, Hassan Ghasemzadeh Mohammadi, and Marco Platzner. “LDAX: A Learning-Based Fast Design Space Exploration Framework for Approximate Circuit Synthesis.” In <i>Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021</i>, 27–32. ACM, 2021. <a href=\"https://doi.org/10.1145/3453688.3461506\">https://doi.org/10.1145/3453688.3461506</a>.","ama":"Awais M, Ghasemzadeh Mohammadi H, Platzner M. LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. In: <i>Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021</i>. ACM; 2021:27-32. doi:<a href=\"https://doi.org/10.1145/3453688.3461506\">https://doi.org/10.1145/3453688.3461506</a>"},"publisher":"ACM","date_updated":"2022-01-06T06:55:07Z","author":[{"first_name":"Muhammad","last_name":"Awais","orcid":"https://orcid.org/0000-0003-4148-2969","full_name":"Awais, Muhammad","id":"64665"},{"first_name":"Hassan","last_name":"Ghasemzadeh Mohammadi","full_name":"Ghasemzadeh Mohammadi, Hassan","id":"61186"},{"last_name":"Platzner","full_name":"Platzner, Marco","id":"398","first_name":"Marco"}],"date_created":"2021-04-13T10:17:47Z","title":"LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis","conference":{"location":"Virtual","end_date":"2021-06-25","start_date":"2021-06-22","name":"31st ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021"},"doi":"https://doi.org/10.1145/3453688.3461506","publication":"Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021","type":"conference","status":"public","_id":"21610","department":[{"_id":"78"}],"user_id":"64665","language":[{"iso":"eng"}]},{"department":[{"_id":"78"}],"user_id":"64665","_id":"22309","language":[{"iso":"eng"}],"keyword":["Approximate computing","Design space exploration","Accelerator synthesis"],"publication":"Proceedings of IEEE Computer Society Annual Symposium on VLSI","type":"conference","status":"public","abstract":[{"text":"Approximate computing (AC) has acquired significant maturity in recent years as a promising approach to obtain energy and area-efficient hardware. Automated approximate accelerator synthesis involves a great deal of complexity on the size of design space which exponentially grows with the number of possible approximations. Design space exploration of approximate accelerator synthesis is usually targeted via heuristic-based search methods. The majority of existing frameworks prune a large part of the design space using a greedy-based approach to keep the problem tractable. Therefore, they result in inferior solutions since many potential solutions are neglected in the pruning process without the possibility of backtracking of removed approximate instances. In this paper, we address the aforementioned issue by adopting Monte Carlo Tree Search (MCTS), as an efficient stochastic learning-based search algorithm, in the context of automated synthesis of approximate accelerators. This enables the synthesis frameworks to deeply subsamples the design space of approximate accelerator synthesis toward most promising approximate instances based on the required performance goals, i.e., power consumption, area, or/and delay. We investigated the challenges of providing an efficient open-source framework that benefits analytical and search-based approximation techniques simultaneously to both speed up the synthesis runtime and improve the quality of obtained results. Besides, we studied the utilization of machine learning algorithms to improve the performance of several critical steps, i.e., accelerator quality testing, in the synthesis framework. The proposed framework can help the community to rapidly generate efficient approximate accelerators in a reasonable runtime.","lang":"eng"}],"author":[{"id":"64665","full_name":"Awais, Muhammad","last_name":"Awais","orcid":"https://orcid.org/0000-0003-4148-2969","first_name":"Muhammad"},{"first_name":"Marco","last_name":"Platzner","full_name":"Platzner, Marco"}],"date_created":"2021-06-14T14:05:17Z","date_updated":"2022-01-06T06:55:31Z","publisher":"IEEE","conference":{"name":"IEEE Computer Society Annual Symposium on VLSI","start_date":"2021-07-07","end_date":"2021-07-09","location":"Tampa, Florida USA (Virtual)"},"title":"MCTS-Based Synthesis Towards Efficient Approximate Accelerators","page":"384-389","citation":{"ama":"Awais M, Platzner M. MCTS-Based Synthesis Towards Efficient Approximate Accelerators. In: <i>Proceedings of IEEE Computer Society Annual Symposium