Pythia: Scheduling of Concurrent Network Packet Processing Applications on Heterogeneous Devices

Abstract

Modern commodity computing systems are composed of a number of heterogeneous processing units, each one with its own unique performance and energy characteristics. However, the majority of current network packet processing frameworks targets only one device (either the CPU or an accelerator), leaving the remaining computational resources underutilized or even idle. In this paper, we propose an adaptive scheduling approach for network packet processing applications that exploits any heterogeneous architecture that can be found in a commodity high-end hardware setup. Our scheduler not only distributes the workloads to the appropriate devices in the system to achieve the desired performance results, but also enables the multiplexing of diverse, concurrently executed network packet processing applications, eliminating the interference effects introduced at run-time. The evaluation results show that our scheduler is able to tackle any interference in the shared hardware resources as well to respond quickly to dynamic fluctuations (e.g., application overloads, traffic bursts, infrastructural changes, etc.) that may occur at real time.