Projects per year
Abstract
In the quest for more advanced and energy-efficient edge AI, probabilistic reasoning models can complement or replace deep learning (DL) models, as they are generative, explainable, and trustworthy. However, their hardware implementation and acceleration are still in the early stages compared to DL due to more ad-hoc implementations and challenges translating them into computational steps. This recently evolved with Probabilistic Circuits (PCs), which can be trained with mainstream software and lead to more hardware-efficient inference. Yet, there is currently no single open-source framework dedicated to computing PCs on hardware. In this work, we introduce such a framework called AutoPC, allowing us to (1) compare PCs trained with different PC algorithms to find the most suited, (2) find the optimal resolution required for hardware computation with minimal cost, and (3) automatically generate FPGA hardware for executing PC models with high speed (40-200 GOPS) up to the FPGA capacity. We hope AutoPC serves as a baseline to showcase the possibilities of probabilistic reasoning and broaden the use of PCs.
Original language | English |
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Title of host publication | 2024 22nd IEEE Interregional NEWCAS Conference, NEWCAS 2024 |
Publisher | IEEE |
Pages | 21-25 |
Number of pages | 5 |
ISBN (Electronic) | 979-8-3503-6175-9 |
DOIs | |
Publication status | Published - 2024 |
MoE publication type | A4 Conference publication |
Event | IEEE International New Circuits and Systems Conference - Sherbrooke, Canada Duration: 16 Jun 2024 → 19 Jun 2024 Conference number: 22 |
Publication series
Name | IEEE International New Circuits and Systems Conference |
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ISSN (Electronic) | 2474-9672 |
Conference
Conference | IEEE International New Circuits and Systems Conference |
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Abbreviated title | NEWCAS |
Country/Territory | Canada |
City | Sherbrooke |
Period | 16/06/2024 → 19/06/2024 |
Keywords
- Design Automation
- High level HW-Simulation
- HW-SW co-design
- Probablistic Circuits
Fingerprint
Dive into the research topics of 'AutoPC: An Open-Source Framework for Efficient Probabilistic Reasoning on FPGA Hardware'. Together they form a unique fingerprint.Projects
- 1 Finished
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WHISTLE: When integrated systems gain life experience: towards self-learning circuits with resource-efficient embedded artificial intelligence
Andraud, M. (Principal investigator), Adam, K. (Project Member), Yao, L. (Project Member), Periasamy, K. (Project Member), Leslin, J. (Project Member) & Bhowmick, S. (Project Member)
01/09/2020 → 31/08/2024
Project: Academy of Finland: Other research funding
Equipment
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Aalto Electronics-ICT
Ryynänen, J. (Manager)
Department of Electronics and NanoengineeringFacility/equipment: Facility