Discovering Programmer Intention Behind Written Source Code. - Gadiel Sznaier Camps; Nicolas Bohm Agostini; David R. Kaeli (ICMLA, 2019)

Exploiting Adaptive Data Compression to Improve Performance and Energy-Efficiency of Compute Workloads in Multi-GPU Systems. - Mohammad Khavari Tavana; Yifan Sun 002; Nicolas Bohm Agostini; David R. Kaeli (IPDPS, 2019)

Summarizing CPU and GPU Design Trends with Product Data. - Yifan Sun 002; Nicolas Bohm Agostini; Shi Dong 002; David R. Kaeli (CoRR, 2019)

Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC. - Nicolas Bohm Agostini; Shi Dong 002; Elmira Karimi; Marti Torrents Lapuerta; José Cano 001; José L. Abellán; David R. Kaeli (SBAC-PAD, 2020)

OpenCGRA: Democratizing Coarse-Grained Reconfigurable Arrays. - Cheng Tan 002; Nicolas Bohm Agostini; Jeff Zhang 001; Marco Minutoli; Vito Giovanni Castellana; Chenhao Xie 001; Tong Geng; Ang Li 006; Kevin J. Barker; Antonino Tumeo (ASAP, 2021)

Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis. - Jeff Jun Zhang; Nicolas Bohm Agostini; Shihao Song; Cheng Tan 002; Ankur Limaye; Vinay Amatya; Joseph B. Manzano; Marco Minutoli; Vito Giovanni Castellana; Antonino Tumeo; Gu-Yeon Wei; David Brooks 001 (ASAP, 2021)

A Secure and Reusable Software Architecture for Supporting Online Data Harmonization. - Zlatan Feric; Nicolas Bohm Agostini; Daniel Beene; Antonio J. Signes-Pastor; Yuliya Halchenko; Deborah Watkins; Debra MacKenzie; Margaret Karagas; Justin Manjourides; Akram Alshawabkeh; David R. Kaeli (IEEE BigData, 2021)

Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators. - Serena Curzel; Nicolas Bohm Agostini; Shihao Song; Ismet Dagli; Ankur Limaye; Cheng Tan 002; Marco Minutoli; Vito Giovanni Castellana; Vinay Amatya; Joseph B. Manzano; Anup Das 001; Fabrizio Ferrandi; et al. (ICCAD, 2021)

DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications. - Cheng Tan 002; Tong Geng; Chenhao Xie 001; Nicolas Bohm Agostini; Jiajia Li 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (ICCD, 2021)

SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. - Jude Haris; Perry Gibson; José Cano 001; Nicolas Bohm Agostini; David R. Kaeli (SBAC-PAD, 2021)

Performance Evaluation and Improvement of Real-Time Computer Vision Applications for Edge Computing Devices. - Julian Gutierrez 002; Nicolas Bohm Agostini; David R. Kaeli (ICPE (Companion), 2021)

Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs. - Shi Dong 002; Yifan Sun 002; Nicolas Bohm Agostini; Elmira Karimi; Daniel Lowell; Jing Zhou; José Cano 001; José L. Abellán; David R. Kaeli (IEEE Trans. Parallel Distributed Syst., 2021)

SODA-OPT an MLIR based flow for co-design and high-level synthesis. - Nicolas Bohm Agostini; Serena Curzel; David R. Kaeli; Antonino Tumeo (CF, 2022)

Hardware acceleration of complex machine learning models through modern high-level synthesis. - Serena Curzel; Nicolas Bohm Agostini; Antonino Tumeo; Fabrizio Ferrandi (CF, 2022)

The SODA approach: leveraging high-level synthesis for hardware/software co-design and hardware specialization: invited. - Nicolas Bohm Agostini; Serena Curzel; Ankur Limaye; Vinay Amatya; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; Antonino Tumeo; Fabrizio Ferrandi (DAC, 2022)

SO(DA)2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk). - Antonino Tumeo; Nicolas Bohm Agostini; Serena Curzel; Ankur Limaye; Cheng Tan 002; Vinay Amatya; Marco Minutoli; Vito Giovanni Castellana; Ang Li 006; Joseph B. Manzano (PARMA-DITAM@HiPEAC, 2022)

From High-Level Frameworks to custom Silicon with SODA. - Serena Curzel; Nicolas Bohm Agostini; Reece Neff; Ankur Limaye; Jeff Jun Zhang; Vinay Amatya; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; David Brooks 001; Gu-Yeon Wei; Fabrizio Ferrandi; et al. (HCS, 2022)

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs. - Cheng Tan 002; Nicolas Bohm Agostini; Tong Geng; Chenhao Xie 001; Jiajia Li 001; Ang Li 006; Kevin J. Barker; Antonino Tumeo (HPCA, 2022)

An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration. - Nicolas Bohm Agostini; Serena Curzel; Vinay Amatya; Cheng Tan 002; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; David R. Kaeli; Antonino Tumeo (ICCAD, 2022)

SODA Synthesizer: An Open-Source, Multi-Level, Modular, Extensible Compiler from High-Level Frameworks to Silicon. - Nicolas Bohm Agostini; Ankur Limaye; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; Antonino Tumeo; Serena Curzel; Fabrizio Ferrandi (ICCAD, 2022)

