PROPACK: Executing Concurrent Serverless Functions Faster and Cheaper

被引:7
作者
Basu, Rohan [1 ]
Patel, Tirthak [2 ]
Liew, Richmond [1 ]
Babuji, Yadu Nand [3 ]
Chard, Ryan [3 ]
Tiwari, Devesh [1 ]
机构
[1] Northeastern Univ, Boston, MA 02115 USA
[2] Rice Univ, Houston, TX 77251 USA
[3] Argonne Natl Lab, Argonne, IL 60439 USA
来源
PROCEEDINGS OF THE 32ND INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE PARALLEL AND DISTRIBUTED COMPUTING, HPDC 2023 | 2023年
关键词
Serverless Computing; Cloud Computing; Scalability;
D O I
10.1145/3588195.3592988
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The serverless computing model has been on the rise in recent years due to a lower barrier to entry and elastic scalability. However, our experimental evidence suggests that multiple serverless computing platforms suffer from serious performance inefficiencies when a high number of concurrent function instances are invoked, which is a desirable capability for parallel applications. To mitigate this challenge, this paper introduces ProPack, a novel solution that provides higher performance and yields cost savings for end users running applications with high concurrency. ProPack leverages insights obtained from experimental study to build a simple and effective analytical model that mitigates the scalability bottleneck. Our evaluation on multiple serverless platforms including AWS Lambda and Google confirms that ProPack can improve average performance by 85% and save cost by 66%. ProPack provides significant improvement (over 50%) over the state-of-the-art serverless workload manager such as Pywren, and is also, effective at mitigating the concurrency bottleneck for FuncX, a recent on-premise serverless execution platform for parallel applications.
引用
收藏
页码:211 / 224
页数:14
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