The IX Operating System Project: Energy Proportionality and Workload Consolidation for Latency-Critical Applications
Speaker(s) : Édouar BUGNION (EPFL)The conventional wisdom is that aggressive networking requirements, such as high packet rates for small messages and microsecond-scale tail latency, are best addressed outside the kernel, in a user-level networking stack. We present IX, a dataplane operating system that provides high I/O performance, while maintaining the key advantage of strong protection offered by existing kernels. IX uses hardware virtualization to separate management and scheduling functions of the kernel (control plane) from network processing (dataplane). The dataplane architecture builds upon a native, zero-copy API and optimizes for both bandwidth and latency by dedicating hardware threads and networking queues to dataplane instances, processing bounded batches of packets to completion, and by eliminating coherence traffic and multi-core synchronization. The control plane adjusts core allocation and voltage/frequency settings based on the measured delays for latency-critical workloads. This allows for energy proportionality and frees the maximum amount of resources per server for other background applications, while respecting service-level objectives.
We demonstrate that IX outperforms Linux and state-of-the-art, user-space network stacks significantly in both throughput and end-to-end latency. Moreover, IX improves the throughput of a widely deployed, key-value store by up to 3.6x and reduces tail latency by more than 2x. We compare the efficiency of our solution to the Pareto-optimal frontier of 224 distinct static configurations. Dynamic resource control saves 44%–54% of processor energy, which corresponds to 85%–93% of the Pareto-optimal upper bound. Dynamic resource control also allows background jobs to run at 32%–46% of their standalone throughput, which corresponds to 82%–92% of the Pareto bound.
Joint work with Adam Belay, George Prekas, Mia Primorac, Ana Klimovic, Samuel Grossman, and Christos Kozyrakis. Published at OSDI 14 (Best Paper Award) and SoCC ’15.
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