A message-driven mapping framework for VGG-19 inference on the MAVeC accelerator is claimed to generate over 97% of messages on-chip and sustain 88-92% SiteO utilization in simulation.
hub
DaDianNao: A Machine-Learning Supercomputer,
1 Pith paper cite this work, alongside 1,508 external citations. Polarity classification is still indexing.
1
Pith paper citing it
1,508
external citations · OpenAlex
hub tools
citation-role summary
background 1
citation-polarity summary
fields
cs.AR 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Hardware-Aware Data and Instruction Mapping for AI Tasks: Balancing Parallelism, I/O and Memory Tradeoffs
A message-driven mapping framework for VGG-19 inference on the MAVeC accelerator is claimed to generate over 97% of messages on-chip and sustain 88-92% SiteO utilization in simulation.