A GPU-sharing framework that dynamically resizes Nvidia MIG partitions and predicts memory growth achieves up to 6.2x throughput and 5.9x energy improvements on batches of scientific and ML jobs.
CASE: a compiler-assisted scheduling framework for multi-gpu systems
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.DC 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Managing Multi Instance GPUs for High Throughput and Energy Savings
A GPU-sharing framework that dynamically resizes Nvidia MIG partitions and predicts memory growth achieves up to 6.2x throughput and 5.9x energy improvements on batches of scientific and ML jobs.