{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T15:32:48Z","timestamp":1780673568353,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":82,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T00:00:00Z","timestamp":1730678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["101071179"],"award-info":[{"award-number":["101071179"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,11,4]]},"DOI":"10.1145\/3666025.3699335","type":"proceedings-article","created":{"date-parts":[[2024,11,4]],"date-time":"2024-11-04T18:48:26Z","timestamp":1730746106000},"page":"239-252","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Fast-Inf: Ultra-Fast Embedded Intelligence on the Batteryless Edge"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1652-1690","authenticated-orcid":false,"given":"Leonardo Lucio","family":"Custode","sequence":"first","affiliation":[{"name":"University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7493-6539","authenticated-orcid":false,"given":"Pietro","family":"Farina","sequence":"additional","affiliation":[{"name":"University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4631-7834","authenticated-orcid":false,"given":"Eren","family":"Yildiz","sequence":"additional","affiliation":[{"name":"Ege University, Izmir, Turkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2421-7624","authenticated-orcid":false,"given":"Renan Beran","family":"Kilic","sequence":"additional","affiliation":[{"name":"University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9528-6923","authenticated-orcid":false,"given":"Kasim Sinan","family":"Yildirim","sequence":"additional","affiliation":[{"name":"University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9723-1830","authenticated-orcid":false,"given":"Giovanni","family":"Iacca","sequence":"additional","affiliation":[{"name":"University of Trento, Trento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,11,4]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/IPSN.2018.00047"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430722"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3624718"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3550304"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3560905.3568561"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3508396.3512870"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3478077"},{"key":"e_1_3_2_1_8_1","unstructured":"Peter Belcak and Roger Wattenhofer. 2023. Fast Feedforward Networks. arXiv preprint arXiv:2308.14711."},{"key":"e_1_3_2_1_9_1","unstructured":"Emmanuel Bengio Pierre-Luc Bacon Joelle Pineau and Doina Precup. 2015. Conditional computation in neural networks for faster models. arXiv preprint arXiv:1511.06297."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2994551.2994564"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3055031.3055082"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3594738.3611369"},{"key":"e_1_3_2_1_13_1","volume-title":"Classification and regression trees","author":"Breiman Leo","unstructured":"Leo Breiman. 2017. Classification and regression trees. Routledge, London, UK."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3486618"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3608475"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3370748.3406588"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2022.3142525"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/RTAS54340.2022.00012"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/2983990.2983995"},{"key":"e_1_3_2_1_20_1","unstructured":"Elia Cunegatti Doina Bucur and Giovanni Iacca. 2023. Peeking inside Sparse Neural Networks using Multi-Partite Graph Representations. arXiv preprint arXiv:2305.16886."},{"key":"e_1_3_2_1_21_1","volume-title":"Kasim Sinan Yildirim, and Giovanni Iacca.","author":"Custode Leonardo Lucio","year":"2024","unstructured":"Leonardo Lucio Custode, Pietro Farina, Eren Yildiz, Renan Beran Kilic, Kasim Sinan Yildirim, and Giovanni Iacca. 2024. Github Repo. https:\/\/github.com\/DIOL-UniTN\/Fast-Inf-FFF."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3520304.3528897"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411839"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3510850"},{"key":"e_1_3_2_1_26_1","unstructured":"Digilent. [n. d.]