Acceleration-as-a-{\mu}Service: A Cloud-native Monte-Carlo Option Pricing Engine on CPUs, GPUs and Disaggregated FPGAs

Beat Weiss; Burkhard Ringlein; Christoph Hagleitner; Dionysios Diamantopoulos; Francois Abel; Mark Lantz; Mitra Purandare; Raphael Polig

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Acceleration-as-a-{\mu}Service: A Cloud-native Monte-Carlo Option Pricing Engine on CPUs, GPUs and Disaggregated FPGAs

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arxiv 2106.06293 v1 pith:KPNFQXZH submitted 2021-06-11 cs.NI cs.ARcs.DC

Dionysios Diamantopoulos , Raphael Polig , Burkhard Ringlein , Mitra Purandare , Beat Weiss , Christoph Hagleitner , Mark Lantz , Francois Abel This is my paper · ORCID

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keywords cloudacceleratorsframeworkmicroservicesserviceworkloadacceleration-as-a-accelerator

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The evolution of cloud applications into loosely-coupled microservices opens new opportunities for hardware accelerators to improve workload performance. Existing accelerator techniques for cloud sacrifice the consolidation benefits of microservices. This paper presents CloudiFi, a framework to deploy and compare accelerators as a cloud service. We evaluate our framework in the context of a financial workload and present early results indicating up to 485x gains in microservice response time.

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