SPNC: An Open-Source MLIR-Based Compiler for Fast Sum-Product Network Inference on CPUs and GPUs-Reference-Cited by-同舟云学术

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SPNC: An Open-Source MLIR-Based Compiler for Fast Sum-Product Network Inference on CPUs and GPUs

Published:2022-04-02 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
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Author:

Sommer Lukas¹,Axenie Cristian²,Koch Andreas¹

Affiliation:

1. Embedded Systems and Applications Group, TU Darmstadt,Germany

2. Intelligent Cloud Technologies Laboratory,Huawei Munich Research Center,Munich,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9741235/9741095/09741277.pdf?arnumber=9741277

Reference17 articles.

1. Evolutionary multi-level acyclic graph partitioning

2. Sum-Product Networks for Robust Automatic Speaker Identification

3. Spn-asi;nicolson,2020

4. Random sum-product networks: A simple but effective approach to probabilistic deep learning;peharz;Proceedings of UAI,2019

5. Rat-spn;peharz,2019

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Lifting Code Generation of Cardiac Physiology Simulation to Novel Compiler Technology;Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization;2023-02-17

2. GPU Code Generation of Cardiac Electrophysiology Simulation with MLIR;Euro-Par 2023: Parallel Processing;2023

3. Programming Autonomous Machines : Special Session Paper;2022 International Conference on Embedded Software (EMSOFT);2022-10

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