. Analog Discovery 2 (Legacy). https:\/\/digilent.com\/reference\/test-and-measurement\/analog-discovery-2\/start"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3563216"},{"key":"e_1_3_2_1_28_1","unstructured":"Pietro Farina Subrata Biswas Eren Yildiz Khakim Akhunov Saad Ahmed Bashima Islam and Kasim Sinan Yildirim. 2024. Memory-efficient Energy-adaptive Inference of Pre-Trained Models on Batteryless Embedded Systems. arXiv preprint arXiv:2405.10426."},{"key":"e_1_3_2_1_29_1","volume-title":"International Conference on Machine Learning. PMLR","author":"Frankle Jonathan","year":"2020","unstructured":"Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, and Michael Carbin. 2020. Linear mode connectivity and the lottery ticket hypothesis. In International Conference on Machine Learning. PMLR, Vienna, Austria, 3259--3269."},{"key":"e_1_3_2_1_30_1","unstructured":"Nicholas Frosst and Geoffrey Hinton. 2017. Distilling a Neural Network Into a Soft Decision Tree. arXiv preprint arXiv:1711.09784."},{"key":"e_1_3_2_1_31_1","volume-title":"Low-Power Computer Vision","author":"Gholami Amir","unstructured":"Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W Mahoney, and Kurt Keutzer. 2022. A survey of quantization methods for efficient neural network inference. In Low-Power Computer Vision. Chapman and Hall\/CRC, Boca Raton, FL, USA, 291--326."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3297858.3304011"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/MS.2022.3184519"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314221.3314597"},{"key":"e_1_3_2_1_35_1","unstructured":"Song Han Huizi Mao and William J Dally. 2015. Deep compression: Compressing deep neural networks with pruning trained quantization and Huffman coding. arXiv preprint arXiv:1510.00149."},{"key":"e_1_3_2_1_36_1","first-page":"9","article-title":"Learning both weights and connections for efficient neural network","volume":"28","author":"Han Song","year":"2015","unstructured":"Song Han, Jeff Pool, John Tran, and William Dally. 2015. Learning both weights and connections for efficient neural network. Advances in Neural Information Processing Systems 28 (2015), 9.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3131672.3131674"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3131672.3131673"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Andrey Ignatov. 2017. Real-time human activity recognition from accelerometer data using Convolutional Neural Networks. https:\/\/github.com\/aiff22\/HAR","DOI":"10.1016\/j.asoc.2017.09.027"},{"key":"e_1_3_2_1_40_1","unstructured":"Texas Instruments Inc. 2017. MSP430FR59xx Mixed-Signal Microcontrollers (Rev. F). https:\/\/www.ti.com\/lit\/ds\/symlink\/msp430fr5969.pdf"},{"key":"e_1_3_2_1_41_1","unstructured":"Texas Instruments Inc. 2019. EnergyTrace User Guide. https:\/\/software-dl.ti.com\/simplelink\/esd\/simplelink_cc13x2_26x2_sdk\/4.10.00.78\/exports\/docs\/ble5stack\/ble_user_guide\/html\/energy-trace\/energy-trace.html"},{"key":"e_1_3_2_1_42_1","unstructured":"Texas Instruments Inc. 2020. FRAM FAQs. https:\/\/www.ti.com\/lit\/wp\/slat151\/slat151.pdf"},{"key":"e_1_3_2_1_43_1","unstructured":"Infineon. 2020. 8MB EXCELON LP Ferroelectric RAM. https:\/\/www.infineon.com\/dgdl\/Infineon-CY15B108QN_CY15V108QN_Excelon(TM)_LP_8-Mbit_(1024K_X_8)_Serial_(SPI)_F-RAM-DataSheet-v10_00-EN.pdf?fileId=8ac78c8c7d0d8da4017d0ee7134b6ff4"},{"key":"e_1_3_2_1_44_1","unstructured":"Texas Instruments. 2016. Low-Energy Accelerator (LEA) Frequently Asked Questions (FAQ). https:\/\/www.ti.com\/lit\/an\/slaa720\/slaa720.pdf"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411808"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581791.3596845"},{"key":"e_1_3_2_1_47_1","unstructured":"Jeff Johnson. 2018. Rethinking floating point for deep learning. arXiv preprint arXiv:1811.01721."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3613304"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.3012217"},{"key":"e_1_3_2_1_50_1","unstructured":"Yong-Deok Kim Eunhyeok Park Sungjoo Yoo Taelim Choi Lu Yang and Dongjun Shin. 2015. Compression of deep convolutional neural networks for fast and low power mobile applications. arXiv preprint arXiv:1511.06530."},{"key":"e_1_3_2_1_51_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2017","unstructured":"Diederik P. Kingma and Jimmy Ba. 2017. Adam: A Method for Stochastic Optimization. arXiv preprint arXiv:1412.6980."