on VLSI</i>. IEEE; 2021:384-389.","ieee":"M. Awais and M. Platzner, “MCTS-Based Synthesis Towards Efficient Approximate Accelerators,” in <i>Proceedings of IEEE Computer Society Annual Symposium on VLSI</i>, Tampa, Florida USA (Virtual), 2021, pp. 384–389.","chicago":"Awais, Muhammad, and Marco Platzner. “MCTS-Based Synthesis Towards Efficient Approximate Accelerators.” In <i>Proceedings of IEEE Computer Society Annual Symposium on VLSI</i>, 384–89. IEEE, 2021.","bibtex":"@inproceedings{Awais_Platzner_2021, title={MCTS-Based Synthesis Towards Efficient Approximate Accelerators}, booktitle={Proceedings of IEEE Computer Society Annual Symposium on VLSI}, publisher={IEEE}, author={Awais, Muhammad and Platzner, Marco}, year={2021}, pages={384–389} }","short":"M. Awais, M. Platzner, in: Proceedings of IEEE Computer Society Annual Symposium on VLSI, IEEE, 2021, pp. 384–389.","mla":"Awais, Muhammad, and Marco Platzner. “MCTS-Based Synthesis Towards Efficient Approximate Accelerators.” <i>Proceedings of IEEE Computer Society Annual Symposium on VLSI</i>, IEEE, 2021, pp. 384–89.","apa":"Awais, M., &#38; Platzner, M. (2021). MCTS-Based Synthesis Towards Efficient Approximate Accelerators. <i>Proceedings of IEEE Computer Society Annual Symposium on VLSI</i>, 384–389."},"year":"2021"},{"publisher":"ACM","date_updated":"2022-01-06T06:52:45Z","author":[{"orcid":"https://orcid.org/0000-0003-4148-2969","last_name":"Awais","id":"64665","full_name":"Awais, Muhammad","first_name":"Muhammad"},{"last_name":"Ghasemzadeh Mohammadi","full_name":"Ghasemzadeh Mohammadi, Hassan","id":"61186","first_name":"Hassan"},{"first_name":"Marco","id":"398","full_name":"Platzner, Marco","last_name":"Platzner"}],"date_created":"2020-03-02T15:49:38Z","title":"A Hybrid Synthesis Methodology for Approximate Circuits","doi":"10.1145/3386263.3406952","conference":{"location":"Beijing, China","name":"ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020"},"publication_status":"published","year":"2020","page":"421-426","citation":{"bibtex":"@inproceedings{Awais_Ghasemzadeh Mohammadi_Platzner_2020, title={A Hybrid Synthesis Methodology for Approximate Circuits}, DOI={<a href=\"https://doi.org/10.1145/3386263.3406952\">10.1145/3386263.3406952</a>}, booktitle={Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020}, publisher={ACM}, author={Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}, year={2020}, pages={421–426} }","mla":"Awais, Muhammad, et al. “A Hybrid Synthesis Methodology for Approximate Circuits.” <i>Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020</i>, ACM, 2020, pp. 421–26, doi:<a href=\"https://doi.org/10.1145/3386263.3406952\">10.1145/3386263.3406952</a>.","short":"M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020, ACM, 2020, pp. 421–426.","apa":"Awais, M., Ghasemzadeh Mohammadi, H., &#38; Platzner, M. (2020). A Hybrid Synthesis Methodology for Approximate Circuits. In <i>Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020</i> (pp. 421–426). Beijing, China: ACM. <a href=\"https://doi.org/10.1145/3386263.3406952\">https://doi.org/10.1145/3386263.3406952</a>","ama":"Awais M, Ghasemzadeh Mohammadi H, Platzner M. A Hybrid Synthesis Methodology for Approximate Circuits. In: <i>Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020</i>. ACM; 2020:421-426. doi:<a href=\"https://doi.org/10.1145/3386263.3406952\">10.1145/3386263.3406952</a>","chicago":"Awais, Muhammad, Hassan Ghasemzadeh Mohammadi, and Marco Platzner. “A Hybrid Synthesis Methodology for Approximate Circuits.” In <i>Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020</i>, 421–26. ACM, 2020. <a href=\"https://doi.org/10.1145/3386263.3406952\">https://doi.org/10.1145/3386263.3406952</a>.","ieee":"M. Awais, H. Ghasemzadeh Mohammadi, and M. Platzner, “A Hybrid Synthesis Methodology for Approximate Circuits,” in <i>Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020</i>, Beijing, China, 2020, pp. 421–426."