Name
Title | ||
|---|---|---|
SPNC: An Open-Source MLIR-Based Compiler for Fast Sum-Product Network Inference on CPUs and GPUs |
Abstract | ||
|---|---|---|
Sum-Product Networks (SPNs) are an alternative to the widely used Neural Networks (NNs) for machine learning. SPNs can not only reason about (un)certainty by qualifying their output with a probability, they also allow fast (tractable) inference by having run-times that are just linear w.r.t. the network size.We present SPNC, the first tool flow for generating fast native code for SPN inference on ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/CGO53902.2022.9741277 | 2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) |
Keywords | DocType | ISSN |
Training,Codes,Semantics,Graphics processing units,Machine learning,Libraries,Task analysis | Conference | 2164-2397 |
ISBN | Citations | PageRank |
978-1-6654-0584-3 | 2 | 0.40 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukas Sommer | 1 | 8 | 7.53 |
| Cristian Axenie | 2 | 2 | 0.40 |
| Andreas Koch | 3 | 94 | 15.13 |