TY - GEN
T1 - Libra
T2 - 32nd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2023
AU - Yu, Hanfei
AU - Fontenot, Christian
AU - Wang, Hao
AU - Li, Jian
AU - Yuan, Xu
AU - Park, Seung Jong
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/8/7
Y1 - 2023/8/7
N2 - Serverless computing has been favored by users and infrastructure providers from various industries, including online services and scientific computing. Users enjoy its auto-scaling and ease-of-management, and providers own more control to optimize their service. However, existing serverless platforms still require users to pre-define resource allocations for their functions, leading to frequent misconfiguration by inexperienced users in practice. Besides, functions' varying input data further escalate the gap between their dynamic resource demands and static allocations, leaving functions either over-provisioned or under-provisioned. This paper presents Libra, a safe and timely resource harvesting framework for multi-node serverless clusters. Libra makes precise harvesting decisions to accelerate function invocations with harvested resources and jointly improve resource utilization by profiling dynamic resource demands and availability proactively. Experiments on OpenWhisk clusters with real-world workloads show that Libra reduces response latency by 39% and achieves 3X resource utilization compared to state-of-the-art solutions.
AB - Serverless computing has been favored by users and infrastructure providers from various industries, including online services and scientific computing. Users enjoy its auto-scaling and ease-of-management, and providers own more control to optimize their service. However, existing serverless platforms still require users to pre-define resource allocations for their functions, leading to frequent misconfiguration by inexperienced users in practice. Besides, functions' varying input data further escalate the gap between their dynamic resource demands and static allocations, leaving functions either over-provisioned or under-provisioned. This paper presents Libra, a safe and timely resource harvesting framework for multi-node serverless clusters. Libra makes precise harvesting decisions to accelerate function invocations with harvested resources and jointly improve resource utilization by profiling dynamic resource demands and availability proactively. Experiments on OpenWhisk clusters with real-world workloads show that Libra reduces response latency by 39% and achieves 3X resource utilization compared to state-of-the-art solutions.
KW - resource harvesting
KW - serverless computing
UR - http://www.scopus.com/inward/record.url?scp=85169604638&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85169604638&partnerID=8YFLogxK
U2 - 10.1145/3588195.3592996
DO - 10.1145/3588195.3592996
M3 - Conference contribution
AN - SCOPUS:85169604638
T3 - HPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing
SP - 181
EP - 194
BT - HPDC 2023 - Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing
Y2 - 16 June 2023 through 23 June 2023
ER -