Abstract
In-network computing accelerates applications natively running on the host by executing them within network devices. While in-network computing offers significant performance improvements, its limitations and design trade-offs have not been explored. To usefully and efficiently run applications within the network, we first need to understand the implications of their design. In this work we introduce LaKe, a Layered Key-Value Store design, running as an in-network application. LaKe is a scalable design, enabling the exploration of design decisions and their effect on throughput, latency and power efficiency. LaKe achieves full line rate throughput, while maintaining a latency of 1.1 μs and better power efficiency than existing hardware based memcached designs.
| Original language | English |
|---|---|
| Title of host publication | 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018 |
| Editors | David Andrews, Claudia Feregrino, Rene Cumplido, Dirk Stroobandt |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728119687 |
| DOIs | |
| Publication status | Published - 2019 Feb 13 |
| Event | 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018 - Cancun, Mexico Duration: 2018 Dec 3 → 2018 Dec 5 |
Publication series
| Name | 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018 |
|---|
Conference
| Conference | 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018 |
|---|---|
| Country | Mexico |
| City | Cancun |
| Period | 18/12/3 → 18/12/5 |
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Keywords
- Energy Efficiency
- FPGA
- In-network computing
- Key-value store
ASJC Scopus subject areas
- Hardware and Architecture
- Software
Cite this
LaKe : The power of in-network computing. / Tokusashi, Yuta; Matsutani, Hiroki; Zilberman, Noa.
2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018. ed. / David Andrews; Claudia Feregrino; Rene Cumplido; Dirk Stroobandt. Institute of Electrical and Electronics Engineers Inc., 2019. 8641696 (2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - LaKe
T2 - The power of in-network computing
AU - Tokusashi, Yuta
AU - Matsutani, Hiroki
AU - Zilberman, Noa
PY - 2019/2/13
Y1 - 2019/2/13
N2 - In-network computing accelerates applications natively running on the host by executing them within network devices. While in-network computing offers significant performance improvements, its limitations and design trade-offs have not been explored. To usefully and efficiently run applications within the network, we first need to understand the implications of their design. In this work we introduce LaKe, a Layered Key-Value Store design, running as an in-network application. LaKe is a scalable design, enabling the exploration of design decisions and their effect on throughput, latency and power efficiency. LaKe achieves full line rate throughput, while maintaining a latency of 1.1 μs and better power efficiency than existing hardware based memcached designs.
AB - In-network computing accelerates applications natively running on the host by executing them within network devices. While in-network computing offers significant performance improvements, its limitations and design trade-offs have not been explored. To usefully and efficiently run applications within the network, we first need to understand the implications of their design. In this work we introduce LaKe, a Layered Key-Value Store design, running as an in-network application. LaKe is a scalable design, enabling the exploration of design decisions and their effect on throughput, latency and power efficiency. LaKe achieves full line rate throughput, while maintaining a latency of 1.1 μs and better power efficiency than existing hardware based memcached designs.
KW - Energy Efficiency
KW - FPGA
KW - In-network computing
KW - Key-value store
UR - http://www.scopus.com/inward/record.url?scp=85063158727&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063158727&partnerID=8YFLogxK
U2 - 10.1109/RECONFIG.2018.8641696
DO - 10.1109/RECONFIG.2018.8641696
M3 - Conference contribution
AN - SCOPUS:85063158727
T3 - 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018
BT - 2018 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2018
A2 - Andrews, David
A2 - Feregrino, Claudia
A2 - Cumplido, Rene
A2 - Stroobandt, Dirk
PB - Institute of Electrical and Electronics Engineers Inc.
ER -