Nicolas Bohm Agostini

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 33

Top Topics

Gallium Arsenide

Code Generation

Design Space Exploration

Top Venues

Publications

Jude Haris, Nicolas Bohm Agostini, Antonino Tumeo, David R. Kaeli, José Cano
Data Transfer Optimizations for Host-CPU and Accelerators in AXI4MLIR. CoRR (2024)
Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera, Gilbert Jonatan, José L. Abellán, Ajay Joshi, John Kim, David R. Kaeli
NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator. CoRR (2024)
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
Towards Automated Generation of Chiplet-Based Systems Invited Paper. ASPDAC (2024)
Nicolas Bohm Agostini, Jude Haris, Perry Gibson, Malith Jayaweera, Norm Rubin, Antonino Tumeo, José L. Abellán, José Cano, David R. Kaeli
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. CGO (2024)
Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera, Gilbert Jonatan, José L. Abellán, Ajay Joshi, John Kim, David R. Kaeli
NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator. ISCA (2024)
Nicolas Bohm Agostini, Jude Haris, Perry Gibson, Malith Jayaweera, Norm Rubin, Antonino Tumeo, José L. Abellán, José Cano, David R. Kaeli
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. CoRR (2023)
Vito Giovanni Castellana, Nicolas Bohm Agostini, Ankur Limaye, Vinay Amatya, Marco Minutoli, Joseph B. Manzano, Antonino Tumeo, Serena Curzel, Michele Fiorito, Fabrizio Ferrandi
Towards On-Chip Learning for Low Latency Reasoning with End-to-End Synthesis. ASP-DAC (2023)
Jude Haris, Perry Gibson, José Cano, Nicolas Bohm Agostini, David R. Kaeli
SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference. J. Parallel Distributed Comput. 173 (2023)
Yixuan Luo, Cheng Tan, Nicolas Bohm Agostini, Ang Li, Antonino Tumeo, Nirav Dave, Tong Geng
ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs. DAC (2023)
Nicolas Bohm Agostini, Serena Curzel, Ankur Limaye, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, Antonino Tumeo, Fabrizio Ferrandi
The SODA approach: leveraging high-level synthesis for hardware/software co-design and hardware specialization: invited. DAC (2022)
Antonino Tumeo, Nicolas Bohm Agostini, Serena Curzel, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Ang Li, Joseph B. Manzano
: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk). PARMA-DITAM@HiPEAC (2022)
Serena Curzel, Nicolas Bohm Agostini, Reece Neff, Ankur Limaye, Jeff Jun Zhang, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, David Brooks, Gu-Yeon Wei, Fabrizio Ferrandi, Antonino Tumeo
From High-Level Frameworks to custom Silicon with SODA. HCS (2022)
Nicolas Bohm Agostini, Serena Curzel, Vinay Amatya, Cheng Tan, Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, David R. Kaeli, Antonino Tumeo
An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration. ICCAD (2022)
Nicolas Bohm Agostini, Serena Curzel, Jeff Jun Zhang, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, David Brooks, Gu-Yeon Wei, Antonino Tumeo
Bridging Python to Silicon: The SODA Toolchain. IEEE Micro 42 (5) (2022)
Nicolas Bohm Agostini, Ankur Limaye, Marco Minutoli, Vito Giovanni Castellana, Joseph B. Manzano, Antonino Tumeo, Serena Curzel, Fabrizio Ferrandi
SODA Synthesizer: An Open-Source, Multi-Level, Modular, Extensible Compiler from High-Level Frameworks to Silicon. ICCAD (2022)
