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FaaSter: Accelerated Functions-as-a-Service with Heterogeneous GPUs
Journal
Proceedings - 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics, HiPC 2021
Date Issued
2021-01-01
Author(s)
Garg, Anshuj
Kulkarni, Purushottam
Bellur, Umesh
Yenamandra, Sriram
Abstract
In this work, we present FaaSter, an Accelerated Functions as a Service (AFaaS) offering that unifies the function-as-a-service model with GPU acceleration resources. FaaSter provides an acceleration function library as a service, which in turn is provisioned on heterogeneous GPUs. To provide seamless access to these accelerated functions and ensure that each function has the best possible response time, we utilize GPU kernel slicing to split and execute an accelerated function instance across multiple heterogeneous GPUs. The central challenge is to be able to quickly decide the number of slices to split each function into and then map the slices to the right GPUs. To this end, we present a scheduling heuristic that is able to significantly reduce the average turn-around time of functions when compared to a non-sliceable full GPU scheduling approach. Our evaluation results show that the FaaSter scheduler achieves 62 % mean and up to 80 % improvement in average turn-around time and always performs equal to or better than non-sliceable GPU scheduling.
Subjects