DCC is a data-centric compiler that co-optimizes data partitioning strategies with compute loop partitioning for ML kernels on multiple PIM architectures, reporting up to 13.17x speedup on AttAcc PIM and 4.52x average for LLM inference over GPU.
Op- tiPIM: Optimizing Processing-in-Memory Acceleration Using Integer Linear Programming
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AR 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures
DCC is a data-centric compiler that co-optimizes data partitioning strategies with compute loop partitioning for ML kernels on multiple PIM architectures, reporting up to 13.17x speedup on AttAcc PIM and 4.52x average for LLM inference over GPU.