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De-specializing an HLS library for Deep Neural Networks: improvements upon hls4ml., , , and . CoRR, (2021)A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures., , , , , , , , , and 16 other author(s). CoRR, (2023)An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration., , , , , , , , and . ICCAD, page 6:1-6:9. ACM, (2022)SO(DA)2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk)., , , , , , , , , and . PARMA-DITAM@HiPEAC, volume 100 of OASIcs, page 1:1-1:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)TrueFloat: A Templatized Arithmetic Library for HLS Floating-Point Operators., , and . SAMOS, volume 14385 of Lecture Notes in Computer Science, page 486-493. Springer, (2023)Hardware acceleration of complex machine learning models through modern high-level synthesis., , , and . CF, page 209-210. ACM, (2022)Invited: Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications., , , , , , , , and . DAC, page 1327-1330. IEEE, (2021)A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach., , , , , , , , , and 21 other author(s). CoRR, (2024)MLIR Loop Optimizations for High-Level Synthesis: A Case Study., , , , and . PACT, page 544-545. ACM, (2022)From High-Level Frameworks to custom Silicon with SODA., , , , , , , , , and 3 other author(s). HCS, page 1-13. IEEE, (2022)