Search Results - "Agostini, Nicolas Bohm" :: K.UTB vyhledávací portál | TBU Library Retrieval Portal

End-to-End Synthesis of Dynamically Controlled Machine Learning Accelerators

End-to-End Synthesis of Dynamically Controlled Machine Learning Accelerators

by Curzel, Serena, Agostini, Nicolas Bohm, Castellana, Vito Giovanni, Minutoli, Marco, Limaye, Ankur, Manzano, Joseph, Zhang, Jeff, Brooks, David, Wei, Gu-Yeon, Ferrandi, Fabrizio, Tumeo, Antonino
Published in IEEE transactions on computers (01.12.2022)

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Journal Article

Bridging Python to Silicon: The SODA Toolchain

Bridging Python to Silicon: The SODA Toolchain

by Agostini, Nicolas Bohm, Curzel, Serena, Zhang, Jeff Jun, Limaye, Ankur, Tan, Cheng, Amatya, Vinay, Minutoli, Marco, Castellana, Vito Giovanni, Manzano, Joseph, Brooks, David, Wei, Gu-Yeon, Tumeo, Antonino
Published in IEEE MICRO (01.09.2022)

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Journal Article

VCSR: An Efficient GPU Memory-Aware Sparse Format

VCSR: An Efficient GPU Memory-Aware Sparse Format

by Karimi, Elmira, Agostini, Nicolas Bohm, Dong, Shi, Kaeli, David
Published in IEEE transactions on parallel and distributed systems (01.12.2022)

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Journal Article

SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference

SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference

by Haris, Jude, Gibson, Perry, Cano, José, Bohm Agostini, Nicolas, Kaeli, David
Published in Journal of parallel and distributed computing (01.03.2023)

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Journal Article

Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs

Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs

by Dong, Shi, Sun, Yifan, Agostini, Nicolas Bohm, Karimi, Elmira, Lowell, Daniel, Zhou, Jing, Cano, Jose, Abellan, Jose L., Kaeli, David
Published in IEEE transactions on parallel and distributed systems (01.10.2021)

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Journal Article

ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs

ML-CGRA: An Integrated Compilation Framework to Enable Efficient Machine Learning Acceleration on CGRAs

by Luo, Yixuan, Tan, Cheng, Agostini, Nicolas Bohm, Li, Ang, Tumeo, Antonino, Dave, Nirav, Geng, Tong
Published in 2023 60th ACM/IEEE Design Automation Conference (DAC) (09.07.2023)

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Conference Proceeding

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

by Agostini, Nicolas Bohm, Haris, Jude, Gibson, Perry, Jayaweera, Malith, Rubin, Norm, Tumeo, Antonino, Abellan, Jose L., Cano, Jose, Kaeli, David
Published in 2024 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) (02.03.2024)

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Conference Proceeding

Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC

Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC

by Bohm Agostini, Nicolas, Dong, Shi, Karimi, Elmira, Torrents Lapuerta, Marti, Cano, Jose, Abellan, Jose L., Kaeli, David
Published in 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) (01.09.2020)

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Conference Proceeding

Towards Automated Generation of Chiplet-Based Systems Invited Paper

Towards Automated Generation of Chiplet-Based Systems Invited Paper

by Limaye, Ankur, Barone, Claudio, Agostini, Nicolas Bohm, Minutoli, Marco, Manzano, Joseph, Castellana, Vito Giovanni, Gozzi, Giovanni, Fiorito, Michele, Curzel, Serena, Ferrandi, Fabrizio, Tumeo, Antonino
Published in 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC) (22.01.2024)

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Conference Proceeding

Exploiting Adaptive Data Compression to Improve Performance and Energy-Efficiency of Compute Workloads in Multi-GPU Systems

Exploiting Adaptive Data Compression to Improve Performance and Energy-Efficiency of Compute Workloads in Multi-GPU Systems

by Khavari Tavana, Mohammad, Sun, Yifan, Bohm Agostini, Nicolas, Kaeli, David
Published in 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (01.05.2019)

