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ORCIDNicolas Bohm Agostini
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2020 – today
- 2025
[j6]Milan Jain
, Nicolas Bohm Agostini, Sayan Ghosh, Antonino Tumeo:
Analyzing inference workloads for spatiotemporal modeling. Future Gener. Comput. Syst. 163: 107513 (2025)- 2024
- [c23]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: 771-776 - [c22]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: 143-157 - [c21]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: 946-960 - [i5]Jude Haris, Nicolas Bohm Agostini, Antonino Tumeo, David R. Kaeli, José Cano:
Data Transfer Optimizations for Host-CPU and Accelerators in AXI4MLIR. CoRR abs/2402.19184 (2024) - [i4]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 abs/2404.15510 (2024) - 2023
- [j5]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: 140-151 (2023) - [c20]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: 632-638 - [c19]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: 1-6 - [i3]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 abs/2312.14821 (2023) - 2022
- [j4]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): 78-88 (2022) - [j3]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): 3074-3087 (2022) - [j2]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): 3977-3989 (2022) - [c18]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: 201-202 - [c17]Serena Curzel, Nicolas Bohm Agostini, Antonino Tumeo, Fabrizio Ferrandi:
Hardware acceleration of complex machine learning models through modern high-level synthesis. CF 2022: 209-210 - [c16]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: 1359-1362 - [c15]Antonino Tumeo, Nicolas Bohm Agostini, Serena Curzel, Ankur Limaye, Cheng Tan, Vinay Amatya, Marco Minutoli, Vito Giovanni Castellana, Ang Li, Joseph B. Manzano:
SO(DA)2: End-to-end Generation of Specialized Reconfigurable Architectures (Invited Talk). PARMA-DITAM@HiPEAC 2022: 1:1-1:15 - [c14]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: 1-13 - [c13]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: 304-316 - [c12]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: 6:1-6:9 - [c11]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: 18:1-18:7 - 2021
- [j1]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): 2448-2463 (2021) - [c10]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: 149-155 - [c9]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: 218-225 - [c8]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: 2801-2812 - [c7]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: 1-7 - [c6]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: 33-40 - [c5]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: 33-43 - [c4]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: 139-144 - [i2]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 abs/2110.00478 (2021) - 2020
- [c3]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: 10-19
2010 – 2019
- 2019
- [c2]Gadiel Sznaier Camps, Nicolas Bohm Agostini, David R. Kaeli:
Discovering Programmer Intention Behind Written Source Code. ICMLA 2019: 432-437 - [c1]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: 664-674 - [i1]Yifan Sun, Nicolas Bohm Agostini, Shi Dong, David R. Kaeli:
Summarizing CPU and GPU Design Trends with Product Data. CoRR abs/1911.11313 (2019)
Coauthor Index
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