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.
McPAL: Scaling Un- structured Sparse Inference with Multi-Chiplet HBM-PIM Architecture for LLMs
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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.