# Harvard Architecture, Circuits and Compilers ## Harvard Architecture, Circuits, and Compilers Group Research on deep learning, infrastructures for heterogeneous systems, hardware specialization, and efficient power delivery [Harvard Architecture, Circuits, and Compilers Group chevron\_right](/research) ![Slide1](/sites/g/files/omnuum11281/files/styles/hwp_28_10__1920x685/public/vlsiarch/files/3u6a9736-1170x530.jpg?itok=h7F9r0NK) ## Welcome to the Harvard Architecture, Circuits, and Compilers Group! Our research focuses on computer architectures and systems that overcome fundamental limitations we now face due to the end of Moore’s Law at all layers of the hardware-software stack. Topics of active research include **deep learning, research infrastructures for heterogeneous systems, hardware specialization, and efficient power delivery.** Please explore our website to learn more about our projects and the people behind them. ## Recent Publications Download 2 citations download- [BibTeX](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=bibtex) - [EndNote X3 XML](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=endnote8) - [EndNote 7 XML](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=endnote7) - [Endnote tagged](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=tagged) - [Marc](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=marc) - [PubMedId](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=pubmed_id) - [RIS](/bibcite/export?pager_style=no_pager&number_of_items=2&sort_field=bibcite_year--desc&taxonomy_filters%5Bfield_hwp_c_peoplepublications%5D&taxonomy_filters%5Bfield_hwp_c_project123456%5D&&&format=ris) ### 2023 Matthew Adiletta, Jesmin Tithi, Emmanouil-Ioannis Farsarakis, Gerasimos Gerogiannis, Robert Adolf, Robert Benke, Sidharth Kashyap, Samuel Hsia, Kartik Lakhotia, Fabrizio Petrini, Gu-Yeon Wei, and David Brooks. 2023. “[Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA](/publications/characterizing-scalability-graph-convolutional-networks-intel%C2%AE-piuma)”. In IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). Raleigh, North Carolina Matthew Adiletta, Jesmin Tithi, Emmanouil-Ioannis Farsarakis, Gerasimos Gerogiannis, Robert Adolf, Robert Benke, Sidharth Kashyap, Samuel Hsia, Kartik Lakhotia, Fabrizio Petrini, Gu-Yeon Wei, and David Brooks. 2023. “[Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA](/publications/characterizing-scalability-graph-convolutional-networks-intel%C2%AE-piuma)”. In IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). Raleigh, North Carolina - add\_circle\_outline do\_not\_disturb\_on Abstract - [ picture\_as\_pdfispass\_gnn\_characterizati...](/sites/g/files/omnuum11281/files/vlsiarch/files/ispass_gnn_characterization_on_piuma_final.pdf) Large-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel's Programmable Integrated... - [ picture\_as\_pdfispass\_gnn\_characterizati...](/sites/g/files/omnuum11281/files/vlsiarch/files/ispass_gnn_characterization_on_piuma_final.pdf) Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, and Carole-Jean Wu. 2023. “[MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation](/publications/mp-rec-hardware-software-co-design-enable-multi-path-recommendation)”. In ASPLOS. Vancouver, Canada Samuel Hsia, Udit Gupta, Bilge Acun, Newsha Ardalani, Pan Zhong, Gu-Yeon Wei, David Brooks, and Carole-Jean Wu. 2023. “[MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation](/publications/mp-rec-hardware-software-co-design-enable-multi-path-recommendation)”. In ASPLOS. Vancouver, Canada - add\_circle\_outline do\_not\_disturb\_on Abstract - [ descriptionPublisher's Version](https://arxiv.org/abs/2302.10872) Deep learning recommendation systems serve personalized content under diverse tail-latency targets and input-query loads. In order to do so, state-of-the-art recommendation models rely on terabyte-scale embedding tables to learn user preferences over... - [ descriptionPublisher's Version](https://arxiv.org/abs/2302.10872) [ See all publications arrow\_circle\_right ](/publications) ## Recent News [### RecSSD accepted to ASLPOS 2021! ](/news/test-news-item-1) November 11, 2020 “RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference” has been accepted for presentation at the ASPLOS’21 conference. Congratulations to Mark and the other contributing authors! [### "Chasing Carbon" accepted to HPCA 2021! ](/news/test-news-item-2) October 28, 2020 Our recent work with Facebook AI, "Chasing Carbon: The Elusive Environmental Footprint of Computing," has been accepted to HPCA 2021 industry track. Congrats to all! [ See all news arrow\_circle\_right ](/news-events)