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Conference Proceeding

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

by Nicolas Bohm Agostini, Haris, Jude, Gibson, Perry, Jayaweera, Malith, Rubin, Norm, Tumeo, Antonino, Abellán, José L, Cano, José, Kaeli, David
Published in arXiv.org (22.12.2023)

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Paper Journal Article

Analyzing inference workloads for spatiotemporal modeling

Analyzing inference workloads for spatiotemporal modeling

by Jain, Milan, Agostini, Nicolas Bohm, Ghosh, Sayan, Tumeo, Antonino
Published in Future generation computer systems (01.02.2025)

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Journal Article

Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis

Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis

by Zhang, Jeff Jun, Bohm Agostini, Nicolas, Song, Shihao, Tan, Cheng, Limaye, Ankur, Amatya, Vinay, Manzano, Joseph, Minutoli, Marco, Castellana, Vito Giovanni, Tumeo, Antonino, Wei, Gu-Yeon, Brooks, David
Published in 2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP) (01.07.2021)

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Conference Proceeding

A Secure and Reusable Software Architecture for Supporting Online Data Harmonization

A Secure and Reusable Software Architecture for Supporting Online Data Harmonization

by Feric, Zlatan, Agostini, Nicolas Bohm, Beene, Daniel, Signes-Pastor, Antonio J., Halchenko, Yuliya, Watkins, Deborah, MacKenzie, Debra, Karagas, Margaret, Manjourides, Justin, Alshawabkeh, Akram, Kaeli, David
Published in 2021 IEEE International Conference on Big Data (Big Data) (01.12.2021)

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Conference Proceeding Journal Article

SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference

SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference

by Haris, Jude, Gibson, Perry, Cano, Jose, Agostini, Nicolas Bohm, Kaeli, David
Published in 2021 IEEE 33rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) (01.10.2021)

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Conference Proceeding

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator

by Shivdikar, Kaustubh, Agostini, Nicolas Bohm, Jayaweera, Malith, Jonatan, Gilbert, Abellan, Jose L., Joshi, Ajay, Kim, John, Kaeli, David
Published in 2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) (29.06.2024)

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Conference Proceeding

An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration

An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration

by Agostini, Nicolas Bohm, Curzel, Serena, Amatya, Vinay, Tan, Cheng, Minutoli, Marco, Castellana, Vito Giovanni, Manzano, Joseph, Kaeli, David, Tumeo, Antonino
Published in 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD) (29.10.2022)

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Conference Proceeding

SODA Synthesizer: an Open-source, Multi-level, Modular, Extensible Compiler from High-level Frameworks to Silicon

SODA Synthesizer: an Open-source, Multi-level, Modular, Extensible Compiler from High-level Frameworks to Silicon

by Agostini, Nicolas Bohm, Limaye, Ankur, Minutoli, Marco, Castellana, Vito Giovanni, Manzano, Joseph, Tumeo, Antonino, Curzel, Serena
Published in 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD) (29.10.2022)

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Conference Proceeding

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

DRIPS: Dynamic Rebalancing of Pipelined Streaming Applications on CGRAs

by Tan, Cheng, Agostini, Nicolas Bohm, Geng, Tong, Xie, Chenhao, Li, Jiajia, Li, Ang, Barker, Kevin J., Tumeo, Antonino
Published in 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA) (01.04.2022)

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Conference Proceeding

DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications

DynPaC: Coarse-Grained, Dynamic, and Partially Reconfigurable Array for Streaming Applications

by Tan, Cheng, Geng, Tong, Xie, Chenhao, Agostini, Nicolas Bohm, Li, Jiajia, Li, Ang, Barker, Kevin, Tumeo, Antonino
Published in 2021 IEEE 39th International Conference on Computer Design (ICCD) (01.10.2021)

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Conference Proceeding