},"_id":"16213","department":[{"_id":"78"}],"user_id":"64665","language":[{"iso":"eng"}],"publication":"Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020","type":"conference","abstract":[{"text":"Automated synthesis of approximate circuits via functional approximations is of prominent importance to provide efficiency in energy, runtime, and chip area required to execute an application. Approximate circuits are usually obtained either through analytical approximation methods leveraging approximate transformations such as bit-width scaling or via iterative search-based optimization methods when a library of approximate components, e.g., approximate adders and multipliers, is available. For the latter, exploring the extremely large design space is challenging in terms of both computations and quality of results. While the combination of both methods can create more room for further approximations, the \\textit{Design Space Exploration}~(DSE) becomes a crucial issue. In this paper, we present such a hybrid synthesis methodology that applies a low-cost analytical method followed by parallel stochastic search-based optimization. We address the DSE challenge through efficient pruning of the design space and skipping unnecessary expensive testing and/or verification steps. The experimental results reveal up to 10.57x area savings in comparison with both purely analytical or search-based approaches. ","lang":"eng"}],"status":"public"},{"title":"CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation","publisher":"Elsevier","date_created":"2018-07-20T14:08:49Z","year":"2019","keyword":["Approximate Computing","Framework","Pareto Front","Accuracy"],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Existing approaches and tools for the generation of approximate circuits often lack generality and are restricted to certain circuit types, approximation techniques, and quality assurance methods. Moreover, only few tools are publicly available. This hinders the development and evaluation of new techniques for approximating circuits and their comparison to previous approaches. In this paper, we first analyze and classify related approaches and then present CIRCA, our flexible framework for search-based approximate circuit generation. CIRCA is developed with a focus on modularity and extensibility. We present the architecture of CIRCA with its clear separation into stages and functional blocks, report on the current prototype, and show initial experiments."}],"publication":"Microelectronics Reliability","doi":"10.1016/j.microrel.2019.04.003","date_updated":"2022-01-06T06:59:25Z","volume":99,"author":[{"first_name":"Linus Matthias","last_name":"Witschen","id":"49051","full_name":"Witschen, Linus Matthias"},{"full_name":"Wiersema, Tobias","id":"3118","last_name":"Wiersema","first_name":"Tobias"},{"last_name":"Ghasemzadeh Mohammadi","id":"61186","full_name":"Ghasemzadeh Mohammadi, Hassan","first_name":"Hassan"},{"first_name":"Muhammad","last_name":"Awais","orcid":"https://orcid.org/0000-0003-4148-2969","id":"64665","full_name":"Awais, Muhammad"},{"full_name":"Platzner, Marco","id":"398","last_name":"Platzner","first_name":"Marco"}],"page":"277-290","intvolume":"        99","citation":{"ieee":"L. M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, and M. Platzner, “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation,” <i>Microelectronics Reliability</i>, vol. 99, pp. 277–290, 2019.","chicago":"Witschen, Linus Matthias, Tobias Wiersema, Hassan Ghasemzadeh Mohammadi, Muhammad Awais, and Marco Platzner. “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation.” <i>Microelectronics Reliability</i> 99 (2019): 277–90. <a href=\"https://doi.org/10.1016/j.microrel.2019.04.003\">https://doi.org/10.1016/j.microrel.2019.04.003</a>.","ama":"Witschen LM, Wiersema T, Ghasemzadeh Mohammadi H, Awais M, Platzner M. CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. <i>Microelectronics Reliability</i>. 2019;99:277-290. doi:<a href=\"https://doi.org/10.1016/j.microrel.2019.04.003\">10.1016/j.microrel.2019.04.003</a>","short":"L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, Microelectronics Reliability 99 (2019) 277–290.","bibtex":"@article{Witschen_Wiersema_Ghasemzadeh Mohammadi_Awais_Platzner_2019, title={CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation}, volume={99}, DOI={<a href=\"https://doi.org/10.1016/j.microrel.2019.04.003\">10.1016/j.microrel.2019.04.003</a>}, journal={Microelectronics Reliability}, publisher={Elsevier}, author={Witschen, Linus Matthias and Wiersema, Tobias and Ghasemzadeh Mohammadi, Hassan and Awais, Muhammad and Platzner, Marco}, year={2019}, pages={277–290} }","mla":"Witschen, Linus Matthias, et al. “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation.” <i>Microelectronics Reliability</i>, vol. 99, Elsevier, 2019, pp. 