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COREY scheduler optimizes Mamba SSMs but static tuning remains faster

By PulseAugur Editorial · [1 sources] ·

Researchers have developed COREY, a new runtime scheduler designed to optimize the performance of Mamba selective state space models (SSMs). COREY maps activation entropy to chunk sizes, aiming to improve the efficiency of selective-scan kernels. While COREY demonstrated significant latency reductions at the kernel level, achieving up to 4.41x improvement on consumer GPUs, its end-to-end performance did not surpass static chunk tuning due to scheduling overhead. AI

IMPACT COREY demonstrates potential for optimizing SSM performance, though current implementations show static tuning remains competitive.

RANK_REASON This is a research paper detailing a new scheduling method for Mamba SSMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COREY scheduler optimizes Mamba SSMs but static tuning remains faster

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This is a research paper detailing a new scheduling method for Mamba SSMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Bo Ma, Jinsong Wu, Weiqi Yan ·

    COREY: Entropy-Guided Runtime Chunk Scheduling for Selective Scan Kernels

    arXiv:2604.10597v3 Announce Type: replace Abstract: Mamba selective state space models (SSMs) provide linear-time sequence modeling but remain sensitive to selective-scan chunk scheduling. We present COREY, a \emph{concept-and-feasibility} runtime scheduler that maps fixed-bin ac…

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