cs.ET · 2026-07-07 · No. 46

Emerging Technologies, 2026-07-07.

1 new papers in cs.ET. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

1 entries
  1. 01

    Optimizing ML Workload Partitioning between CPUs and CIM Accelerators for Heterogeneous Computing

    Joel Klein, Rebecca Pelke, Roberto Laudani, Jan Moritz Joseph, Rainer Leupers

    cs.ET · cs.AI · cs.AR · cs.DC · cs.LG

    Computing-in-Memory (CIM) accelerators execute Matrix-Vector Multiplications (MVMs) in memory, making them a compelling solution for Machine Learning (ML) workloads. However, existing ML workload partitioning approaches for CIM accelerators do not fully account for Resistive Random Access Memory (RRAM) constraints such as limited memory, high write latency, and limited endurance. They also neglect parallelism, low-level architectural effects,...

    arxiv.org/abs/2607.05240 · PDF

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