Chiplet Heterogeneity And Advanced Scheduling With Pipelining


A technical paper titled “Inter-Layer Scheduling Space Exploration for Multi-model Inference on Heterogeneous Chiplets” was published by researchers at University of California Irvine.


“To address increasing compute demand from recent multi-model workloads with heavy models like large language models, we propose to deploy heterogeneous chiplet-based multi-chip module (MCM)-based accelerators. We develop an advanced scheduling framework for heterogeneous MCM accelerators that comprehensively consider complex heterogeneity and inter-chiplet pipelining. Our experiments using our framework on GPT-2 and ResNet-50 models on a 4-chiplet system have shown up to 2.2x and 1.9x increase in throughput and energy efficiency, compared to a monolithic accelerator with an optimized output-stationary dataflow.”

Find the technical paper here. Published December 2023 (preprint).

Odema, Mohanad, Hyoukjun Kwon, and Mohammad Abdullah Al Faruque. “Inter-Layer Scheduling Space Exploration for Multi-model Inference on Heterogeneous Chiplets.” arXiv preprint arXiv:2312.09401 (2023).

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