Publications by Jongmoo Choi

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2017

Proceedins of the 2017 IEEE International Conference on Cluster Computing (CLUSTER), Honolulu, HI, USA, September 2017
While the memory footprints of cloud and HPC applications continue to increase, fundamental issues with DRAM scaling are likely to prevent traditional main memory systems, composed of monolithic DRAM, from greatly growing in capacity. Hybrid memory systems can mitigate the scaling limitations of monolithic DRAM by pairing together multiple memory technologies (e.g., different types of DRAM, or DRAM and non-volatile memory) at the same level of the memory hierarchy. The goal of a hybrid main memory is to combine the different advantages of the multiple memory types in a cost-effective manner while avoiding the disadvantages of each technology. Memory pages are placed in and migrated between the different memories within a hybrid memory system, based on the properties of each page. It is important to make intelligent page management (i.e., placement and migration) decisions, as they can significantly affect system performance.In this paper, we propose utility-based hybrid memory management (UH-MEM), a new page management mechanism for various hybrid memories, that systematically estimates the utility (i.e., the system performance benefit) of migrating a page between different memory types, and uses this information to guide data placement. UH-MEM operates in two steps. First, it estimates how much a single application would benefit from migrating one of its pages to a different type of memory, by comprehensively considering access frequency, row buffer locality, and memory-level parallelism. Second, it translates the estimated benefit of a single application to an estimate of the overall system performance benefit from such a migration.We evaluate the effectiveness of UH-MEM with various types of hybrid memories, and show that it significantly improves system performance on each of these hybrid memories. For a memory system with DRAM and non-volatile memory, UH-MEM improves performance by 14% on average (and up to 26%) compared to the best of three evaluated state-of-the-art mechanisms across a large number of data-intensive workloads.
@inproceedings{abc,
	abstract = {While the memory footprints of cloud and HPC applications continue to increase, fundamental issues with DRAM scaling are likely to prevent traditional main memory systems, composed of monolithic DRAM, from greatly growing in capacity. Hybrid memory systems can mitigate the scaling limitations of monolithic DRAM by pairing together multiple memory technologies (e.g., different types of DRAM, or DRAM and non-volatile memory) at the same level of the memory hierarchy. The goal of a hybrid main memory is to combine the different advantages of the multiple memory types in a cost-effective manner while avoiding the disadvantages of each technology. Memory pages are placed in and migrated between the different memories within a hybrid memory system, based on the properties of each page. It is important to make intelligent page management (i.e., placement and migration) decisions, as they can significantly affect system performance.In this paper, we propose utility-based hybrid memory management (UH-MEM), a new page management mechanism for various hybrid memories, that systematically estimates the utility (i.e., the system performance benefit) of migrating a page between different memory types, and uses this information to guide data placement. UH-MEM operates in two steps. First, it estimates how much a single application would benefit from migrating one of its pages to a different type of memory, by comprehensively considering access frequency, row buffer locality, and memory-level parallelism. Second, it translates the estimated benefit of a single application to an estimate of the overall system performance benefit from such a migration.We evaluate the effectiveness of UH-MEM with various types of hybrid memories, and show that it significantly improves system performance on each of these hybrid memories. For a memory system with DRAM and non-volatile memory, UH-MEM improves performance by 14\% on average (and up to 26\%) compared to the best of three evaluated state-of-the-art mechanisms across a large number of data-intensive workloads.},
	author = {Yang Li and Saugata Ghose and Jongmoo Choi and Jin Sun and Hui Wang and Onur Mutlu},
	booktitle = {Proceedins of the 2017 IEEE International Conference on Cluster Computing (CLUSTER)},
	title = {Utility-Based Hybrid Memory Management},
	venue = {Honolulu, HI, USA},
	year = {2017}
}

2015

Proceedings of the 48th International Symposium on Microarchitecture, MICRO 2015, Waikiki, HI, USA, December 2015
@inproceedings{abc,
	author = {Jinglei Ren and Jishen Zhao and Samira Manabi Khan and Jongmoo Choi and Yongwei Wu and Onur Mutlu},
	booktitle = {Proceedings of the 48th International Symposium on Microarchitecture, MICRO 2015, Waikiki, HI, USA},
	title = {ThyNVM: enabling software-transparent crash consistency in persistent memory systems.},
	url = {http://doi.acm.org/10.1145/2830772.2830802},
	year = {2015}
}
2015 International Conference on Parallel Architecture and Compilation, PACT 2015, San Francisco, CA, USA, October 2015
@inproceedings{abc,
	author = {Donghyuk Lee and Lavanya Subramanian and Rachata Ausavarungnirun and Jongmoo Choi and Onur Mutlu},
	booktitle = {2015 International Conference on Parallel Architecture and Compilation, PACT 2015, San Francisco, CA, USA},
	title = {Decoupled Direct Memory Access: Isolating CPU and IO Traffic by Leveraging a Dual-Data-Port DRAM.},
	url = {http://dx.doi.org/10.1109/PACT.2015.51},
	year = {2015}
}
IEEE 31st Symposium on Mass Storage Systems and Technologies, MSST 2015, Santa Clara, CA, USA, May 2015
@inproceedings{abc,
	author = {Yixin Luo and Yu Cai and Saugata Ghose and Jongmoo Choi and Onur Mutlu},
	booktitle = {IEEE 31st Symposium on Mass Storage Systems and Technologies, MSST 2015, Santa Clara, CA, USA},
	title = {WARM: Improving NAND flash memory lifetime with write-hotness aware retention management.},
	url = {http://dx.doi.org/10.1109/MSST.2015.7208284},
	year = {2015}
}
IEEE 31st Symposium on Mass Storage Systems and Technologies, MSST 2015, Santa Clara, CA, USA, May 2015
@inproceedings{abc,
	author = {Dongwoo Kang and Seungjae Baek and Jongmoo Choi and Donghee Lee and Sam H. Noh and Onur Mutlu},
	booktitle = {IEEE 31st Symposium on Mass Storage Systems and Technologies, MSST 2015, Santa Clara, CA, USA},
	title = {Amnesic cache management for non-volatile memory.},
	url = {http://dx.doi.org/10.1109/MSST.2015.7208291},
	year = {2015}
}
Proceedings of the 11th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, Istanbul, Turkey, March 2015
@inproceedings{abc,
	author = {Hui Wang and Canturk Isci and Lavanya Subramanian and Jongmoo Choi and Depei Qian and Onur Mutlu},
	booktitle = {Proceedings of the 11th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, Istanbul, Turkey},
	title = {A-DRM: Architecture-aware Distributed Resource Management of Virtualized Clusters.},
	url = {http://doi.acm.org/10.1145/2731186.2731202},
	year = {2015}
}
CoRR, January 2015
@article{abc,
	author = {Yang Li and Jongmoo Choi and Jin Sun and Saugata Ghose and Hui Wang and Justin Meza and Jinglei Ren and Onur Mutlu},
	journal = {CoRR},
	title = {Managing Hybrid Main Memories with a Page-Utility Driven Performance Model.},
	url = {http://arxiv.org/abs/1507.03303},
	year = {2015}
}