277–90, doi:<a href=\"https://doi.org/10.1016/j.microrel.2019.04.003\">10.1016/j.microrel.2019.04.003</a>.","apa":"Witschen, L. M., Wiersema, T., Ghasemzadeh Mohammadi, H., Awais, M., &#38; Platzner, M. (2019). CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. <i>Microelectronics Reliability</i>, <i>99</i>, 277–290. <a href=\"https://doi.org/10.1016/j.microrel.2019.04.003\">https://doi.org/10.1016/j.microrel.2019.04.003</a>"},"publication_identifier":{"issn":["0026-2714"]},"publication_status":"published","_id":"3585","project":[{"name":"SFB 901 - Subproject B4","_id":"12"},{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"department":[{"_id":"78"}],"user_id":"49051","status":"public","type":"journal_article"},{"title":"CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation","date_updated":"2022-01-06T06:59:26Z","author":[{"first_name":"Linus Matthias","full_name":"Witschen, Linus Matthias","id":"49051","last_name":"Witschen"},{"last_name":"Wiersema","full_name":"Wiersema, Tobias","id":"3118","first_name":"Tobias"},{"first_name":"Hassan","last_name":"Ghasemzadeh Mohammadi","full_name":"Ghasemzadeh Mohammadi, Hassan","id":"61186"},{"first_name":"Muhammad","orcid":"https://orcid.org/0000-0003-4148-2969","last_name":"Awais","full_name":"Awais, Muhammad","id":"64665"},{"first_name":"Marco","id":"398","full_name":"Platzner, Marco","last_name":"Platzner"}],"date_created":"2018-07-20T14:10:46Z","year":"2018","page":"6","citation":{"ama":"Witschen LM, Wiersema T, Ghasemzadeh Mohammadi H, Awais M, Platzner M. CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. <i>Third Workshop on Approximate Computing (AxC 2018)</i>.","ieee":"L. M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, and M. Platzner, “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation,” <i>Third Workshop on Approximate Computing (AxC 2018)</i>. .","chicago":"Witschen, Linus Matthias, Tobias Wiersema, Hassan Ghasemzadeh Mohammadi, Muhammad Awais, and Marco Platzner. “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation.” <i>Third Workshop on Approximate Computing (AxC 2018)</i>, n.d.","apa":"Witschen, L. M., Wiersema, T., Ghasemzadeh Mohammadi, H., Awais, M., &#38; Platzner, M. (n.d.). CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. <i>Third Workshop on Approximate Computing (AxC 2018)</i>.","short":"L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, Third Workshop on Approximate Computing (AxC 2018) (n.d.).","bibtex":"@article{Witschen_Wiersema_Ghasemzadeh Mohammadi_Awais_Platzner, title={CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation}, journal={Third Workshop on Approximate Computing (AxC 2018)}, author={Witschen, Linus Matthias and Wiersema, Tobias and Ghasemzadeh Mohammadi, Hassan and Awais, Muhammad and Platzner, Marco} }","mla":"Witschen, Linus Matthias, et al. “CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation.” <i>Third Workshop on Approximate Computing (AxC 2018)</i>."},"has_accepted_license":"1","publication_status":"accepted","keyword":["Approximate Computing","Framework","Pareto Front","Accuracy"],"ddc":["000"],"language":[{"iso":"eng"}],"file_date_updated":"2018-07-20T14:13:31Z","_id":"3586","project":[{"name":"SFB 901 - Subproject B4","_id":"12"},{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"department":[{"_id":"78"}],"user_id":"49051","abstract":[{"text":"Existing approaches and tools for the generation of approximate circuits often lack generality and are restricted to certain circuit types, approximation techniques, and quality assurance methods. Moreover, only few tools are publicly available. This hinders the development and evaluation of new techniques for approximating circuits and their comparison to previous approaches. In this paper, we first analyze and classify related approaches and then present CIRCA, our flexible framework for search-based approximate circuit generation. CIRCA is developed with a focus on modularity and extensibility. We present the architecture of CIRCA with its clear separation into stages and functional blocks, report on the current prototype, and show initial experiments.","lang":"eng"}],"status":"public","file":[{"creator":"tobias82","date_created":"2018-07-20T14:13:31Z","date_updated":"2018-07-20T14:13:31Z","access_level":"closed","file_name":"WitschenWMAP2018.pdf","file_id":"3587","file_size":285348,"content_type":"application/pdf","relation":"main_file","success":1}],"publication":"Third