Serena Curzel, Nicolas Bohm Agostini, Vito Giovanni Castellana, Marco Minutoli, Ankur Limaye, Joseph B. Manzano, Jeff Zhang, David Brooks, Gu-Yeon Wei, Fabrizio Ferrandi, Antonino Tumeo
End-to-End Synthesis of Dynamically Controlled Machine Learning Accelerators. IEEE Trans. Computers 71 (12) (2022)
Nicolas Bohm Agostini, Serena Curzel, David R. Kaeli, Antonino Tumeo
SODA-OPT an MLIR based flow for co-design and high-level synthesis. CF (2022)
Cheng Tan, Nicolas Bohm Agostini, Tong Geng, Chenhao Xie, Jiajia Li, Ang Li, Kevin J. Barker, Antonino Tumeo
DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs. HPCA (2022)
Serena Curzel, Nicolas Bohm Agostini, Antonino Tumeo, Fabrizio Ferrandi
Hardware acceleration of complex machine learning models through modern high-level synthesis. CF (2022)
Elmira Karimi, Nicolas Bohm Agostini, Shi Dong, David R. Kaeli
VCSR: An Efficient GPU Memory-Aware Sparse Format. IEEE Trans. Parallel Distributed Syst. 33 (10) (2022)
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
A Secure and Reusable Software Architecture for Supporting Online Data Harmonization. IEEE BigData (2021)
Jude Haris, Perry Gibson, José Cano, Nicolas Bohm Agostini, David R. Kaeli
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. CoRR (2021)
Jeff Jun Zhang, Nicolas Bohm Agostini, Shihao Song, Cheng Tan, Ankur Limaye, Vinay Amatya, Joseph B. Manzano, Marco Minutoli, Vito Giovanni Castellana, Antonino Tumeo, Gu-Yeon Wei, David Brooks
Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis. ASAP (2021)
Serena Curzel, Nicolas Bohm Agostini, Shihao Song, Ismet Dagli, Ankur Limaye, Cheng Tan, Marco Minutoli, Vito Giovanni Castellana, Vinay Amatya, Joseph B. Manzano, Anup Das, Fabrizio Ferrandi, Antonino Tumeo
Automated Generation of Integrated Digital and Spiking Neuromorphic Machine Learning Accelerators. ICCAD (2021)
Cheng Tan, Nicolas Bohm Agostini, Jeff Zhang, Marco Minutoli, Vito Giovanni Castellana, Chenhao Xie, Tong Geng, Ang Li, Kevin J. Barker, Antonino Tumeo
OpenCGRA: Democratizing Coarse-Grained Reconfigurable Arrays. ASAP (2021)
Cheng Tan, Tong Geng, Chenhao Xie, Nicolas Bohm Agostini, Jiajia Li, Ang Li, Kevin J. Barker, Antonino Tumeo
DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications. ICCD (2021)
Julian Gutierrez, Nicolas Bohm Agostini, David R. Kaeli
Performance Evaluation and Improvement of Real-Time Computer Vision Applications for Edge Computing Devices. ICPE (Companion) (2021)
Shi Dong, Yifan Sun, Nicolas Bohm Agostini, Elmira Karimi, Daniel Lowell, Jing Zhou, José Cano, José L. Abellán, David R. Kaeli
Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs. IEEE Trans. Parallel Distributed Syst. 32 (10) (2021)
Jude Haris, Perry Gibson, José Cano, Nicolas Bohm Agostini, David R. Kaeli
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. SBAC-PAD (2021)
Nicolas Bohm Agostini, Shi Dong, Elmira Karimi, Marti Torrents Lapuerta, José Cano, José L. Abellán, David R. Kaeli
Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC. SBAC-PAD (2020)
Mohammad Khavari Tavana, Yifan Sun, Nicolas Bohm Agostini, David R. Kaeli
Exploiting Adaptive Data Compression to Improve Performance and Energy-Efficiency of Compute Workloads in Multi-GPU Systems. IPDPS (2019)
Gadiel Sznaier Camps, Nicolas Bohm Agostini, David R. Kaeli
Discovering Programmer Intention Behind Written Source Code. ICMLA (2019)
Yifan Sun, Nicolas Bohm Agostini, Shi Dong, David R. Kaeli
Summarizing CPU and GPU Design Trends with Product Data. CoRR (2019)