1:30 pm – 2:45 pm<\/td> | Session 4 – Applications\/ML<\/mark><\/strong> Chair: Mohamed Abdelfattah<\/td><\/tr><\/td> | ATHEENA: A Toolflow for Hardware Early-Exit Network Automation<\/strong> \u2605<\/mark> Benjamin Biggs, George A. Constantinides, and Christos-Savvas Bouganis (Imperial College London, UK)<\/td><\/tr><\/td> | Modular and Lean Architecture with Elasticity for Sparse Matrix Vector Multiplication on FPGAs<\/strong> Abhishek Kumar Jain, Chirag Ravishankar, Hossein Omidian, Sharan Kumar, Maithilee Kulkarni, Aashish Tripathi, and Dinesh Gaitonde (AMD)<\/td><\/tr><\/td> | HARFLOW3D: A latency-oriented 3D-CNN Accelerator Toolflow for HAR on FPGA Devices<\/strong> Petros Toupas (Imperial College London, Information Technologies Institute at CERTH); Alexander Montgomerie-Corcoran (Imperial College London); Dimitrios Tzovaras (Information Technologies Institute at CERTH); Christos-Savvas Bouganis (Imperial College London, UK)<\/td><\/tr><\/td> | Power2Picture: Using Generative CNNs for Input Recovery of Neural Network Accelerators through Power Side-Channels on FPGAs<\/strong> Lukas Huegle, Martin Gotthard, Vincent Meyers, Jonas Krautter, Dennis R. E. Gnad, and Mehdi B. Tahoori (Karlsruhe Institute of Technology (KIT))<\/td><\/tr>2:45 pm – 3:00 pm <\/td> | Break<\/span><\/td><\/tr>3:00 pm – 4:15 pm<\/td> | Session 5 – Applications<\/mark><\/strong> Chair: Gabriel Weisz<\/td><\/tr><\/td> | Computing and Compressing Electron Repulsion Integrals on FPGAs<\/strong> Xin Wu, Tobias Kenter, Robert Schade, Thomas D. K\u00fchne, and Christian Plessl (Paderborn University)<\/td><\/tr><\/td> | Tensor-Product-Based Accelerator for Area-efficient and Scalable Number Theoretic Transform<\/strong> Yuying ZHANG, Sathi Sarveswara Reddy, and Zili KOU (Hong Kong University of Science and Technology); Sharad Sinha (Indian Institute of Technology Goa); Wei ZHANG (Hong Kong University of Science and Technology)<\/td><\/tr><\/td> | SQL2FPGA: Automatic Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms<\/strong> Alec Lu and Zhenman Fang (Simon Fraser University)<\/td><\/tr><\/td> | DGNN-Booster: A Generic FPGA Accelerator Framework For Dynamic Graph Neural Network Inference<\/strong> (short paper) Hanqiu Chen and Cong Hao (Georgia Institute of Technology)<\/td><\/tr>4:15 pm – 4:30 pm<\/td> | Closing and Award Ceremony <\/span><\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" FCCM 2023 Preliminary Program *All times shown in the Pacific Time Zone (UTC-8) Monday (May 8) and Thursday (May 11): Workshops and Tutorials Tuesday – May 9 \u2605 indicates best paper candidate Open Research Objects (ORO) Research Objects Reviewed (ROR) Results Reproduced (ROR-R) 8:00 am – 8:45 am Light Breakfast and Registration 8:45 am – … <\/p>\n Continue reading “Program 2023”<\/span><\/a><\/p>\n","protected":false},"author":579,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"_links":{"self":[{"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/pages\/2477"}],"collection":[{"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/users\/579"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/comments?post=2477"}],"version-history":[{"count":10,"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/pages\/2477\/revisions"}],"predecessor-version":[{"id":3203,"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/pages\/2477\/revisions\/3203"}],"wp:attachment":[{"href":"https:\/\/www.wp.fccm.org\/wp-json\/wp\/v2\/media?parent=2477"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} | | | | | | | | | | | |