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3373376.3378476"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3356250.3360030"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3386901.3388947"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom53586.2022.9762400"},{"key":"e_1_3_2_1_56_1","first-page":"11711","article-title":"MCUNet: Tiny Deep Learning on IoT Devices","volume":"33","author":"Lin Ji","year":"2020","unstructured":"Ji Lin, Wei-Ming Chen, Yujun Lin, Chuang Gan, Song Han, et al. 2020. MCUNet: Tiny Deep Learning on IoT Devices. Advances in Neural Information Processing Systems 33 (2020), 11711--11722.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_57_1","unstructured":"Zhuang Liu Mingjie Sun Tinghui Zhou Gao Huang and Trevor Darrell. 2018. Rethinking the value of network pruning. arXiv preprint arXiv:1810.05270."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133920"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3360285"},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581791.3596859"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1145\/3384419.3430782"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107385"},{"key":"e_1_3_2_1_63_1","unstructured":"Powercast. 2016. The Powercast P2110B Powerharvester. https:\/\/www.powercastco.com\/wp-content\/uploads\/2016\/12\/P2110B-Datasheet-Rev-3.pdf"},{"key":"e_1_3_2_1_64_1","unstructured":"Powercast. 2018. The Powercast TX91501B Powercaster. https:\/\/www.powercastco.com\/wp-content\/uploads\/2019\/10\/User-Manual-TX-915-01B-Rev-A-1.pdf"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3608473"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107281"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/2618128.2618136"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_32"},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3064066"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3613424.3614283"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3495243.3558265"},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1145\/3495243.3558264"},{"key":"e_1_3_2_1_73_1","unstructured":"Cheng Tai Tong Xiao Yi Zhang Xiaogang Wang et al. 2015. Convolutional neural networks with low-rank regularization. arXiv preprint arXiv:1511.06067."},{"key":"e_1_3_2_1_74_1","unstructured":"Pete Warden. 2018. Speech commands: A dataset for limited-vocabulary speech recognition. arXiv preprint arXiv:1804.03209."},{"key":"e_1_3_2_1_75_1","volume-title":"TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers","author":"Warden Pete","unstructured":"Pete Warden and Daniel Situnayake. 2019. TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers. O'Reilly Media, Sebastopol, CA, USA."},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/3620666.3651370"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485730.3485947"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.061"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1145\/3274783.3274837"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1145\/3552326.3587435"},{"key":"e_1_3_2_1_81_1","volume-title":"Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation. USENIX Association","author":"Yildiz Eren","year":"2022","unstructured":"Eren Yildiz, Lijun Chen, and Kasim Sinan Yildirim. 2022. Immortal Threads: Multithreaded Event-driven Intermittent Computing on {Ultra-Low-Power} Microcontrollers. In Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation. USENIX Association, Berkeley, CA, USA, 339--355."},{"key":"e_1_3_2_1_82_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2918951"}],"event":{"name":"SenSys '24: 22nd ACM Conference on Embedded Networked Sensor Systems","location":"Hangzhou China","acronym":"SenSys '24","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","SIGBED ACM Special Interest Group on Embedded Systems","SIGMETRICS ACM Special Interest Group on Measurement and Evaluation","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3666025.3699335","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3666025.3699335","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T22:53:47Z","timestamp":1750287227000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3666025.3699335"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,4]]},"references-count":82,"alternative-id":["10.1145\/3666025.3699335","10.1145\/3666025"],"URL":"https:\/\/doi.org\/10.1145\/3666025.3699335","relation":{},"subject":[],"published":{"date-parts":[[2024,11,4]]},"assertion":[{"value":"2024-11-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}