2 research outputs found
RFaaS: RDMA-Enabled FaaS Platform for Serverless High-Performance Computing
The rigid MPI programming model and batch scheduling dominate
high-performance computing. While clouds brought new levels of elasticity into
the world of computing, supercomputers still suffer from low resource
utilization rates. To enhance supercomputing clusters with the benefits of
serverless computing, a modern cloud programming paradigm for pay-as-you-go
execution of stateless functions, we present rFaaS, the first RDMA-aware
Function-as-a-Service (FaaS) platform. With hot invocations and decentralized
function placement, we overcome the major performance limitations of FaaS
systems and provide low-latency remote invocations in multi-tenant
environments. We evaluate the new serverless system through a series of
microbenchmarks and show that remote functions execute with negligible
performance overheads. We demonstrate how serverless computing can bring
elastic resource management into MPI-based high-performance applications.
Overall, our results show that MPI applications can benefit from modern cloud
programming paradigms to guarantee high performance at lower resource costs