Workshop on Approximate Computing (AxC 2018)","type":"preprint"},{"title":"An MCTS-based Framework for Synthesis of Approximate Circuits","doi":"10.1109/VLSI-SoC.2018.8645026","date_updated":"2022-01-06T06:50:46Z","date_created":"2019-07-10T09:21:38Z","author":[{"full_name":"Awais, Muhammad","id":"64665","last_name":"Awais","orcid":"https://orcid.org/0000-0003-4148-2969","first_name":"Muhammad"},{"first_name":"Hassan","full_name":"Ghasemzadeh Mohammadi, Hassan","id":"61186","last_name":"Ghasemzadeh Mohammadi"},{"last_name":"Platzner","id":"398","full_name":"Platzner, Marco","first_name":"Marco"}],"year":"2018","page":"219-224","citation":{"short":"M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: 26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), 2018, pp. 219–224.","bibtex":"@inproceedings{Awais_Ghasemzadeh Mohammadi_Platzner_2018, title={An MCTS-based Framework for Synthesis of Approximate Circuits}, DOI={<a href=\"https://doi.org/10.1109/VLSI-SoC.2018.8645026\">10.1109/VLSI-SoC.2018.8645026</a>}, booktitle={26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)}, author={Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}, year={2018}, pages={219–224} }","mla":"Awais, Muhammad, et al. “An MCTS-Based Framework for Synthesis of Approximate Circuits.” <i>26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)</i>, 2018, pp. 219–24, doi:<a href=\"https://doi.org/10.1109/VLSI-SoC.2018.8645026\">10.1109/VLSI-SoC.2018.8645026</a>.","apa":"Awais, M., Ghasemzadeh Mohammadi, H., &#38; Platzner, M. (2018). An MCTS-based Framework for Synthesis of Approximate Circuits. In <i>26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)</i> (pp. 219–224). <a href=\"https://doi.org/10.1109/VLSI-SoC.2018.8645026\">https://doi.org/10.1109/VLSI-SoC.2018.8645026</a>","ama":"Awais M, Ghasemzadeh Mohammadi H, Platzner M. An MCTS-based Framework for Synthesis of Approximate Circuits. In: <i>26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)</i>. ; 2018:219-224. doi:<a href=\"https://doi.org/10.1109/VLSI-SoC.2018.8645026\">10.1109/VLSI-SoC.2018.8645026</a>","ieee":"M. Awais, H. Ghasemzadeh Mohammadi, and M. Platzner, “An MCTS-based Framework for Synthesis of Approximate Circuits,” in <i>26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)</i>, 2018, pp. 219–224.","chicago":"Awais, Muhammad, Hassan Ghasemzadeh Mohammadi, and Marco Platzner. “An MCTS-Based Framework for Synthesis of Approximate Circuits.” In <i>26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)</i>, 219–24, 2018. <a href=\"https://doi.org/10.1109/VLSI-SoC.2018.8645026\">https://doi.org/10.1109/VLSI-SoC.2018.8645026</a>."},"keyword":["Approximate computing","High-level synthesis","Accuracy","Monte-Carlo tree search","Circuit simulation"],"language":[{"iso":"eng"}],"_id":"10598","department":[{"_id":"78"}],"user_id":"64665","abstract":[{"text":"Approximate computing has become a very popular design\r\nstrategy that exploits error resilient computations to achieve higher\r\nperformance and energy efficiency. Automated synthesis of approximate\r\ncircuits is performed via functional approximation, in which various\r\nparts of the target circuit are extensively examined with a library\r\nof approximate components/transformations to trade off the functional\r\naccuracy and computational budget (i.e., power). However, as the number\r\nof possible approximate transformations increases, traditional search\r\ntechniques suffer from a combinatorial explosion due to the large\r\nbranching factor. In this work, we present a comprehensive framework\r\nfor automated synthesis of approximate circuits from either structural\r\nor behavioral descriptions. We adapt the Monte Carlo Tree Search\r\n(MCTS), as a stochastic search technique, to deal with the large design\r\nspace exploration, which enables a broader range of potential possible\r\napproximations through lightweight random simulations. The proposed\r\nframework is able to recognize the design Pareto set even with low\r\ncomputational budgets. Experimental results highlight the capabilities of\r\nthe proposed synthesis framework by resulting in up to 61.69% energy\r\nsaving while maintaining the predefined quality constraints.","lang":"eng"}],"status":"public","publication":"26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)","type":"conference"}]