تقرير
ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model
العنوان: | ICGMM: CXL-enabled Memory Expansion with Intelligent Caching Using Gaussian Mixture Model |
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المؤلفون: | Chen, Hanqiu, Wang, Yitu, Cargnini, Luis Vitorio, Soltaniyeh, Mohammadreza, Li, Dongyang, Sun, Gongjin, Subedi, Pradeep, Chang, Andrew, Chen, Yiran, Hao, Cong |
سنة النشر: | 2024 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Hardware Architecture, Computer Science - Emerging Technologies, Electrical Engineering and Systems Science - Systems and Control |
الوصف: | Compute Express Link (CXL) emerges as a solution for wide gap between computational speed and data communication rates among host and multiple devices. It fosters a unified and coherent memory space between host and CXL storage devices such as such as Solid-state drive (SSD) for memory expansion, with a corresponding DRAM implemented as the device cache. However, this introduces challenges such as substantial cache miss penalties, sub-optimal caching due to data access granularity mismatch between the DRAM "cache" and SSD "memory", and inefficient hardware cache management. To address these issues, we propose a novel solution, named ICGMM, which optimizes caching and eviction directly on hardware, employing a Gaussian Mixture Model (GMM)-based approach. We prototype our solution on an FPGA board, which demonstrates a noteworthy improvement compared to the classic Least Recently Used (LRU) cache strategy. We observe a decrease in the cache miss rate ranging from 0.32% to 6.14%, leading to a substantial 16.23% to 39.14% reduction in the average SSD access latency. Furthermore, when compared to the state-of-the-art Long Short-Term Memory (LSTM)-based cache policies, our GMM algorithm on FPGA showcases an impressive latency reduction of over 10,000 times. Remarkably, this is achieved while demanding much fewer hardware resources. Comment: This paper is accepted by DAC2024 |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2408.05614 |
رقم الأكسشن: | edsarx.2408.05614 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |