PhD Seminar • Systems and Networking — Nessie: A Decoupled, Client-Driven Key-Value Store Using RDMAExport this event to calendar

Friday, June 28, 2019 — 1:30 PM EDT

Ben Cassell, PhD candidate
David R. Cheriton School of Computer Science

Key-value storage systems are an integral part of many data centre applications, but as demand increases so does the need for high performance. This has motivated new designs that use Remote Direct Memory Access (RDMA) to reduce communication overhead. Current RDMA-enabled key-value stores (RKVSes) target workloads involving small values, running on dedicated servers on which no other applications are running. Outside of these domains, however, there may be other RKVS designs that provide better performance. 

In this paper, we introduce Nessie, an RKVS that is fully client-driven, meaning no server process is involved in servicing requests. Nessie also decouples its index and storage data structures, allowing indices and data to be placed on different servers. This flexibility can decrease the number of network operations required to service a request. These design elements make Nessie well-suited for a different set of workloads than existing RKVSes. Compared to a server-driven RKVS, Nessie more than doubles system throughput when there is CPU contention on the server, improves throughput by 70% for PUT-oriented workloads when data value sizes are 128 KB or larger, and reduces power consumption by 18% at 80% system utilization and 41% at 20% system utilization compared with idle power consumption.

Location 
DC - William G. Davis Computer Research Centre
1304
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

S M T W T F S
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
1
2
3
4
5
  1. 2019 (196)
    1. October (3)
    2. September (20)
    3. August (18)
    4. July (12)
    5. June (23)
    6. May (23)
    7. April (32)
    8. March (25)
    9. February (16)
    10. January (24)
  2. 2018 (220)
    1. December (16)
    2. November (19)
    3. October (26)
    4. September (22)
    5. August (17)
    6. July (20)
    7. June (13)
    8. May (25)
    9. April (34)
    10. March (24)
    11. February (3)
    12. January (1)
  3. 2017 (36)
  4. 2016 (21)
  5. 2015 (36)
  6. 2014 (33)
  7. 2013 (23)
  8. 2012 (4)
  9. 2011 (1)
  10. 2010 (1)
  11. 2009 (1)
  12. 2008 (1)