| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | March 1, 2019 |
| Latest Amendment Date: | May 23, 2023 |
| Award Number: | 1845853 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Deepankar Medhi
dmedhi@nsf.gov (703)292-2935 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | July 1, 2019 |
| End Date: | June 30, 2025 (Estimated) |
| Total Intended Award Amount: | $578,228.00 |
| Total Awarded Amount to Date: | $578,228.00 |
| Funds Obligated to Date: |
FY 2020 = $110,007.00 FY 2021 = $113,406.00 FY 2022 = $116,923.00 FY 2023 = $120,562.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1109 GEDDES AVE STE 3300 ANN ARBOR MI US 48109-1015 (734)763-6438 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3003 S. State St Ann Arbor MI US 48109-1274 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Networking Technology and Syst |
| Primary Program Source: |
01002021DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT 01002223DB NSF RESEARCH & RELATED ACTIVIT 01002324DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Applications in modern cloud datacenters are deployed in resource containers to isolate them from each other. Memory stranding is a pervasive problem in such containerized datacenters, where many memory-intensive applications grind to a halt even when free memory exists in other machines. This leads to low utilization, memory fragmentation, and overall increased cost. Memory disaggregation over ultra-fast networks can pool together such stranded memory in theory, but making it practical faces novel systems design, algorithmic, and integration challenges. They include bridging the still-sizable latency gap between local memory access vs. Remote Direct Memory Access (RDMA), transparently addressing network-wide fault-tolerance, load imbalance, and performance isolation issues, scalability, and enabling support for heterogeneous software and hardware technologies.
The overarching research objective of this proposal is to realize a Unified Disaggregated Memory (UDM) abstraction over ultra-fast networks to expose stranded memory across the datacenter as a pool of available memory to out-of-memory containers in a fast, resilient, and scalable manner without any changes to the applications. By designing a comprehensive solution to address host-level, network-level, and end-to-end aspects of the aforementioned challenges, this research aims to make memory disaggregation practical. Specifically, by leveraging the unique characteristics of memory-intensive workloads, ultra-low-latency networks, and multi-tenancy in modern datacenters, this proposal will (i) design a low-latency host networking stack; (ii) enable performance isolation throughout the network; (iii) provide resilience to network-wide uncertainties such as failures and load imbalance; and (iv) incorporate support for heterogeneous memory (e.g., persistent memory), networking technologies, and resource management software.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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