TY - JOUR
T1 - Exploring Memory Access Similarity to Improve Irregular Application Performance for Distributed Hybrid Memory Systems
AU - Liu, Wenjie
AU - He, Xubin
AU - Liu, Qing
N1 - Funding Information:
This work was supported in part by the US National Science Foundation under Grants 2134203, 1828363, 1812861, 2134202, and 2144403.
Publisher Copyright:
© 1990-2012 IEEE.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - With the increasing problem complexity, more irregular applications are deployed on high-performance clusters due to the parallel working paradigm, and yield irregular memory access behaviors across nodes. However, the irregularity of memory access behaviors is not comprehensively studied, which results in low utilization of the integrated hybrid memory system compositing of stacked DRAM and off-chip DRAM. To address this problem, we devise a novel method called Similarity-Managed Hybrid Memory System (SM-HMS) to improve the hybrid memory system performance by leveraging the memory access similarity among nodes in a cluster. Within SM-HMS, two techniques are proposed, Memory Access Similarity Measuring and Similarity-based Memory Access Behavior Sharing. To quantify the memory access similarity, memory access behaviors of each node are vectorized, and the distance between two vectors is used as the memory access similarity. The calculated memory access similarity is used to share memory access behaviors precisely across nodes. With the shared memory access behaviors, SM-HMS divides the stacked DRAM into two sections, the sliding window section and the outlier section. The shared memory access behaviors guide the replacement of the sliding window section while the outlier section is managed in the LRU manner. Our evaluation results with a set of irregular applications on various clusters consisting of up to 256 nodes have shown that SM-HMS outperforms the state-of-the-art approaches, Cameo, Chameleon, and Hyrbid2, on job finish time reduction by up to 58.6%, 56.7%, and 31.3%, with 46.1%, 41.6%, and 19.3% on average, respectively. SM-HMS can also achieve up to 98.6% (91.9% on average) of the ideal hybrid memory system performance.
AB - With the increasing problem complexity, more irregular applications are deployed on high-performance clusters due to the parallel working paradigm, and yield irregular memory access behaviors across nodes. However, the irregularity of memory access behaviors is not comprehensively studied, which results in low utilization of the integrated hybrid memory system compositing of stacked DRAM and off-chip DRAM. To address this problem, we devise a novel method called Similarity-Managed Hybrid Memory System (SM-HMS) to improve the hybrid memory system performance by leveraging the memory access similarity among nodes in a cluster. Within SM-HMS, two techniques are proposed, Memory Access Similarity Measuring and Similarity-based Memory Access Behavior Sharing. To quantify the memory access similarity, memory access behaviors of each node are vectorized, and the distance between two vectors is used as the memory access similarity. The calculated memory access similarity is used to share memory access behaviors precisely across nodes. With the shared memory access behaviors, SM-HMS divides the stacked DRAM into two sections, the sliding window section and the outlier section. The shared memory access behaviors guide the replacement of the sliding window section while the outlier section is managed in the LRU manner. Our evaluation results with a set of irregular applications on various clusters consisting of up to 256 nodes have shown that SM-HMS outperforms the state-of-the-art approaches, Cameo, Chameleon, and Hyrbid2, on job finish time reduction by up to 58.6%, 56.7%, and 31.3%, with 46.1%, 41.6%, and 19.3% on average, respectively. SM-HMS can also achieve up to 98.6% (91.9% on average) of the ideal hybrid memory system performance.
KW - Cluster
KW - DRAM
KW - hybrid memory system
KW - irregular application
KW - memory system
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U2 - 10.1109/TPDS.2022.3227544
DO - 10.1109/TPDS.2022.3227544
M3 - Article
AN - SCOPUS:85144786513
SN - 1045-9219
VL - 34
SP - 797
EP - 809
JO - IEEE Transactions on Parallel and Distributed Systems
JF - IEEE Transactions on Parallel and Distributed Systems
IS - 3
ER -