Bridging Python to Silicon: The SODA Toolchain. - Nicolas Bohm Agostini; Serena Curzel; Jeff Jun Zhang; Ankur Limaye; Cheng Tan 002; Vinay Amatya; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; David Brooks 001; Gu-Yeon Wei; Antonino Tumeo (IEEE Micro, 2022)

End-to-End Synthesis of Dynamically Controlled Machine Learning Accelerators. - Serena Curzel; Nicolas Bohm Agostini; Vito Giovanni Castellana; Marco Minutoli; Ankur Limaye; Joseph B. Manzano; Jeff Zhang 001; David Brooks 001; Gu-Yeon Wei; Fabrizio Ferrandi; Antonino Tumeo (IEEE Trans. Computers, 2022)

VCSR: An Efficient GPU Memory-Aware Sparse Format. - Elmira Karimi; Nicolas Bohm Agostini; Shi Dong 002; David R. Kaeli (IEEE Trans. Parallel Distributed Syst., 2022)

Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis. - Vito Giovanni Castellana; Nicolas Bohm Agostini; Ankur Limaye; Vinay Amatya; Marco Minutoli; Joseph B. Manzano; Antonino Tumeo; Serena Curzel; Michele Fiorito; Fabrizio Ferrandi (ASP-DAC, 2023)

ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs. - Yixuan Luo; Cheng Tan 002; Nicolas Bohm Agostini; Ang Li 006; Antonino Tumeo; Nirav Dave; Tong Geng (DAC, 2023)

SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference. - Jude Haris; Perry Gibson; José Cano 001; Nicolas Bohm Agostini; David R. Kaeli (J. Parallel Distributed Comput., 2023)

Towards Automated Generation of Chiplet-Based Systems Invited Paper. - Ankur Limaye; Claudio Barone; Nicolas Bohm Agostini; Marco Minutoli; Joseph B. Manzano; Vito Giovanni Castellana; Giovanni Gozzi; Michele Fiorito; Serena Curzel; Fabrizio Ferrandi; Antonino Tumeo (ASPDAC, 2024)

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. - Nicolas Bohm Agostini; Jude Haris; Perry Gibson; Malith Jayaweera; Norm Rubin; Antonino Tumeo; José L. Abellán; José Cano 001; David R. Kaeli (CGO, 2024)

Extending High-Level Synthesis with AI/ML Methods. - Nicolas Bohm Agostini; Giovanni Gozzi; Michele Fiorito; Claudio Barone; Serena Curzel; Ankur Limaye; Marco Minutoli; Vito Giovanni Castellana; Joseph B. Manzano; Fabrizio Ferrandi; Antonino Tumeo (ICCAD, 2024)

Computing with a Chemical Reservoir. - Connah G. M. Johnson; Nicolas Bohm Agostini; William R. Cannon; Antonino Tumeo (ICRC, 2024)

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator. - Kaustubh Shivdikar; Nicolas Bohm Agostini; Malith Jayaweera; Gilbert Jonatan; José L. Abellán; Ajay Joshi; John Kim 001; David R. Kaeli (ISCA, 2024)

Data Transfer Optimizations for Host-CPU and Accelerators in AXI4MLIR. - Jude Haris; Nicolas Bohm Agostini; Antonino Tumeo; David R. Kaeli; José Cano 001 (CoRR, 2024)

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks. - Nicolas Bohm Agostini; Connah Johnson; William R. Cannon; Antonino Tumeo (ASP-DAC, 2025)

A Synthesis Methodology for Intelligent Memory Interfaces in Accelerator Systems. - Ankur Limaye; Nicolas Bohm Agostini; Claudio Barone; Vito Giovanni Castellana; Michele Fiorito; Fabrizio Ferrandi; Andres Marquez 001; Antonino Tumeo (ASP-DAC, 2025)

The U.S. Microelectronics Research Programs and Where They Lower Barriers to Co-Design. Invited Paper. - James Alfred Ang; Antonino Tumeo; Nicolas Bohm Agostini; Ankur Limaye (CF (Companion), 2025)

ChemComp: Compiling and Computing with Chemical Reaction Networks. - Nicolas Bohm Agostini; Connah G. M. Johnson; William R. Cannon; Antonino Tumeo (DATE, 2025)

Online Learning for Dynamic Structural Characterization in Electron Energy Loss Spectroscopy. - M. Lakshmi Varshika; Jonathan Hollenbach; Nicolas Bohm Agostini; Ankur Limaye; Antonino Tumeo; Anup Das 001 (DATE, 2025)

UltraFormer: An Efficient Transformer for FPGAs. - Victor Agostinelli; Nicolas Bohm Agostini; Antonino Tumeo (FCCM, 2025)

ML4SODA: A Decision Tree Guided Design Space Exploration for Fast and High Quality MLIR-based HLS. - Darshith Manjunath; Nicolas Bohm Agostini; Antonino Tumeo; Jeff Zhang 001; Chaitali Chakrabarti (ACM Great Lakes Symposium on VLSI, 2025)

HEC: Equivalence Verification Checking for Code Transformation via Equality Saturation. - Jiaqi Yin; Zhan Song; Nicolas Bohm Agostini; Antonino Tumeo; Cunxi Yu (USENIX ATC, 2025)

Analyzing inference workloads for spatiotemporal modeling. - Milan Jain; Nicolas Bohm Agostini; Sayan Ghosh; Antonino Tumeo (Future Gener. Comput. Syst., 2025)