DOSA: Organic Compilation for Neural Network Inference on Distributed FPGAs
Ringlein B, Abel F, Diamantopoulos D, Weiss B, Hagleitner C, Fey D (2023)
Publication Type: Conference contribution
Publication year: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2023-July
Pages Range: 43-50
Conference Proceedings Title: Proceedings - IEEE International Conference on Edge Computing
Event location: Hybrid, Chicago, IL, USA
ISBN: 9798350304831
DOI: 10.1109/EDGE60047.2023.00019
Abstract
The computational requirements of artificial intelligence workloads are growing exponentially. In addition, more and more compute is moved towards the edge due to latency or localization constraints. At the same time, Dennard scaling has ended and Moore's law is winding down. These trends created an opportunity for specialized accelerators including field-programmable gate arrays (FPGAs), but the poor support and usability of today's tools prevents FPGAs from being deployed at scale for deep neural network (DNN) inference applications. In this work, we propose an organic compiler - DOSA - that drastically lowers the barrier for deploying FPGAs. DOSA builds on the operation set architecture concept and integrates the DNN accelerator components generated by existing DNN-to-FPGA frameworks to produce an overall efficient solution. DOSA starts from DNNs represented in the community standard ONNX and automatically implements model- and data-parallelism, based on the performance targets and resource footprints provided by the user. Deploying a DNN using DOSA on 9 FPGAs exhibits a speedup of up to 52 times compared to a CPU and 18 times compared to a GPU.
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Switzerland (CH)How to cite
APA:
Ringlein, B., Abel, F., Diamantopoulos, D., Weiss, B., Hagleitner, C., & Fey, D. (2023). DOSA: Organic Compilation for Neural Network Inference on Distributed FPGAs. In Claudio Ardagna, Feras Awaysheh, Hongyi Bian, Carl K. Chang, Rong N. Chang, Flavia Delicato, Nirmit Desai, Jing Fan, Geoffrey C. Fox, Andrzej Goscinski, Zhi Jin, Anna Kobusinska, Omer Rana (Eds.), Proceedings - IEEE International Conference on Edge Computing (pp. 43-50). Hybrid, Chicago, IL, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Ringlein, Burkhard, et al. "DOSA: Organic Compilation for Neural Network Inference on Distributed FPGAs." Proceedings of the 7th IEEE International Conference on Edge Computing and Communications, EDGE 2023, Hybrid, Chicago, IL, USA Ed. Claudio Ardagna, Feras Awaysheh, Hongyi Bian, Carl K. Chang, Rong N. Chang, Flavia Delicato, Nirmit Desai, Jing Fan, Geoffrey C. Fox, Andrzej Goscinski, Zhi Jin, Anna Kobusinska, Omer Rana, Institute of Electrical and Electronics Engineers Inc., 2023. 43-50.
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